Process safety risk, cyber security risk and societal risk

Introduction

I wanted my next blog to be a blog on quantitative risk estimation using the TRITON attack scenario, published by MITRE Engenuity some months ago, as the example for an estimation. But as I started writing the blog I kind of got lost in side notes to explain the choices made.

Topics such as the difference between threat based risk and asset based risk, the regulations around societal risk, conditional likelihood, repeatable events, dependent and independent events, and threat analysis levels slipped in the text making it a blog even longer than usual for me. But it are all elements that play an important role in quantitative risk analysis and require some level of understanding to understand the estimation method.

So I decided to split the blog into multiple blogs and discuss some of these topics as separate blogs before publishing the blog on the TRITON / TRISIS risk. The first topic I like to discuss is societal risk and how this impacts process safety and most of all how it can impact cyber security risk criteria. But let’s start with process safety and its relationship with societal risk.

Process Safety risk and Societal risk

Societal risk is not an easy topic to discuss because it has a direct relationship to the law in a country. As such, there are differences between countries. Words can become very important, even ALARP can mean different things in different countries and some countries don’t even follow ALARP but work with ALARA only the difference of one word from Practical to Achievable, but a world of difference in the court room. In this blog I focus on Europe, although I encountered similar regulations in the countries of the Middle East and also saw examples in Asia and expect them to be in the US too.

Societal risk has a direct relationship with process safety and as such there is an indirect relationship with cybersecurity. Cybersecurity as one of the enablers of the functional safety task in a production installation such as a chemical factory or refinery.

The topic of quantitative risk analysis and its criteria is discussed in great detail in the CCPS (Center for Chemical Process Safety) publication “Guidelines for developing quantitative safety risk criteria”, actually a must read for OT cyber risk professionals. Though published in 2009, so before the StuxNet (2010) and TRITON/TRISIS (2017) cyber security incidents – therefore no reference to cyber security risk, the principles discussed are still relevant today.

The StuxNet attack showed us the vulnerability of production processes for cyber attacks and the TRITON/TRISIS attack showed us that the process safety function is not necessarily guaranteed during such a cyber attack. So societal risk caused by cyber attacks should be high on our agenda, however it is not.

Regulations of governments set risk criteria that apply to the impact a production process “may” have on individuals or a group of people. Regulations focus on the impact and how frequent it occurs, the cause of this impact is not relevant. This cause can be either a random failure in the production installation or an intentional failure caused by a cyber attack. The societal risk criteria of the law don’t differentiate between the two.

Since zero risk does not exist, we can only reduce the likelihood (the frequency of the occurrence) that a specific harmful event occurs. Preventing it to occur by elimination (risk avoidance) would mean abandoning the production process. We sometimes do this, for example Germany abandoned nuclear power generation, but most often we attempt to reduce the likelihood to lower the risk. The law has specified average event frequencies that set limits for the likelihood of these events, these limits are guiding the process safety design of a production facility but now also set requirements for the cyber security design if we consider loss based risk.

The relationship between societal risk and process safety risk.

Let’s first define risk, the CCPS definition of risk is:

“Risk is a measure of human injury, environmental damage, or economic loss in terms of both the incident likelihood and the magnitude of the loss”

The criteria for each are specified differently with so far a strong focus of the regulations on human injury and environmental damage. Though the recent wave of ransomware attacks has also shifted government attention toward economic loss, but there are no limits set. My focus in the blog is human injury, so process safety.

Let’s consider a simplified imaginary process safety scenario. We have a reactor that needs cooling to prevent a run-away reaction if the temperature is too high, a run-away reaction that would build-up pressure to a level that might cause an explosion or a loss of containment of a hazardous (perhaps flammable) vapor that can cause multiple fatalities. This cooling is provided by a jacket filled with water, water that is supplied and circulated by a pump.

This type of scenario is quite common. A potential cause for creating such a run-away reaction would be the failure of the pump, a pump failure would stop the circulation of the cooling water allowing the reactor to heat up with the potential run-away reaction. The plant’s process safety design has set a target that requires reducing the likelihood of such an event happening to 1 event per 10.000 year. If we know the average event frequency of the pump failure we can consider additional risk reduction controls that reduce the likelihood to the 1E-04 limit. The process for estimating such risk reduction is LOPA (Layer Of Protection Analysis), a quantitative method for process safety risk assessment. A process safety hazop is a qualitative method and is as such not capable of generating a likelihood frequency.

LOPA uses a table of event frequencies for various failures that can occur, for example the expectancy for a pump to fail is generally set to once every 10 years. We could attempt to improve the reliability of the pump by having a redundant pump, but we still might have a common factor that would impact both pumps. For example a cyber attack might be such a common factor, or maybe a power failure if both pumps would be electrical driven.

It would be difficult and costly to realize a reliability of the pump function that meets the 1E-04 criterium of our example. So instead we use a process safety function to reduce the risk by automatically bringing the reactor into a safe state after the pump failure preventing the explosion and / or loss of containment.

If we ignore any attempts to improve the pump’s reliability we need a safety instrumented function (SIF) that is able to bring the reactor into a safe state, this function needs a reliability that reduces the risk by a factor 1000 (1E-03).

A SIF is an application that is triggered by some event, perhaps the flow rate of the cooling water or the temperature in the reactor vessel, to start initiating actions (closing / opening valves) bringing the reactor in a safe state. Reducing the risk requires that all components used by the SIF have a reliability that meets the reliability criteria that result in the risk reduction with a factor 1000. This is where the safety integrity limit (SIL) comes in.

A SIF typically requires input from one or more sensors (e.g. a flow sensor), some safety instrumented system (SIS) executing the program logic, and one or more safety valves to create the safe state of the reactor. All components of the SIF together need to meet the reliability requirement to reduce the risk with the required factor. A SIL 3 SIF means we reduce risk with a factor 1000, a SIL 2 SIF would be a factor 100. The SIL is a function of the mean time between failure (MTBF) of the components and a test frequency.

Chemical plants typically require SIL 2 or SIL 3 safety systems to be able to meet the criteria. To reach the SIL level, the SIS must have a reliability level that meets SIL 3 criteria. But also the MTBF of the field equipment needs to meet the requirements. If the MTBF of a transmitter would be too low to meet the criteria we would use multiple transmitters and perhaps a 2oo3 voting mechanism to reach this reliability. Same is true for the safety valves, we may have multiple safety valves in series to increase the likelihood that at least one will act. The SIS is a very special type of controller with many diagnostic functions monitoring the various internal states of the controller and its I/O connections to make certain that it performs when demanded. For this, SIS undergoes a series of certification tests allowing it to claim a specific SIL level. So process safety is capable by using reliable functions to prevent an event from causing a high impact.

So in our example above, the process safety function reduced the risk with a factor 1000. As result we have now a likelihood of 1E-04 that a loss of containment or explosion occurs with a potential consequence of multiple fatalities due to the pump failure. This example has many simplifications, but it explains the principle of how we reduce risk in process safety.

The other question I need to answer is why did we choose the 1E-04 and not 1E-02 or 1E-06? This is where the regulations around societal risk come into the picture. Governments set these limits. So lets take a more detailed view on topics like individual risk, societal risk, and aggregate risk before linking all to cyber security risk.

Societal risk

Early examples of quantitative risk assessments (QRA) for the process industry go back to the early seventies with the Canvey island study in the UK, the Rijnmond study in the Netherlands and an LNG project study in California. Today QRA is the standard approach resulting in quantitative risk criteria for the industry and standardization of the risk estimation method. Regulation exist for both individual risk and societal risk.

Individual risk expresses the risk to a single person exposed to a hazard, where societal risk expresses the cumulative risk to groups of people affected by the incident. This makes societal risk more complex because it is a measure on a scale based on the number of people impacted. Sometimes the term aggregate risk is used, aggregate risk is the special case of societal risk for on-site personnel in buildings.

Criteria for societal risk are more strict than for individual risk, also different criteria exist for societal risk depending if on-site personnel is affected or if off-site persons are impacted. Some regulations also differentiate between off-site persons being aware of process hazards (for example personnel of another plant next to the facility where the incident occurs) and the general public with less awareness and protective equipment.

Regulations use Frequency-Number (F-N) curves to specify the criteria, in the next diagram I show the criteria for some European countries.

F-N curve showing some differences between European countries

The curve shows the boundaries for societal risk as they are specified within Europe. We can see differences between countries and we can see the new directive within the European union for new plants. Above is very familiar for process safety engineers because this are the limitations that determine their target frequency in LOPA (1E-04 in my example). Some companies can use the less restrictive F-N diagrams for on site personnel, other companies have identified scenarios that might impact the public space and need to follow more restrictive criteria.

In the design of a safety function we typically don’t take the regulatory limit as our target, we add what is called risk capacity by specifying a more restrictive target. So if the regulatory limit would be 1E-03 we might set the target to 1E-04 adding “space” between the risk tolerance limit and acceptable risk limit. Terminology can be sensitive here, specifically the word “acceptable” is a sensitive term for some country’s legal system. Alternatives like Tolerable Acceptable, Tolerable Not Acceptable have been used to sub-divide the area between Not Acceptable and Acceptable. This because a fatality is never acceptable, however since zero risk doesn’t exist we still have to assign fatal incidents with a very low likelihood of occurring an actionable risk level.

The relationship between cyber security risk and societal risk

Though I write these blogs as a private person with a personal opinion and view on cyber security risk, I can not avoid linking this view to my experience build as an employee of Honeywell. The team I work for focuses on cyber security consultancy services and security products for the industry. My first risk assessment was almost 10 years ago in 2012 and I am still involved in risk assessments today.

So almost 10 years of experience working for a major supplier of control and safety solutions, building, maintaining and securing the largest production installations ever build. Working over 40 years for this company in different roles gave me a very detailed insight on how these solutions work and how they are applied to automate production processes. This also gave me detailed insight into a lot of factual data around cyber security risk within plants. Some of these insights I can generalize and discuss in this blog.

Very high level, when we assess cyber security risk (loss based risk) the process is identifying the various system functions, identifying the hazards and their attack scenarios (actually based upon a repository of hundreds of different attack scenarios including their countermeasures and potential functional deviations for almost a 100 different OT systems of different vendors), conducting a criticality and consequence analysis and estimating residual risk based on the countermeasures implemented.

Important information for this blog are the results of the consequence analysis, these results are derived from analyzing the LOPA and HAZOP studies carried out by asset owners. A task of consequence analysis is to go over all identified process safety scenarios and determine if the causes of these scenarios can be the result of a functional deviation of a cyber attack or if the safeguard implemented by the process safety system can be disrupted or used for the attack.

Based upon the results of more than 30 consequence analysis I did it shows that on average between 40 and 60% of all identified process scenarios (identified by HAZOP and LOPA) can also be caused by a cyber attack. So in our example of a pump failure, we can also intentionally cause this by stopping the pump and preventing the SIS to act upon it.

Overall approximately 5% of these “hackable” process scenarios involve fatalities as potential consequence, an even higher percentage of scenarios can cause the highest level of economic loss. This percentage of course differs by plant, there are plants without potential fatalities and there are plants with a much higher percentage of scenarios that result into potential fatalities. Never the less these numbers show that cyber risk in the process industry has a direct relationship with societal risk because a cyber attack can cause this type of incident. An important question is, is the cumulative risk of the process safety risk and cyber security risk below the criteria for societal risk?

There are some important rules and conclusions here to consider:

  • Process scenarios that involve potential fatalities require a safety instrumented function to prevent this. So in principle there should not be any scenario possible where an isolated attack on a BPCS or a failure of a BPCS or process equipment function should result in fatalities. Where ever such scenario is detected in the analysis, it should be corrected.
  • However it is possible that an isolated attack on the safety instrumented system (like the TRITON/TRISIS) attack can cause a scenario resulting in multiple fatalities. This makes the SIS also from a cyber security point of view a very critical system. SIS in this context can be an ESD, BMS, or HIPPS function.
  • The highest impact sensitivity (IS) is scored for attacks that impact both SIS and BPCS. Impact sensitivity being a metric that “weighs” how much “pain” a cyber attack can do by attacking a specific OT function or set of OT functions (e.g. BPCS and SIS).
  • Apart from SIS and BPCS other OT functions with a significant IS score are CCS (compressor control), APC (advanced process control), LIMS (laboratory information), IAMS (instrument asset management), and ASM (analyzer management). For CCS, APC, and ASM this is not surprising. IAMS frequently creates a common point to impact both safety and control while for LIMS we see an increased integration where lab results are transmitted “digitally” to for example the APC. This can create scenarios with a high economic loss since LIMS is directly tight in with product quality.

It is essential for the security of a plant to address cyber security through risk analysis, if the threats and their impact are not known we actually start doing things without knowing if we address the highest risk. Risk analysis should be based on an accurate mapping of the functional deviations caused by a cyber attack against the process scenarios that can result from these attacks. With accurate I mean not using consequence statements such as “Loss of View” or “Loss of Control” these are far to general to be used for this mapping. OT functions have much more specific functional deviations, that can be identified if we have a detailed understanding of the workings of the OT function.

Then the most important question, does the cumulative risk of process safety and cyber security risk meet the regulatory criteria? This is the hardest question to answer because the event frequencies of process safety (based on random failure events) and the event frequencies of cyber security (based on intentional action, and based on skills and motivation) differs very much. Never the less the cumulative event frequency of the two needs to meet the same regulatory limit, as mentioned the societal risk criteria are not specified for process safety they are specified for the production process as a whole. We also know that this cumulative risk is higher than each separate risk, adding new threats doesn’t lower risk and an intentional occurrence has typically a higher event frequency than a random occurrence. If the consequence is the same, the risk will be higher.

To discuss this I need the following diagram.

Threat analysis levels

If we analyze cyber security risk for a plant we typically consider threats at OT function level. The asset, channel and application level is (should be) covered by the design teams during the threat modelling stages of the product development process. However the results at OT function level of this analysis provide an event frequency based on the likelihood of success of the attack. So as if there would be a queue of capable threat actors ready and willing to attack the plant. In a normal situation (so no cyber war) this is not so, threat actors are very selective when it comes to executing targeted attacks specifically if they are very skilled and need advanced methods to succeed.

Therefor not every plant has to fear an attack of a nation sponsored threat actor aiming to cause an attack resulting in serious process impact. Attacks have cost, the cost of a failed attack (e.g. TRITON /TRISIS) are high. To develop such an attack is a considerable investment for a threat actor. This is of course quite different for ransomware attacks with an economic objective, that type of attack is more common. So we always have to consider risk by looking at different threat actors with different motives and capabilities.

For the overall likelihood of a cyber attack two event frequencies are important: the event frequency related to the OT function level threats which depends on the type of threat actor, the TTP, the countermeasures, and the dynamic and static exposure of the OT function; and a second event frequency at management level defining how often such an attack will happen and what threat actors would be interested. The OT function level risk is basically a technical exercise and can be estimated with various risk assessment methodologies, of which methods based on FAIR are used by multiple service providers.

For analyzing management level threats, other factors play a role. Some based on historical occurrences, some driven by geo-politics. Overall a more difficult and subjective factor to assess, typically requiring a threat profiling exercise.
The combination of the two event frequencies (using conditional likelihood formulas because one event depends on the other event) results in an overall event frequency for the cyber security risk. This is the frequency that needs to meet the societal risk criteria when considering loss based risk. At OT function level we can reach reliable results, however this is more difficult at management level.

So does cyber security risk meet the societal risk criteria is a question for which there is no reliable answer.

Another difficulty is that we have different cyber security risk assessment methods, often resulting in different quantitative outcomes. Governments have solved this for process safety by standardizing the estimation of societal risk through enforcing the use of a specific method or tool. However these methods or tools do not consider cyber security risk at this point in time.

Unfortunately none of the standard organizations seems to be willing or able to address this gap. IEC 62443-3-2 is very high level, actually not addressing any of above issues, primarily an introduction on risk. And what I have seen from TR84 it is not much better because it copies IEC 62443-3-2 for a large part and also doesn’t address this legal aspect of process safety and cyber security risk.

But this topic is a gap that needs to be filled, a gap that will be very high on the agenda if a cyber attack occurs with societal impact resulting in multiple fatalities. The TRITON / TRISIS attempt shows that it was merely “luck” and not the result of any impressive cyber security that it didn’t happen.

So maybe an organization like ENISA, that is not organized around volunteers, will consider closing this gap. In order to meet European regulations the gap should be closed.

I hope that people that took the effort to read the blog till the end realize how difficult estimating loss based risk is, and conclude that it might be far easier to use an FMEAC method to estimate risk based on a risk priority number for the security design.

However IEC 62443.3.2 makes the link in its method to the hazop with its loss based impact, so we are driven into considering this complex field of regulations.

I don’t think this is necessary for a good security design, I think it is primarily the result of an attempt to show cyber security is important. What is easier in that case then to link it with big brother process safety, but for proper cyber security design an FMEAC analysis brings us the same results.

So be careful specifying the need for business related risk if some form of legal or financial justification is not required, it opens a can of worms.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 43 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them, and conducting cyber security risk assessments for process installations since 2012.


Author: Sinclair Koelemij

OTcybersecurity web site

Results from the Poll


I started last Friday a small poll to get the opinion of the security community on assigning a security level to a specific type of production process. I selected a refinery, a chemical plant (as example a Poly Propylene plant), a bulk power generation plant and a wind mill farm for power generation.

Apart from people voting for a specific security level, there was also some discussion if the question I asked was correct. And yes it was a tricky question, IEC 62443 never intended to use security levels this way. But never the less IEC 62443.3.3 did create kind of threat actor profile by using the threat actor’s intention, capabilities, resources, and motivation as the differentiator between the security levels. So one could also read the question (and this was my intention) as against what threat actor profile do we need to protect the plant. First let me show the results:

Poll results (8/13/2021 – 8/19/2021)

I leave the security level assignments for what they are, good or bad assignment wouldn’t be an appropriate judgement because the criticality of the production process hasn’t been defined. But we can see in the top two diagrams that there is a certain tendency toward the higher security levels for the selected production processes.

I was also curious if there would be a difference in score between different disciplines, so I divided the votes (452 in total) over 4 groups. The votes from asset owners (135 votes), votes from subject matter experts working for OT service providers (220 votes), votes from subject matter experts working for IT service providers (79 votes), and a number of votes (total 18) of non-related disciplines. Seems like the OT service providers and the asset owners reasonably align in their judgement, and the IT providers and others like the SL 4 score.


Then about the discussion, is the question asked yes or no a valid question? From an IEC 62443 perspective probably not, but if I take the definition of security levels and their relationship with the threat actor profile literally, why not.

But ok, IEC 62443 likes us to define the system in security zones and conduits. Than determine the risk and assign a security level. However there is no transformation matrix defined in the standard. The only transformation matrix I am aware of is in the ISA course material. In the course material a qualitative risk assessment is provided, and the results of this assessment are converted into a security level. But formally there is no defined transformation matrix between risk and security level. Additionally qualitative risk assessments have no link with the quantitative results of the plant’s risk analysis based on the results of their Hazop / LOPA analysis. (See my blog on this topic) A plant’s risk matrix looks like this:

Example risk matrix

In the diagram a plant expresses which risk are acceptable (A), Tolerable Acceptable (TA), Tolerable Non-Acceptable (TNA), or Not acceptable (NA). Horizontally we have the likelihood, generally expressed in events per annum, and vertically we have the consequence severity scores / LOPA target factors. Above example uses 4 risk levels, but also 5 risk levels are used, in a 5 x 5 matrix. But different plants have different matrices and not always 5 x 5, e.g. 7×5 is also quite common aligning with the 7 likelihood categories used in LOPA.

In IEC 62443.3.2 the standard links to loss scenarios such as provided by the HAZOP / LOPA documentation. If we express risk as loss based risk, an important demand of asset owners, the transformation matrix converting risk to SL should align somehow with the risk matrix. But this is a challenge, every plant has its own transformation matrix because a risk seen as Non-Acceptable should not be assigned a security level as SL 2 if the consequence of the process scenario could even be single or multiple fatalities. So we would have many different transformation matrices.

Like I mentioned the ISA course material avoids this issue by working with a qualitative risk assessment and producing outcome that is not aligned with the plant risk matrix. However qualitative risk assessments are a subject matter expert’s opinion, and therefore often very subjective. Especially if workshops don’t have enough participants, and the workshop leader tries to get consensus on the scores. IEC 62443.3.2 denies the existence of quantitative methods, but these methods do exist and are used. I intend to show you how this works in my next blog, but it takes some time to create.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 43 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them, and conducting cyber security risk assessments for process installations since 2012.


Author: Sinclair Koelemij

OTcybersecurity web site

ICS cyber security risk criteria


Abstract

In my previous blog (Why process safety risk and cyber security risk differ) I discussed the differences between process safety risk and cyber security risk and why these two risks don’t align. In this blog I like to discuss some of the cyber security risk criteria, why they differ from process safety risk criteria and how they align with cyber security design objectives. And as usual I will challenge some of IEC 62443-3-2 misconceptions.


Cyber security can be either prescriptive or risk based. An example of a prescriptive approach is the IEC 62443-3-3, the standard is a list with security requirements to follow in order to create resilience against a specific cyber threat. For this IEC 62443 uses security levels with the following definitions:

  • SL 1 – Prevent the unauthorized disclosure of information via eavesdropping or casual exposure.
  • SL 2 – Prevent the unauthorized disclosure of information to an entity actively searching for it using simple means with low resources, generic skills and low motivation.
  • SL 3 – Prevent the unauthorized disclosure of information to an entity actively searching for it using sophisticated means with moderate resources, IACS specific skills and moderate motivation.
  • SL 4 – Prevent the unauthorized disclosure of information to an entity actively searching for it using sophisticated means with extended resources, IACS specific skills and high motivation.

I underlined the criteria that create the difference between the security levels. A few examples to translate the formal text from the standard to what is happening in the field.

An example of an SL 1 level of resilience is protection against a process operator looking over the shoulder of a process engineer to retrieve the engineer’s password. Maybe you don’t consider this a cyber attack, but formally it is a cyber attack by a hopefully non-malicious insider.

An example of an SL 2 level of resilience is protection against malware, for example a process control system that became infected by WannaCry, ransomware. WannaCry didn’t target specific asset owners and did not specifically target process control systems. Any system with an exposed Microsoft EternalBlue vulnerability could become victim.

An example of an SL 3 level of resilience is protection against the attack on Ukraine’s power power grid. This was a targeted attack, using a mixture of standard tactics like phishing to get access to the system and specially crafted software to make modifications in the control system.

An example of an SL 4 level of resilience would be the protection against Stuxnet, the attack on Iran’s uranium enrichment facilities. This attack made use of zero-day vulnerabilities, required detailed knowledge of the production process, and thoroughly testing of the attack on a “copy” of the actual system.

The difference between SL 2 and SL 3 is clear, however the difference between SL 3 and SL 4 is a bit arbitrary. For example is the Triton attack an example of SL 3 or can we say it is SL 4. The Triton attack required like Stuxnet also a significant investment for the threat actors. But where Stuxnet had clear political motives, the motives for the Triton attack are less clear for me. SL 4 is often linked to resilience against attacks by nation-states, but with all these “nation state sponsored” threat actors that difference often disappears.

The IEC 62443-3-3 standard assigns the security levels to security zones and conduits of the control system for defining the technical security requirements for the assets in the zone and communication between zones. The targets for a threat actor are either an asset or a channel (the protocols flowing through the conduit). Though the standard also attempts to address risk with the IEC 62443-3-2, there is no clear path from risk to security level. There is not an “official” transformation matrix that converts a specific risk level into a security level, apart from the many issues with such a matrix. So overall IEC 62443-3-3 is a prescriptive form of cyber security. This is common for standards and government regulations, they need clear instructions.

The issue with prescriptive cyber security is that it doesn’t address the specific differences between systems. It is kind of ready-to-wear suit, does overall a good job but a tailor-made suit fits better. The tailor-made suit for cyber security is risk based security. In my opinion risk based security is a must for process automation systems supporting the critical infrastructure. Threat actors targeting critical infrastructure are highly skilled professionals, we should not put them aside as hackers for fun. Also the offensive side is a profession, either servicing a “legal” business such as the military or an “illegal” business such as cyber crime. And this cybercrime business is big business, it is for example bigger than the drugs trade.

Protection against the examples I gave for SL 3 and SL 4 requires a detailed analysis of the attack scenarios available to launch against the process installation, analyzing which barriers are in place to stop or detect these scenarios, and estimating the residual risk after having applied the barriers to see if we meet the risk criteria. For this we need residual risk, the risk after applying the barriers, and residual risk requires quantitative risk analysis to estimate the risk reduction similar to how process safety does this with LOPA as discussed in my previous blog.

Quantitative analysis is required because we want to know the contribution in risk reduction from the various barriers. Barriers being the countermeasures with which we can reduce the likelihood that the attack succeeds or with which we reduce / take away the impact severity of the consequences of a successful cyber attack. A simple example of a likelihood reducing barrier is an antivirus solution, a simple example of an impact severity reducing barrier is a back-up. These barriers are not limited to various security packages but also include design choice in the automation system and the production facility. The list of barriers I work with during my professional time has grown to over 400 and keeps growing with every detailed risk assessment. The combination of attack scenarios (the TTP of the threat actors), barriers and consequences (the deviations of the process automation functions as result of a successful cyber attack) is the base for a risk analysis.

Where a value for consequence severity can either be a subject matter expert assigned severity level for the functional deviation (resulting in a risk priority number (RPN)) or the severity scores / target factors of the worse case process scenarios that can result from the potential functional deviation. These severity scores / target factors come from the HAZOP or LOPA sheets created by the process safety engineers during their analysis of what can go wrong with the process installation and what is required to control the impact when things go wrong. When we use LOPA / HAZOP severity scores for consequence severity we call the resulting risk loss based risk (LBR), the risk a specific financial, safety, or environmental loss occurs. For security design a risk priority number is generally sufficient to identify the required barriers, however to justify the risk mitigation (investment in those barriers) to management and regulatory organizations loss based risk is often a requirement.

To carry out a detailed risk assessment the risk analyst should oversee a wide field of skills, understanding the automation system’s working in detail, understanding the process and safety engineering options, and understanding risk. Therefore risk assessments are teamwork of different subject matter experts, however the risk analyst needs to connect all input to get the result.

But risk assessments is also a very rewarding cyber security activity because communicating risk to management is far easier than explaining them why we invest in a next generation firewall instead of the lower cost packet filter. Senior management understands risk far better than cyber security technology.


So far the intro, lets look at the risk criteria now. ISA / IEC have a tendency in their approach to cyber risk to have a So much for the intro, now let’s look at the risk criteria. ISA/IEC tend to look closely at how process security approaches the subject in their approach to cyber risk and to attempt to copy it.

However as explained in my previous blog there are major differences between cyber security risk and process safety risk making such a comparison more complex than it seems. Many of these differences also have an impact on the risk criteria and the terminology we use. I like to discuss two terms in this blog, unmitigated risk and risk tolerance. Let’s start with unmitigated risk.

Both ISA 62443-3-2 and the ISA TR 84 work group use the term unmitigated risk. As an initial action they want to determine unmitigated risk and compare this with the risk criteria. Unmitigated risk is a term used by process safety for the process safety risk prior to applying the safeguards protecting against randomly occurring events that could cause a specific worse case process impact. The safeguards protect against events like a leaking seal, a failing pump, or an operator error. The event frequency of such an initiating event (e.g. failed pump) is reduced by applying safeguards, the resulting event frequency after applying the safeguard needs to meet specified limits. (See my previous blog) Safety engineers basically reduce an event frequency gap using safeguards with a reliability that actually accomplish this. The safeguard will bring the process into a safe state by itself. Multiple safeguards can exist but each safeguard will prevent the worst case consequence by itself. It is not that safeguard 1 and safeguard 2 need to accomplish the job together, each of them individually does the job. There might be a preferred sequence but not a dependency of protection layers.

Cyber security doesn’t work that way, we might define a specific initiating event frequency for the chance on a virus infection. But after installing an antivirus engine we cannot say the problem is solved and no virus infections will occur. The reliability of a process safety barrier is an entirely different factor than the effectiveness of a cyber security barrier. Both reduce risk, the process safety barrier reduces the risk to the required limit by it self with a reliability that allows us to take the credit for the risk reduction. But the cyber security barrier most likely requires additional barriers to reach an acceptable event frequency / risk reduction.

Another difference is that in cyber security the initiating event is not occurring randomly, it is an intentional action of a threat actor with a certain propensity (A term introduced by Terry Ingoldsby from Amenaza) to target the plant, select a TTP and target a specific function. The threat actor has different TTPs available to accomplish the objective, so the initiating event frequency is not so much one point on the frequency scale but a range with a low and high limit. We cannot pick on forehand the high limit of this range (representing the highest risk) because the process control system’s cyber resilience actually determines if a specific TTP can succeed, so we need to “exercise” a range of scenarios to determine the highest event frequency (highest likelihood) applicable within the range.

A third difference is the defense in depth. In process safety defense in depth is implemented by multiple independent protection layers. For example there might be a safety instrumented function configured in a safety system, but additionally there can be physical protection layers like a dike or other forms of bunding to control the impact. In cyber security we also apply defense in depth, it is considered bad practice if security depends on a single control to protect the system. However many of these cyber security controls share a common element, the infrastructure / computer. We can have an antivirus engine and we can add application whitelisting or USB protection to further reduce the chance that malware enters the system but they all share the same computer platform offering a shared point of failure.

Returning to the original remark on unmitigated risk, in process automation cyber security risk unmitigated risk doesn’t exist. The moment we install a process control system we install some inherent protection barriers. Examples are authentication / authorization, various built-in firewalls, encrypted messages, etc. So when we start a cyber security risk analysis there is no unmitigated risk, we can’t ignore the various barriers built-in the process automation systems. A better term to use is therefore inherent risk. The risk of the system as we analyze it, the inherent risk is also the residual risk but it is not unmitigated there is a range of barriers implemented when we start a risk analysis. The question is more, does the inherent risk meet the risk criteria and if not what barriers are required that result in a residual risk that does meet the criteria.


The second term I like to discuss is risk tolerance. Both IEC 62443 and the ISA TR 84 work group pose that the cyber security must meet the risk tolerance. I fully agree with this, where we differ is that I don’t see risk tolerance as the cyber security design target where the IEC 62443 standard does. In risk theory, risk tolerance is defined as the maximum loss a plant is willing to experience. To further explain my issue with the standard I first discuss the process safety side use of risk tolerance and use an F-N diagram from my previous blog.

Example F-N diagram

This F-N curve shows two limits using a red and a green line. Anything above the red line is unacceptable, anything below the green line is acceptable. The area between the two lines is considered tolerable if it meets the ALARP (As Low As Reasonably Practicable) principle. For a risk to be ALARP, it must be possible to demonstrate that the cost involved in reducing the risk further would be grossly disproportionate to the benefit gained. Determining that a risk is reduced to the ALARP level involves an assessment of the risk to be avoided, an assessment of the investment (in money, time and trouble) involved in taking measures to avoid that risk, and a comparison of the two.

In process safety where the events occur randomly this is possible, in cyber security where the events occur intentionally this is far more difficult.

Can we consider the risk for the power grid in a region with political tensions the same as in the case of a region having no conflicts at all. I worked for refineries that had as a requirement to be resilient against SL 2 level of threat actors, but also refineries that told me they wanted SL 3, and there was even a case where the requirement was SL 4. So in cyber security the ALARP principle is not really followed, there is apparently another limit. The risk tolerance limit is for all the same, but there is also a limit that sets a kind of cyber security comfort level. This level we call the risk appetite, and this level is actually should become our cyber security design target level.

Risk appetite and risk tolerance shouldn’t be the same, there should be a margin between the two that allow for the possibility to respond to failures of the security mechanisms. If risk appetite and risk tolerance are the same and this would also be our design target any issue with a security control would result in an unacceptable risk.

In principal unacceptable risk means we should stop the production (as is the case for process safety), so if the limits would be the same we have created kind of a on/off mechanism. For example if we couldn’t update our antivirus engine for some reason, risk would raise above the limit and we would need to stop the plant. Maybe an extreme example and certainly not really a situation I see happening in real life. However when risk becomes not acceptable we should have an action defined for this case. There are plants that don’t have a daily update but follow a monthly or quarterly AV signature update frequency (making AV engine effectiveness very low with all the polymorph viruses), so apparently risk appetite differs.

If we want to define clear actions / consequences for each risk level we need sufficient risk levels to do this and limits that allow us to respond to failing cyber controls. So we need two limits, risk appetite and risk tolerance. The difference between risk appetite and risk tolerance is called risk capacity, having a small risk capacity means that issues can escalate quickly. A security design must also consider the risk capacity in the selection of barriers, “defense in depth” is an important security principle here because this increases risk capacity.

Example risk matrix

Above shows an example risk matrix (different criteria as the F-N diagram above) with 4 risk levels (A, TA, TNA, NA). Typically 4 or 5 risk levels are chosen and for each level the criteria and action is specified. In above example the risk tolerance level is the line that separates TNA and NA. Risk appetite might be either the line between TA and TNA or between A and TA for a very risk averse asset owner. However the risk capacity of a security design were the risk appetite is defined at the TA / TNA border is much smaller than if our target would be the A / TA border. But in both cases a risk increase due to the failure of a cyber security control with not immediately escalate into a Non Acceptable risk condition.

If we opt for risk based security, we need to have actionable risk levels and in that case a single risk tolerance level as specified and discussed in the IEC 62443-3-2 is just not possible and therefore not practiced for cyber security risk. The ALARP principle and cyber security don’t go together very well.


Maybe a bit boring topic, maybe too much text, never the less I hope the reader understands why unmitigated risk doesn’t exist in cyber security for process automation. And I certainly hope that the reader will understand that the risk tolerance limit is a bad design target.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 43 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them, and conducting cyber security risk assessments for process installations since 2012.


Author: Sinclair Koelemij

OTcybersecurity web site

Why process safety risk and cyber security risk differ


Abstract

When cyber security risk for process automation systems is estimated I often see references made to process safety risk. This has several reasons:

  • For estimating risk we need likelihood and consequence, the process safety HAZOP and LOPA processes used by plants to estimate process safety risk, identify the consequence of the process scenarios they identify and analyze. These methods also classify the consequence in different categories such as for example finance, process safety, and environment.
  • People expect a cyber security risk score that is similar to the process safety risk score, a score expressed as loss based risk. The idea is that the cyber threat potentially increases the process safety risk and they like to know how much that risk is increased. Or more precisely how high is the likelihood that the process scenario could occur as result of a cyber attack.
  • The maturity of the process safety risk estimation method is much higher than the maturity of cyber security risk estimation methods in use. Not that strange if you consider that the LOPA method is about 20 years old, and the HAZOP method goes back to the end sixties. When reading publications, or even the standards on cyber security risk (e.g. IEC 62443-3-2) this lack of maturity is easily detected. Often qualitative methods are selected, however these methods have several drawbacks which I discuss later.

This blog will discuss some of these differences and immaturities. I’ve done this in previous blogs mainly by comparing what the standards say and what I’ve experienced and learned over the past 8 years as a cyber risk analysis practitioner for process automation systems doing a lot of cyber risk analysis for the chemical, and oil and gas industries. This discussion requires some theory, I will use some every day examples to explain to make it more digestible.


Let us start with a very important picture to explain process safety risk and its use, but also to show how process safety risk differs from cyber security risk.

Process safety FN curve

There are various ways to express risk, the two most used are risk matrices and FN plots / FN curve. FN curves require a quantitative risk assessment method, such as used in process safety risk analysis by for example LOPA. In an FN curve we can show the risk criteria. The boundaries for what we consider acceptable risk and what we consider unacceptable risk. I took a diagram that I found on the Internet where we have a number of process safety scenarios (shown as dots on the blue line) their likelihood of occurrence ( the vertical ax) and in this case the consequence expressed in fatalities when such a consequence can happen (horizontal ax). The diagram is taken from a Hydrogen plant, these plants belong to the most dangerous plants, this is why we see the relative high number of scenarios with a single or multiple fatalities.

Process safety needs to meet regulations / laws that are associated with their plant license. One such “rule” is that the likelihood of “in fence” fatalities must be limited to 1 every 1000 years (1.00E-3) If we look at the risk tolerance line (RED) in the diagram we see that what is considered tolerable and intolerable is exactly at the point where the line crosses the 1.00E-03 event frequency (likelihood). Another often used limit is the 1.00E-04 frequency for the limit used as acceptable risk, risk not further addressed.

How does process safety determine this likelihood for a specific process scenario? In process safety we have several structured methods for identifying hazards. One of them is the Hazard and Operability study, in short the HAZOP. In a hazop we analyze, for a specific part of the process, if specific conditions can occur. For example we can take the flow through an industrial furnace and analyze if we can have a high flow, no flow, maybe reverse flow. If such a condition is possible we look at the cause of this (the initiating event), perhaps no flow because a pump fails. If we have established the cause (the initiating event) we consider what would be the process consequence. Well possibly the furnace tubing will be damaged, the feed material would leak into the furnace and an explosion might occur. This is what is called the process consequence. This explosion has an impact on safety, one or multiple field operators might be in the neighborhood and killed by the explosion. There will also be a financial impact, and possibly an environmental impact. A hazop is a multi-month process where a team of specialists goes step by step through all units of the installation and considers all possibilities and ways how to mitigate this hazard. This results in a report with all analysis results documented and classified. Hazops are periodically reviewed in a plant to account for possible changes, this we call the validity period of the analysis.

However we don’t have yet a likelihood expressed as an event frequency such as used in the FN curve. This is where the LOPA method comes in. LOPA has tables for all typical initiating events (causes), so the event frequency for the failure of a pump has a specific value (for example 1E-01, once every 10 years). How were these tables created? Primarily based on statistical experience. These tables have been published, but can also differ between companies. It is not so that a poly propylene factory of company A uses by default the same tables as a poly propylene factory of company B. All use the same principles, but small differences can occur.

In the example we have a failing pump with an initiating frequency of once every 10 years and a process consequence that could result in a single fatality. But we also know that our target for single fatalities should be once per 1000 years or better. So we have to reduce this event frequency of 1E-01 with at least a factor 100 to get to once per 1000 years.

This is why we have protection layers, we are looking for one or more protection layers that offer us a factor one hundred extra protection. One of these protection layers can be the safety system, for example a safety controller that detects the no flow condition by measuring the flow and shuts down the furnace to a safe state using a safety valve. How much “credit” can we take for this shutdown action? This depends on the safety integrity level (SIL) of the safety instrumented function (SIF) we designed. This SIF is more than the safety controller where the logic resides, the SIF includes all components necessary to complete the shutdown function, so will include transmitters that measure the flow and safety valves that close any feed lines and bring other parts of the process into a safe condition.

We assign a SIL to the SIF. We typically (SIL 4 does exist) have 3 safety integrity levels: SIL 1, 2, and 3. According to LOPA a SIL 1 SIF gives us a reduction of a factor 10, SIL 2 will reduce the event frequency by a factor 100, and SIL 3 by a factor 1000.

How do we estimate if a SIF meets the requirements for SIL 1, 2, or 3? This requires us to estimate the average probability of failure on demand for the SIF. This estimation makes use of mean time between failure of the various components of the SIF and the test frequency of these components. For this blog I skip this part of the theory, we don’t have to go into that level of detail. High level we estimate what we call the probability of failure on demand for the protection layer (the SIF). In our example we need a SIF with a SIL 2 rating, a protection level relatively easy to create.

In the FN curve you can also see process scenarios that require more than a factor 100, for example a factor 1000 like in a SIL 3 SIF. This requires a lot more, both from the reliability of the safety controller as well as from the other components. Maybe a single transmitter is not reliable enough anymore and we need some 2oo3 (two out of three) configuration to have a reliable measurement. Never the less the principle is the same, we have some initiating event, we have one or more protection layers capable of reducing the event frequency with a specific factor. These protection layers can be a safety system (like in my example), but also some physical device (e.g. pressure relief valve), an alarm from the control system, an operator action, a periodic preventive maintenance activity, etc. LOPA gives each of these protection layers what is called a credit factor, a factor with which we can reduce the event frequency when the protection layer is present.

So far the theory of process safety risk,. One topic I avoided discussing here is the part where we estimate the probability of failure on demand (PFDavg) for a protection layer. But it has some relevance for cyber risk estimates. If we would go into more detail and discuss these formulas to estimate the effectiveness / reliability of the protection layer we see that the formulas for estimating PFDavg we depend on what is called the demand rate. The demand rate is the frequency which we expect the protection layer will needs to act.

The standard (IEC 61511) makes a difference between what is called low-demand rate and high / continuous demand rate. The LOPA process is based upon the low demand-rate formulas, the tables don’t work for high / continuous demand rate. This is an important point to notice when we start a quantitative cyber risk analysis because the demand rate of a cyber protection layer is by default a high / continuous demand rate type of protection layer. This difference impacts the event frequency scale and as such the likelihood scale. So if we were to estimate cyber risk in a similar manner as we estimated process safety risk we end up with different likelihood scales. I will discuss this later.


A few important points to note from above discussion:

  • Process safety risk is based on randomly occurring events, events based on things going wrong by accident, such as a pump failure, a leaking seal, an operator error, etc.
  • The likelihood scale of process safety risk has a “legal” meaning, plants need to meet these requirements. As such a consolidated process safety and cyber security risk score is not relevant and because of estimation differences not even possible.
  • When we estimate cyber security risk, the process safety risk is only one element. With regard to safety impact the identified safety hazards will most likely be as complete as possible, but the financial impact will not be complete because financial impact might also result from scenarios that do not impact process operations but might impact the business. The process safety hazop or LOPA does not generally address cyber security scenarios for systems that have no potential process impact, for example a historian or metering function.
  • The IEC 62443 standard tries to introduce the concept of “essential” functions and ties these functions directly to the control and safety functions. However plants and automation functions have many essential tasks not directly related to the control and safety functions, for example various logistic functions. The automation function contains all functions connected to level 0, level 1, level 2, level 3, and demilitarized zone. When we do a risk analysis these systems should be included, not just the control and safety elements. The problem that a ship cannot dock to a jetty also has significant cost to consider in a cyber risk analysis.
  • Some people suggest that cyber security provides process safety (or worse the wider safety is even suggested.) This is not true, process safety is provided by the safety systems. The various protection layers in place. Cyber security is an important condition for these functions to do their task, but not more as a condition. The Secret Service protects the president of the US against various threats, but it is the president of the US that governs the country – not the Secret Service by enabling the president to do his task.

Where does cyber security risk differ from process safety risk? Well first of all they have different likelihood scales. Process safety risk is based on random events, cyber security risk is based on intentional events.

Then there is the difference that a process safety protection layer always offers full protection when it is executed, many cyber security protection layers don’t. We can implement antivirus as a first protection layer, application white listing as a 2nd protection layer, they both would do their thing but still the attacker can slip through.

Then there is the difference that a cyber security protection layer is almost continually “challenged”, where in process safety the low demand rate is most often applied, which sets the maximum demand rate to once a year.


If we would look toward cyber security risk in the same way as LOPA does toward process safety risk, we could define various events with their initiating event frequency. For example we could suggest an event such as a malware infection to occur bi-annually. We could assign protection layers against this, for example anti-virus and assign this protection layer a probability of failure on demand (risk reduction factor), so a probability on a false negative or false-positive. If we have an initiating event (the malware infection) with a certain frequency and a protection layer (antivirus) with a specific reduction factor we can estimate a mitigated event frequency (of course taking high demand rate into account).

We can also consider multiple protection layers (e.g. antivirus and application white listing) and arrive at a frequency representing the residual risk after applying the two protection layers. Given various risk factors and parameters to enter the system specific elements and given a program that evaluates the hundreds of attack scenarios, we can arrive at a residual risk for one or hundreds of attack scenarios.

Such methods are followed today, not only by the company I work for but also by several other commercial and non-commercial entities. Is it better or worse than a qualitative risk analysis (the alternative)? I personally believe it is better because the method allows to take multiple protection layers into account. Is it actuarial type of risk, no it is not. But the subjectivity of a qualitative assessment has been removed because of the many factors determining the end result and we have risk now as residual risk based upon taking multiple countermeasures into account.

Still there is another difference between process safety and cyber security risk not accounted for. This is the threat actor in combination with his/her intentions. In process safety we don’t have a threat actor, all is accidental. But in cyber security risk we do have a threat actor and this agent is a factor that influences the initiating event frequency of an attack scenario.

The target attractiveness of facilities differ for different threat actors. A nation state threat actor with all its capabilities is not likely to attack the local chocolate cookie factory, but might show interest in an important pipeline. Different threat actors mean different attack scenarios to include but also influence the initiating event frequency it self. Where non-targeted attacks show a certain randomness of occurrence, a targeted attack doesn’t show this randomness.

We might estimate a likelihood for a certain threat actor to achieve a specific objective for the moment that the attack takes place, but this start moment is not necessarily random. Different factors influence this, so to express cyber risk on a similar event frequency scale as process safety risk is not possible. Cyber security risk is not based on the randomness of the event frequencies. If there is a political friction between Russia and Ukraine, the amount of cyber attacks occurring and skills applied is much bigger than in times without such a conflict.

Therefore cyber security risk and process safety risk cannot be compared. Though the cyber threat certainly increases the process safety risk (both initiating event frequency can be higher and the protection layer might not deliver the level of reliability expected), we can not express this rise in process safety risk level because of the differences discussed above. Process safety risk and cyber security risk are two different things and should be approached differently. Cyber security has this “Secret Service” role, and process safety this “US president” role. We can estimate the cyber security risk that this “Secret Service” role will fail and the US government role is made to do bad things, but that is an entirely different risk than that the US government role will fail. It can fail even when the “Secret Service” role is fully active and doing its job. Therefore cyber security risk has no relation with process safety risk, they are two entirely different risks. The safety protection layers provide process safety (resilience against accidental failure), the cyber security protection layers provide resilience against an intentional and malicious cyber attack.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 43 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them, and conducting cyber security risk assessments for process installations since 2012.


Author: Sinclair Koelemij

OTcybersecurity web site

Cyber risk assessment is an exact business

Abstract


This blog is about risk assessment in cyber physical systems and some of the foundational principles. I created several blogs on the topic of risk assessment before, for example “Identifying risk in cyber physical systems” and “ISA 62443-3-2 an unfettered opinion“. Specifically the one on criticizing the ISA standard caused several sharp reactions. In the meantime ISA 62443-3-2 has been adopted by the IEC and a task group focusing on cyber security and safety instrumented systems (ISA 84 work group 9) addresses the same topic. Though unfortunately the ISA 84 team seems to have the intention to copy the ISA 62443-3-2 work and with this also the structural flaws will enter the work of this group. One of these flaws is the ISA approach toward likelihood.

Therefore this blog addresses this very important aspect of a risk assessment in the cyber physical system arena. Likelihood is actually the only factor of interest, because the impact (severity of the consequences) is a factor that the process hazard analysis the asset owner makes provides. Therefore likelihood / probability is the most important and challenging variable to determine because many of the cyber security controls affect the likelihood of a cyber security hazard occurring. Much of the risk reduction is achieved by reducing the chance that a cyber attack will succeed through countermeasures.

Having said this about likelihood we must not ignore the consequences, as I have advocated in previous blogs. This because risk reduction through “cyber safeguards” (those barriers that either eliminate the possibility of a consequence occurring or reduce the severity of that consequence – see my earlier blogs) is often a more reliable risk reduction than “cyber countermeasures” (those barriers that reduce the likelihood).

But this blog is about likelihood, the bottlenecks we face in estimating the probability and selecting the correct quantitative scale to allow us to express a change in process safety risk as the result of the cyber security threat.

At the risk of losing readers before coming to the conclusions, I would still like to cover this topic in the blog and explain the various problems we face. If you are interested in risk estimation I suggest to read it, if not just forward it to stalk your enemies.



Where to start? It is always dangerous to start with a lot of concepts because for part of the audience this is known stuff, while for others it answers some questions they might have. I am not going to give much formulas, most of these have been discussed in my earlier blogs, but it is important to understand there are different forms of risk. These forms often originate from different questions we like to answer. For example we have:

  • Risk priority numbers (RPN), is a risk value used for ranking / prioritization of choices. This risk is a mathematical number, the bigger the number the bigger the risk;
  • Loss based risk (LBR), is a risk used for justifying decisions. This risk is used in production plants and ties the risk result to monetary loss due to production outage / equipment damage / permit to operate. Or a loss expressed in terms of human safety or environmental damage. Often risk is estimated for multiple loss categories;
  • Temporal risk or actuarial risk, is a risk used for identifying the chance on a certain occurrence over time. For example insurance companies use this method of risk estimation analyzing for example the impact of obesity over a 10 year period to understand how it impacts their cost.

There are more types of risk than above three forms, but these three cover the larger part of the areas where risk is used. The only two I will touch upon in this blog, are RPN and LBR. Temporal risk, the question of how many cyber breaches caused by malware will my plant face in 5 years from now, is not raised today in our industry. Actually at this point in time (2021) we couldn’t even estimate this because we lack the statistical data required to answer the question.

We like to know what is the cyber security risk today, what is my financial, human safety, and environmental risk, can it impact my permit to operate, and how can I reduce this risk in the most effective way? What risk am I willing to accept and what should I keep a close eye on, and what risk will I avoid? RPN and LBR estimates are the methods that provide an answer here and both are extensively used in the process industry. RPN primarily in asset integrity management and LBR for business / mission risk. LBR is generally derived from the process safety risk, but business / mission risk is not the same as process safety risk.


Risk Priority Numbers are the result of what we call Failure Mode Effect and Criticality Analysis (FMECA) a method applied by for example asset integrity management. FMECA was developed by the US military over 80 years ago to change their primarily reactive maintenance processes into proactive maintenance processes. The FMECA method focuses on qualitative and quantitative risk identification for preventing failure, if I would write “for preventing cyber failure” I create the link to cyber security.

For Loss Based Risk there are various estimation methods used (for example based on annual loss expectancy), most of them very specific for a business and often not relevant or not applied in the process industry. The risk estimation method mostly used today in the process industry, is the Layers Of Protection Analysis (LOPA) method. This method is used extensively by the process safety team in a plant. The Hazard and Operability (HAZOP) study identifies the various process hazards, and LOPA adds risk estimation to this process to identify the most prominent risks.

If we know what process consequences can occur (for example a seal leak causing an exposure to a certain chemical, yes / no potential ignition, how many people would be approximately present in the immediate area, is the exposure yes / no contained within the fence of the plant, etc.) we can convert the consequence into a monetary/human safety/environmental loss value. This together with the LOPA likelihood estimate, results in a Loss Based Risk score.

How do we “communicate” risk, well generally in the form of a risk assessment matrix (RAM). A matrix that has a likelihood scale, an impact scale and shows (generally using different colors) what we see as acceptable risk, tolerable risk, and not acceptable risk zones. But other methods exist, however the RAM is the form most often used.


A picture of a typical risk assessment matrix with 5 different risk levels and some criteria for risk appetite and risk tolerance. And a picture to have at least one picture in the blog.

So much for the high-level description, now we need to delve deeper into the “flaws” I mentioned in the introduction / abstract. Now that the going gets tough, I need to explain the differences between low demand mode and high demand / continuous mode as well as the differences between IEC 61511 and IEC 62061 and some differences in how the required risk reduction is estimated, but also how the frequency of events scale ,underlying the qualitative likelihood scale, plays a role in all this. This is a bit of a chicken and egg problem, we need to understand both before understanding the total. Let me try, I start with taking a deeper dive into process safety and the safety integrity limit – the SIL.


In process safety we start with what is called the unmitigated risk, the risk inherent to the production installation. This is already quite different from cyber security risk, where unmitigated risk would be kind of a foolish point to start. Connected to the Internet and without firewalls and other protection controls, the process automation system would be penetrated in milli-seconds by all kind of continuous scanning software. Therefor in cyber security we generally start with residual risk based upon some initial countermeasures and we investigate if this risk level is acceptable / tolerable. But let’s skip a discussion on the difference between risk tolerance and risk appetite, a difference ignored by IEC 62443-3-2 though from a risk management perspective an essential difference that provides us time to manage.

However in plants the unmitigated situation is relevant, this has to do with what is called the demand rate and that we don’t analyze risk from a malicious / intentional perspective. Incidents in process safety are accidental, caused by wear and tear of materials and equipment, human error. No malicious intent, in a HAZOP sheet you will not find scenarios described where process operators intentionally open / close valves in a specific construction/sequence to create damage. And typically most hazards identified have a single or sometimes a double cause, but not much more.

Still asset owners like to see cyber security risk “communicated” in the same risk assessment framework as the conventional business / mission risk derived from process hazard analysis. Is this possible? More to the point, is the likelihood scale of a cyber security risk estimate the same as the likelihood scale of a process safety risk estimate if we take the event frequencies underlying the often qualitative scales of the risk diagrams into account?

In a single question, would the qualitative likelihood score of Expected for a professional boxer to go knock out (intentional action) during the job during his career, be the same as for a professional accountant (accidental)? Can we measure these scales along the same quantitative event frequency scales? I don’t think so. Even if we ignore for a moment the difference in career length, the probability that the accountant goes knock out (considering he is working for a reputable company) during his career is much lower. But the IEC/ISA 62443-3-2 method does seem to think we can mix these scales. But okay, this argument doesn’t necessarily convince a process safety or asset integrity expert, even though they came to the same conclusion. To explain I need to dive a little deeper into the SIL topic in the next section and discuss the influence of another factor, demand rate, on the quantitative likelihood scale.


The hazard (HAZOP) and risk assessment (LOPA) are used in process safety to define the safety requirements. The safety requirements are implemented using what are called Safety Instrumented Functions (SIF). The requirements for a SIF can be seen as two parts:

  • Safety function requirements;
  • Safety integrity requirements;

The SIFs are implemented to bring the production process to a safe state when demands (hazardous events) occur. A demand is for example if the pressure in a vessel rises above a specified limit, the trip point. The safety functional requirements specify the function and the performance requirements for this function. For example the SIF must close an emergency shutdown valve the “Close Flow” function, performance parameters can be the closing time and the leakage allowed in closed position. For this discussion the functional requirements are not that important, but the safety integrity requirements are.


When we discuss safety integrity requirements, we can split the topic into four categories:

  • Performance measures;
  • Architectural constraints;
  • Systematic failures;
  • Common cause failures.

For this discussion the performance measures, expressed as the Safety Integrity Level (SIL), are of importance. For the potential impact of cyber attacks (some functional deviation or lost function) the safety function requirements (above), and the common cause failures, architectural constraints, and systematic failures are of more interest. But the discussion here focuses on risk estimation and more specific the likelihood scale not so much on how and where a cyber attack can cause process safety issues. Those scenarios can be discussed in another blog.

The safety integrity performance requirements define the area I focus on, in these requirements safety integrity performance is expressed as a SIL. The IEC 61508 defines 4 safety integrity levels: SIL 1 to SIL 4. SIL 4 having the most strict requirements. To fulfill a SIL, the safety integrity function (SIF) must meet both a quantitative requirement and a set of qualitative requirements.

According to IEC 61508 the quantitative requirement is formulated based on either an average probability of failure on demand (PFDavg) for what are called low demand SIFs, and a Probability of Failure on Demand per Hour (PFH) high demand / continuous mode SIFs. Two different event frequency scales are defined, one for the low demand SIFs and one for the high demand SIFs. So depending on how often the protection mechanism is “challenged” the risk estimation method will differ.

For the low demand SIFs the SIL expresses a range of risk reduction values, and for the high demand SIFs it is a scale of maximum frequency of dangerous system failures. Two different criteria, two different methods / formulas for estimating risk. If the SIF is demanded less than once a year, low-demand mode applies. If the SIF is demanded more than once a year high demand / continuous mode is required. The LOPA technique for estimating process safety risk is based upon the low-demand mode, the assumption that the SIF is demanded less than once a year. If we would compare our cyber security countermeasure with a SIF, will our countermeasure be demanded just once a year? An antivirus countermeasure is demanded every time we write to disk, not to mention a firewall filter passing / blocking traffic. Risk estimation for cyber security controls is high demand / continuous mode.

LOPA specifies a series of initiating event frequencies (IEF) for various occurrences. These event frequencies can differ between companies, but with some exceptions they are similar. For example the IEF for a control system sensor failure can be set to once per 10 year, and the IEF for unauthorized changes to the SIF can be set to 50 times per year. These are actual examples for a chemical plant, values from the field not an example made up for this blog. The 50 seems high, but by giving it a high IEF it also requires more and stronger protection layers to reduce the risk within the asset owner’s acceptable risk criteria. So there is a certain level of subjectivity in LOPA possible, which creates differences between companies for sometimes the same risk. But most of the values are based on statistical knowledge available in the far more mature process safety discipline compared with the cyber security discipline.

In LOPA the IEF is reduced using protection layers (kind of countermeasure) with a specific PFDavg. PFDavg can be a calculated value, carried out for every safety design, or a value selected from the LOPA guidelines, or an asset owner preferred value.

For example an operator response as protection layer is worth a specific factor (maybe 0.5), so just by having an operator specified as part of the protection layer (maybe a response to an alarm) the new frequency, the Mitigated Event Frequency (MEF), for the failed control system sensor becomes 0.5 x 10 equivalent to once per 5 years. Based upon one or more independent protection layers with their PFD, the IEF is reduced to a MEF. If we create a linear scale for the event frequency and sub-divide the event scale in a number of equal qualitative intervals to create a likelihood scale, we can estimate the risk given a specific impact of the hazardous event. The linearity of the scale is important since we use the formula risk equals likelihood times impact, if the scale would be logarithmic the multiplication wouldn’t work anymore.

In reality the LOPA calculation is a bit more complicated because we also take enabling factors into account, probability of exposure, and multiple protection layers (including BPCS control action, SIF, Operator response, and physical protection layers such as brake plates and pressure relief valves). But the principle to estimate the likelihood remains a simple multiplication of factors. However LOPA applies only for the low demand cases and LOPA is using an event scale based on failures of process equipment and human errors. Not an event scale that takes into account how often a cyber asset like an operator station gets infected by malware, not taking into account intentional events, and starts with the unmitigated situation. Several differences with risk estimation for cyber security failures.


Most chemical and refinery processes follow LOPA and qualify for low-demand mode, with a maximum demand for a SIF of once a year. However in the offshore industry there is a rising demand for SIL based on high demand mode. Also in the case of machinery (IEC 62061) a high demand / continuous mode is required. Using high demand mode results in a different event scale, different likelihood formulas and LOPA no longer applies. Now let us look at cyber security and its likelihood scale. When we estimate risk in cyber physical systems we have to account for this, if we don’t a risk assessment might be a learning exercise because of the process it self but translating the results on a loss based risk scale would be fake.


Let us use the same line of thought used by process safety and translate this into the cyber security language. We can see a cyber attack as a Threat Actor applying a specific Threat Action to Exploit a Vulnerability, resulting in a Consequence. the consequence being a functional deviation of the target’s intended operation if we ignore cyber attacks breaching the confidentiality and focus on attacks attempting to impact the cyber physical system.

The threat actor + threat action + vulnerability combination has a certain event frequency, even if we don’t know yet what that frequency is, there is a certain probability of occurrence. That probability depends on many factors. Threat actors differ in capabilities and opportunity (access to target), also the exploit difficulties of a vulnerability differ and on top of all we protect these vulnerabilities using countermeasures (the protection layers in LOPA) we need to account for. We install antivirus to protect us against storing a malware infected file on the hard disk, we protect us against repeated logins that attempt brute force authentication by implementing a retry limit, we protect us against compromised login credentials by installing two factor authentication, etc. A vulnerability is not just a software deficiency, but also an unused open port on a network switch, or unprotected USB port on a server or desktop. There are hundreds of vulnerabilities in a system, each waiting to be exploited. There are also many cyber countermeasures, each with a certain effectiveness, each creating a protection layer. And with defense in depth we generally have multiple protection layers protecting our vulnerabilities. A very similar model as discussed for LOPA. This was recognized and a security method ROPA (Rings of Protection Analysis) was developed for physical security. Using the same principles to get a likelihood value based upon an event frequency.

Though ROPA was initially developed for physical security, this risk estimation method is and can also be used for cyber security. What is missing today is a standardized table for the IEF and the PFD of the various protection controls. This is not different from ROPA and LOPA because for both methods there is a guideline, but in daily practice each company defined its own list of IEF and PFDavg factors.

Another important difference with process safety is that cyber and physical security require like machinery a high demand / continuous mode which alters the risk estimation formulas (and event scales!), but the principles remain the same. So again the event frequency scale for cyber events differs from the event frequency scale used by LOPA. The demand rate for a firewall or antivirus engine is almost continuous, not limited to once a year like in the low demand mode of LOPA for process safety and derived from this business / mission risk.


The key message in above story is that the event scale used by process safety, for risk estimation is based upon failures of primarily physical equipment and accessories such as sealings and human errors. Where the event scale of cyber security is linked to the threat actor’s capabilities (Tactics, Techniques, Procedures), motivation, resources (Knowledge, money, access to equipment), opportunity (opportunities differ for an insider and outsider, some attacks are more “noisy” than others), it is linked to the effectiveness of the countermeasures (ease of bypassing, false negatives, maintenance), and the exposure of the vulnerabilities (directly exposed to the threat actor, requiring multiple steps to reach the target, detection mechanisms in place, response capabilities). These are different entities, resulting in different scales. We cannot ignore this when estimate loss based risk.

Accepting the conclusion that the event scales differ for process safety and for cyber security is accepting the impossibility to use the same risk assessment matrix for showing cyber security risk and process safety risk as is frequently requested by the asset owner. The impact will be the same, but the likelihood will be different and as such the risk appetite and tolerance criteria will differ.


So where are the flaws in IEC/ ISA 62443-3-2?

Starting with an inventory of the assets and channels in use is always a good idea. The next step, the High Level Risk Assessment (HLRA) is in my opinion the first flaw. There is no information available after the inventory to estimate likelihood. So it is suggested the method to set the likelihood to 1, basically risk assessment becomes a consequence / impact assessment at this point in time. An activity of the FMECA method. Why is a HLRA done, what is the objective of the standard? Well it is suggested that these results are later used to determine if risk is tolerable, if not a detailed risk assessment is done to identify improvements. It is also seen as a kind of early filter mechanism, focusing on the most critical impact. Additionally the HLRA should provide input for the zone and conduit analysis.

Can we using consequence severity / impact determine if the risk is tolerable (a limit suggested by ISA, the risk appetite limit is more appropriate than the risk tolerance limit in my view)?

The consequence severity is coming from the process hazard analysis (PHA) of the plant, so the HAZOP / LOPA documentation. I don’t think this information links to the likelihood of a cyber event happening. I give you a silly example to explain. Hazardous event 1, some one slaps me in the face. Hazardous event 2, a roof tile hits me on my head. Without the knowledge of likelihood (event frequency), I personally would consider the roof tile the more hazardous event. However if I would have some likelihood information telling me slapping me in the face would happen every hour and the roof tile once every 30 years I might reconsider and regret having removed hazard 1 from my analysis. FMECA is a far more valuable process than the suggested HLRA.

Does a HLRA contribute to the zone and conduit design? Zone boundaries are created as a grouping of assets with similar security characteristics following the IEC 62443 definition. Is process impact a security characteristic I can use to create this grouping? How can I relate a tube rupture in a furnace’s firebox to my security zone?

Well, then we must first ask ourselves how such a tube rupture can occur. Perhaps caused by a too high temperature, this I might link to a functional deviation caused by the control system or perhaps it might happen as the consequence that a SIF doesn’t act when it is supposed to act. So I may link the consequence to a process controller or maybe a safety controller causing a functional deviation resulting in the rupture. But this doesn’t bring me the zone, if I would further analyze how this functional deviation is caused I get into more and more detail, very far away from the HLRA. An APC application at the level 3 network segment could cause it, a modification through a breached BPCS engineering station at level 2 could cause it, an IAMS modifying the sensor configuration can cause it, and so on.

Security zone risk can be estimated in different ways, for example as zone risk following the ANSSI method. Kind of risk of the neighborhood you live in. We can also look at asset risk and set the zone risk equal to the asset with the highest risk. But all these methods are based on RPN, not on LBR.

HLRA’s just don’t provide valuable information, we typically use them for early filtering making a complex scope smaller. But that is neither required, nor appropriate for cyber physical systems. Doing a HLRA helps the risk consultant not knowing the plant or the automation systems in use, but in the process of estimating risk and designing a zone and conduit diagram it has no added value.

As next step ISA 62443-3-2 does a detailed risk assessment to identify the risk controls that reduce the risk to a tolerable level. This is another flaw because a design should be based upon an asset owner’s risk appetite, which is the boundary of the acceptable risk. The risk we are happy to accept without much action. The tolerable risk level is linked to the risk tolerance level, if we go above this we get unacceptable risk. An iterative detailed risk assessment identifying how to improve is of course correct, but we should compare with the risk appetite level not the risk tolerance level.

If the design is based on the risk tolerance level there is always panic when something goes wrong. Maybe our AV update mechanism fails, this would lead to an increase in risk, if we already are at the edge because of our security design we enter immediately in an unacceptable risk situation. Where normally our defense in depth, not relying on a single control, would give us some peace of mind to get things fixed. So the risk appetite level is the better target for risk based security design.

Finally there is this attempt to combine the process safety risk and the cyber security risk into one RAM. This is possible but requires a mapping of the cyber security risk likelihood scale on the process risk likelihood scale, because they differ. They differ not necessarily at a qualitative level, but the underlying quantitative mitigated event frequency scale differs. We can not say a Medium score on the cyber security likelihood scale is equivalent with a Medium score on the process safety likelihood scale. And it is the likelihood of the cyber attack that drives the cyber related loss based risk. We have to compare this with the process safety related loss based risk to determine the bigger risk.

This comparison requires a mapping technique to account for the underlying differences in event frequency. When we do this correctly we can spot the increase in business risk due to cyber security breaches. But only an increase, cyber security is not reducing the original process safety risk that determined the business risk before we estimated the cyber security risk.

So a long story, maybe a dull topic for someone not daily involved in risk estimation, but a topic that needs to be addressed. Risk needs a sound mathematical foundation if we want to base our decisions on the results. If we miss this foundation we create the same difference as there is between astronomy and astrology.

For me, at this point in time, until otherwise convinced by your responses, the IEC / ISA 62443-3-2 method is astrology. It can make people happy going through the process, but lacks any foundation to justify decisions based on this happiness.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site

The role of detection controls and a SOC

Abstract


This blog is about cyber security detection controls for cyber physical systems, process automation systems, process control systems or whatever we want to call them. The blog discusses their value in securing these systems and some of the requirements to consider when implementing them. As usual, my blogs approach the subject from a combination of the knowledge area of ​​cyber security and the knowledge area of ​​automation technology. More specific for this topic is the combination of Time Based Security and Asset Integrity Management.



It’s been a while since I started a blog, I postponed my retirement for another 2 years, so just too much to do to spend my weekends creating blogs. But sometimes the level of discomfort rises above my high alarm threshold for discomfort, forcing me to analyze the subject to better understand the cause of this discomfort. After seven months of no blogging, there are plenty of topics to discuss. For this blog I want to analyze the requirements for a cybersecurity detection function for cyber-physical systems. Do they differ from the requirements we set for information systems, and if so, what are these differences? Let’s start with the historical context.


Traditional cybersecurity concepts were based on a combination of fortress mentality and risk aversion. This resulted in the building of static defenses as described in the TCSEC and the Orange Book of the 1980s. But almost 40 years later, this no longer works in a world where the information resides increasingly at the very edge of the automation systems. Approximately 20 years ago a new security model was introduced as an answer to the increasing number of issues the traditional models were facing.

This new model was called Time Based Security, it is a dynamic view of cyber security based on protection, detection and response. Today we still use elements of this model, for example the NIST cybersecurity framework includes the TMS model by defining security as Identify, Protect, Detect, Respond and Recover. For the topic of the blog, I focus specifically on the three elements of the TMS model Protect, Detect and React. The idea behind this model is that the formula P> D + R defines a secure system. This formula expresses that the amount of time it takes for a threat actor to break through protection (P) must be greater than the time it takes to (D) detect the intrusion and the time it takes to respond ( R) on this intrusion.

Time Based Security model

In the days of the Orange Book we were building our fortresses, but also discovered that sooner or later someone found a path across, under or through the wall and we wouldn’t know about it. The TMS model kind of suggests that if we have a very fast detection and response mechanism, we can use a less strong protection mechanism. This is a very convenient idea in a world where systems become increasingly open.

This does not mean that we can throw away our protection strategies, it just means that in addition to protection, we can also implement a good detection and response strategy to compensate for a possible lack of protection. We need a balance, sometimes protection seems the logical answer, in other cases a focus on detection and response makes sense. If we compare this to physical security, it makes sense for a bank to protect a safe from the use of a torch burning through the safe’s wall. Delaying the attack increases the time we have to detect and respond. On the other hand, a counter that faces the public and is therefore relatively unprotected may benefit more from a panic button (detection) to initiate a response.

It is important to realize that detection and response are “sister processes” and that they are in series. If one fails, they both fail. Now with the concept of TMS in mind, let’s move on to a cyber attack on a physical cyber system.


To describe a cyber attack, I use the cyber kill chain defined by Lockheed Martin in combination with a so-called P-F curve. P-F curves are used in the Asset Integrity Management discipline to show equipment health over time to identify the interval between potential failure and functional failure. Since I need a relationship between time and the progress of a cyber attack, I borrowed this technique and created the following diagram.

P-F curve describing the cyber attack over time

A p-f curve has two axes, the vertical axis represents the cyber resilience of the cyber-physical system and the horizontal axis represents the progress of the attack over time. The curve shows several important moments in the time of the attack. The P0 point is where it all starts. In order for an attack to happen, we need a particular vulnerability, even more than this, the vulnerability must be exposed – the threat actor must be able to exploit it.

The threat actor who wants to attack the plant gathers information and looks for ways to penetrate the defenses. He / she can find multiple vulnerabilities, but eventually one will be selected and the threat actor will start developing an exploit. This can be malware that collects more information, but also when enough information has been collected, the code can be developed to attack the cyber-physical system (CPS).

To do this, we need a delivery method, sometimes along with a propagator module that penetrates deeper into the system to deliver the payload (the code that is doing the actual attack on the CPS) to one of the servers in the inner network segments of the system. This could be a USB stick containing malware, but it could also be a phishing email or a website infecting a user’s laptop and perhaps installing a keylogger that waits for the user to connect to the CPS from a remote location. It is not necessarily the factory it was initially aimed at, it could also be a supplier organization that builds the system or provides support services. Sensitive knowledge of the plant is stored in many places, different organizations build, maintain and operate the plant together and as such have a shared responsibility for the security of the plant. There are many scenarios here, for my example I propose that the attacker has developed malicious code with the ability to perform a scripted attack on the Basic Process Control System (BPCS). The BPCS is the automation function controlling the production process, if our target would be a chemical plant it will usually be a Distributed Control System (DCS).

The first time security is faced with the attack is on P1, where the chosen delivery method successfully penetrates the system to deliver its payload. Here we have protection mechanisms such as USB protection checks, antivirus protection, firewalls and maybe two-factor authentication against unauthorized logins. But we should also have detection controls, we can warn the moment a USB device is inserted, we can monitor who is logging into the system, we can even inspect what traffic is going through the firewall and see if it is using a suspicious amount of bandwidth , which indicates a download of a file. We can monitor many indicators to check if something suspicious is happening. All of this falls into a category defined as “early detection”, detection at a time when we can still stop the attack by an appropriate response before the attack hits the BPCS.

Nevertheless, our threat actor is skilled enough to slip through this first layer of defense and the malicious code delivers the payload to a server or desktop station of the BPCS. At this point (P2), the malicious code is installed in the BPCS and the threat actor is ready for its final attack (P3). We assume that the threat actor uses a script that describes the steps to attack the BPCS. Perhaps the script is writing digital outputs that shut down a compressor or initiate an override command to bypass a specific safety instrument function (SIF) in the safety system. Many scenarios are possible at this level in the system once the threat actor has gathered information about how the automation features are implemented. Which tag names represent which function, which parameters to change, which authorizations are required, which parameters are displayed, etc.

At this point, the threat actor passed several access controls that protect the inner security zones, passed controls that prevented malicious code from installing on the BPCS servers / desktops, and whitelisted the application controls that prevented execution of code. For detection at this level, we can use different audit events that signal access to BPCS system, we can also use anomaly detection controls that signal abnormal traffic. An important point here is that the attacker has already penetrated very deep into the system, at such a level that the reaction time to stop the attack is almost impossible without an automated response.

The problem with what we call “late detection” is that we need an automated response to be on time when the actor has an immediate malicious intent. Only when the threat actor postpones the attack until a later moment can we find the time to respond “manually”. However, an automated response requires a lot of knowledge of what to do in different situations and requires a high level of confidence in the detection system. A detection system that delivers an abundance of false positives would become a bigger threat to the production system than a threat actor.


If we look at how quickly attacks on cyber-physical systems progress, we can take Ukraine’s attack on the electricity grid as an example. The estimated time per attack here was estimated to be less than 25 minutes. In these 25 minutes – the speed of onset – the threat actors gained access to the SCADA system: opened the circuit breakers; corrupted the firmware of a protocol converter preventing the panel operators from closing the circuit breakers remotely; and wiped the SCADA hard drives. So in our theoretical TMS model, we would need a D + R time of less than 25 minutes to be effective, even if only partially effective, depending on the moment of detection. This is very short.

Can a security operations center fill this role? What would this require? Let us first look at the detection function to find an answer.


First of all we need a reliable detection mechanism, a detection mechanism that causes false positives will soon slow down any reaction. What is required for a reliable detection mechanism:

  • In-depth knowledge of the various events that can happen, what is an expected event and what is a suspicious event? This can differ depending on the plant’s modes such as: normal operation, abnormal operation, or emergency. Also system behavior is quite different during a plant stop. All of these conditions can be a source of suspicious events;
  • In-depth knowledge of the various protocols in use, for system’s such as DCS including a wide set of proprietary protocols not publicly documented. Also these have shown to be a considerable hurdle for anomaly detection systems;
  • In-depth knowledge of process operations, what activities are normal and which not? Should we detect the modification of the travel rate of a valve, is the change of this alarm setting correct, is disabling this process alarm a suspicious event or a normal action to address a transmitter failure? This level of detection is not even attempted today, anomaly detection systems might detect the program download of a controller or PLC, but the process operator would also know this immediately without a warning from the SOC. In all cases close collaboration with process operations is essential, this would slow down the reaction.

How if the security operations center (SOC) is outsourced, what would be different from an “in-company” SOC?

  • On the in depth knowledge of the various events that can happen, the outsourced SOC will have a small disadvantage because as an external organization the SOC will not always be aware of the the different plant states. But overall it will perform similarly as an in-company SOC.
  • On the in-depth knowledge of the various protocols, the outsourced SOC can have a disadvantage because it will have a bigger learning curve with multiple similar customers. Never the less knowledge of the proprietary protocols would remain a hurdle.
  • The in-depth knowledge of process operations is in my opinion fully out of reach for an outsourced SOC. As such control over this would remain primarily a protection task. Production processes are too specific to formulate criteria for normal and suspicious activity.

How about if the threat actor would also target the detection function? Disabling the detection function during the attack will certainly prevent the reaction. In the case of an outsourced SOC we would expect:

  • A dedicated connection between SOC and plant. If the connection would be over public connections such as the Internet a denial of service attack would become feasible to disable the detection function;
  • A local – in the plant – detection system would still provide information on what is going on if the connection to the SOC fails. The expertise of a SOC might be missing but the detection function would still be available;
  • The detection system would be preferably “out of band” because this would make a simultaneously attack on protection and detection systems more difficult.

How about the reaction function what do we need to have a reaction that can ‘outperform” the threat actor?

Reaction is a cyber physical system is not easy because we have two parts, the programmable electronic automation functions that are attacked and the physical system controlled by the automation system. The physical system has completely independent ‘dynamics”, we can’t just stop an automation function and expect the physical process to be stable in all cases. Cooling might be required, or Even during a plant stop we often need certain functions to be active. Even after a black shutdown – ESD 0 / ESD 0.1 – some functions are still required. There are rotating reactors that need to keep rotating to prevent a runaway reaction, a cement kiln needs to rotate otherwise it just breaks under its wait, cooling might be required to prevent a thermal runaway, and we need power for many functions.

Stopping a cyber attack by disconnecting from external networks is also not always a good idea. Some malware “detonates” when it looses its connection with a command and control server and might wipe the hard disk to hide its details. Detection therefore requires a good identification on what is happening and the reaction on this needs to be aligned with the attack but also with the production process. A wrong reaction can easily increase the damage.

While a SOC can often actively contribute to the response to a breach of the security of an information system, this is in my opinion not possible for a cyber-physical system. In a cyber-physical system, the state of the production process is essential, but also which automation functions remain active. In principle, a safety system – if present – can isolate process parts, make the installation pressure-less / de-energized, but even then some functions are required. Process operations therefore play a key role in the decision-making process, it is generally not acceptable to initiate an ESD 0 when a cyber attack occurs. So several preparatory actions are needed to organize a reaction, such as:

  • We need a disconnection process describing under what circumstances disconnection is allowed and what alternative processes need to startup when disconnection is activated. Without having this defined and approved before the situation occurs it is difficult to quickly respond;
  • We need to have playbooks that document what to do in what situation depending on which automation function is affected. Different scenarios exist we need to be ready and not improvise at the moment the attack occurs, some guidance is required;
  • We need to understand how to contain the attack, is it possible to split a redundant automation system in two halves, a not affected part and an affected part;
  • We need to understand if we can contain the attack to parts of the plant if multiple “trains” exist in order to limit the overall impact;
  • We need to test / train processes to make sure they work when needed.

All this would be documented in the incident handling process where containment and recovery zones, and response strategies are defined to organize an adequate and rapid response. But all this must be in accordance with the state of the production process, possible process reconstitution and the defined / selected recovery strategy.

Process operations plays a key role in the decision making during a cyber attack that impacts the physical system. As such a SOC is primarily advisor and spectator because a knowledge gap. Site knowledge is key here, detailed knowledge of the systems and their automation functions is essential for the reaction process.

Of course we should also think about recovery, but the first focus must be on detection and response, because here we can still limit the impact of the cyber attack if our response is timely and adequate. If we fail at this stage, the problems could be bigger than necessary. An OT SOC differs very much from an IT SOC and has a limited role because of the very specific requirements and unique differences per production process.

So in the early detection zone, a SOC can have a lot of value. In the late detection zone, in the case where the threat actor would act immediately, I think the SOC has a limited role and the site team should take up the incident handling process. But in all cases, with or without a SOC, detection and reaction is a key part of cyber security. It is important to realize that detection and reaction are “sister processes”, even the best detection system is rather useless if there is no proper reaction process that supports it.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site

Identifying risk in cyber physical systems

Abstract


This blog is about risk, more precise about a methodology to estimate risk in cyber physical systems. Additionally I discuss some of the hurdles to overcome when estimating risk. It is a method used in both small (< 2000 I/O) and large projects (> 100.000 I/O) with proven success in showing the relationship between different security design options, the cyber security hazards, and the change in residual cyber security risk.



I always thought the knowledge of risk and gambling would go hand in hand, but risk is a surprisingly “recent” discovery. While people gamble thousands of years, Blaise Pascal and Pierre de Fermat developed the risk methodology as recently as 1654. Risk is unique in the sense that it allowed mankind for the first time to make decisions based on forecasting the future using mathematics. Before the risk concept was developed, fate alone decided over the outcome. Through the concept of risk we can occasionally challenge fate.

Since the days of Pascal and De Fermat many other famous mathematicians contributed to the development of the theory around risk. But the basic principles have not changed. Risk estimation, as we use it today, was developed by Frank Knight (1921) a US economist.

Frank Knight defined some basic principles on what he called “risk identification”, I will quote these principles here and discuss them in the context of cyber security risk for cyber physical systems. All mathematical methods today estimating risk still follow these principles. There are some simple alternatives that estimate likelihood (this is generally the difficulty) of an event using some variables that influence likelihood (e.g. using parameters such as availability of information, connectivity, and management) but they never worked very accurate. I start with the simplest of all, principle 1 of the method.

PRINCIPLE 1 – Identify the trigger event

Something initiates the need for identifying risk. This can be to determine the risk of a flood, the risk of a disease, and in our case the risk of an adverse affect on a production process caused by a cyber attack. So the cyber attack on the process control and automation system is what we call the trigger event.

PRINCIPLE 2 – Identify the hazard or opportunity for uncertain gain.

This is a principal formulated in a way typical for an economist. In the world of process control and automation we focus on the hazards of a cyber attack. In OT security a hazard is generally defined as a potential source of harm to a valued asset. A source of discussion is if we define the hazard at automation system level or at process level. Ultimately we of course need the link to the production process to identify the loss event. But for an OT cyber security protection task, mitigating a malware cascading hazard is a more defined task than mitigating a too high reactor temperature hazard would be.

So for me the hazards are the potential changes in the functionality of the process control and automation functions that control the physical process. Or the absence of such a function preventing manual or automated intervention when the physical process develops process deviations. Something I call Loss of Required Performance (performance deviates from design or operations intent) or Loss of Ability to Perform (function is lost, cannot be executed or completed), using the terminology used by the asset integrity discipline.

PRINCIPLE 3 – Identify the specific harm or harms that could result from the hazard or opportunity for uncertain gain.

This is about consequence. Determining the specific harm in a risk situation must always precede an assessment of the likelihood of that harm. If we would start with analyzing the likelihood / probability, we would quickly be asking ourselves questions like “the likelihood of what?” Once the consequence is identified it is easier to identify the probability. In principal a risk analyst needs to identify a specific harm / consequence that can result from a hazard. Likewise the analyst must identify the severity or impact of the consequence. Here starts the first complexity when dealing with OT security risk. In the previous step (PRINCIPLE 2) I already discussed the reason for expressing the hazard initially at control and automation system level to have a meaningful definition I can use to define mitigation controls (Assuming that risk mitigation is the purpose of all this). So for the consequence I do the same I split the consequence of a specific attack on the control and automation system from the consequence for the physical production. When we do this we no longer have what we call a loss event. The consequence for the physical system results in a loss, like no product, or a product with bad quality, or worse perhaps equipment damage or fire and explosion, possibly injured people or casualties, etc.

The answer for this is, what is called a risk priority number. A risk priority number is based upon what we call consequence severity (just a value on a scale). Where “true” risk would be based on an impact expressed in terms of loss. A risk priority number can be used for ranking identified hazards, they cannot be used for justifying investments. For justifying investments we need to have a risk value based upon a loss. But this step can be achieved later. Initially I am interested in selecting the security controls that contribute most to reducing the risk for the control and automation system. Convincing business management to invest in these controls is a next step. To explain this, I use the following picture.

Risk process

In the middle of the picture there is the functional impact, the deviation in the functionality of the control and automation system. This functional deviation results in a change (or absence off) the control and automation action. This change will be the cause of a deviation in the physical process. I discuss this part later.

PRINCIPLE 4 – Specify the sequence of events that is necessary for the hazard or opportunity for uncertain gain to result in the identified harm(s).

Before we can estimate the uncertainty, the likelihood / probability, we need to identify the specific sequence of events that is necessary for the hazard to result in the identified consequence. The likelihood of that precise sequence occurring will define the probability of the risk. I can use the word risk here because this likelihood is also the likelihood we need to use for the process risk, because it is the cyber-attack that causes the process deviation and the resulting consequence. (See above diagram)

The problem we face that there are many paths leading to from the hazard to the consequence. We need to identify each relevant pathway. On top of this as cyber security specialists we need to add various hurdles for the threat actors to block them reaching the end of the path, the consequence of the attack. This is where counterfactual risk analysis offers the solution. This new methodology helps us achieve this. The method analysis each possible path, based upon a repository filled with hundreds of potential event paths, and estimates the resulting likelihood of each path. Which is the next topic, PRINCIPLE 5.

PRINCIPLE 5 – Identify the most significant uncertainties in the preceding steps.

We can read the time when this statement was written in the sentence “identifying the most significant uncertainties”. In times before counterfactual analysis we needed to limit the number of paths to analyze. This can lead to and actually did lead to incidents because of missing an event path that was considered insignificant or just not identified (e.g. the Fukushima Daiichi nuclear incident). The more complex the problem, the more event paths exist, the easier we forget one. Today the estimation of likelihood and so risk progressed and is dealt with differently. Considering the complexity of the control and automation systems we have today combined with the abundance of tactics, technologies, and procedures available for the threat actor to attack, the number of paths to analyze is very high. Traditional methods can only cover a limited amount of variations, generally obvious attack scenarios we are familiar with before we start the risk analysis. The result of the traditional methods do not offer the level of detail required. Such a method would spot the hazard of malware cascading risk, the risk that malware propagates through the network. But it is not so important to learn how high malware cascading risk is, it is more important to know if it exists, which assets and channels cause it, and which security zones are affected. This information results from the event paths used in described method.

These questions require a risk estimation with a level of detail missed by the legacy methods. This is specifically very important for OT cyber security, because the number of event paths leading to deviation of a specific control and automation function is much larger than for example the number of event paths identified in process safety hazard analysis. An average sized refinery quickly leads to over 10.000 event paths to analyze.


Still we need “true” risk, risk linked to an actual loss. So far we have determined the likelihood for the event paths, we have grouped these paths to link them to hazards, so we have a likelihood for a hazard and we have a likelihood that a specific consequence can happen. Happily we can consolidate the information at this point, because we need to assign severity. Consequences (functional deviations) can be consolidated in what are called failure modes.

These failure modes result in the deviations in the production process. The plant has conducted a process safety hazop (process hazard analysis for US readers) to identify the event paths for the production system. The hazop identifies for a specific physical deviation (e.g. too high temperature, too high pressure, reverse flow, etc.) what the cause could be of this deviation and what the consequence for the production system is. These process event paths have a relationship with the failure modes / consequences identified by the first part of the risk analysis. A specific cause is can only result from a specific failure mode. We can link the cause to the failure mode and get what is called the extended event path (See diagram above) This provides us with part of the production process consequences. These consequences have an impact, an actual loss to get the mission risk required for justification of cyber security investment.

But the hazop information does not provide all possible event paths because there might be a new malicious combination of causes missed (causes can be combined by an attacker in a single attack to create a bigger impact) and we can attack the safeguards. For example we have the safety instrumented system that implements part of the countermeasures that can become a new source of risk.

The role of the SIS

To explain the role of a SIS, I use above picture to show that OT cyber security has a limited scope within overall process safety (And it would be even more limited if I used the word safety that defines personal safety, process safety, and functional safety). Several of the safeguards specified for the process safety hazard might not be a programmable electronic system and as such not a target for a cyber attack. But some such as the safety instrumented system, or a boiler management system are, so we need to consider them in our analysis and add new extended event paths where required. TRISIS / TRITON showed us SIS is a source of risk.


Since the TRISIS / TRITON cyber attack we need to consider SIS also as a source of new causes most likely not considered in a hazop. The TRISIS/TRITON attack showed us the possibility of modifying the program logic of the logic solver. This can range from simple actions like not closing shutdown valves prior to opening blow down valves and initiating a shutdown action to more complex unit or equipment specific scenarios. Though at operations level we distinguish between manual and automated emergency shutdown, for cyber security we cannot make this difference. Automated shutdown meaning the the shutdown action is triggered by a measured trip level and manual shutdown meaning that the shutdown is triggered by a push button, within the SIS program it is all the same. Once a threat actor is capable of modifying the logic, the difference between manual and automated shutdown disappears and even the highest level of ESD (ESD 0) can be initiated, shutting down the complete plant, potentially with tampered logic.

Consequences caused by cyber attacks so far

If we would look at what would be the ultimate loss resulting from a cyber attack, The “only” loss not caused by a cyber attack are so far fire, explosion, and loss of life. This is not because a cyber attack has not the capability to cause these losses, but we were primarily lucky that some attacks failed. Let’s hope we can keep it that way by adequately analyzing risk and mitigating the residual risk to a level that is acceptable / tolerable.


I don’t want to make the blog too long, but in future blogs I might jump back to some of these principles. There is more to explain on the number of risk levels, how to make risk actionable, etc. If you would unravel the text and add some more detail that I didn’t discuss the used risk method is relatively simple as the next diagram shows.

NORSOK risk model

This model is used by the Norwegian offshore industry for emergency preparedness analysis. A less complex analysis as a cyber security analysis is but that difference is primarily in how the risk picture is established. This picture is from the 2010 version (rev 3) but not that different from the rev 2 version (2001) that is freely available on the Internet. This model is also very similar to ISO 31000 shown in the next diagram.

ISO 31000 risk model

If you read how and where these models are used and how field proven the models are, also in the control and automation world, might explain a bit how surprised I was when I noticed IEC/ISA 62443-3-2 invented a whole new approach with various gaps. New is good when existing methods fail, but if methods exist that meet all requirements for a field proven methodology I think we should use these methods. Plants and engineers don’t benefit from reinventing the wheel. I am adding IEC to the ISA 62443 because last week IEC approved the standard.

I didn’t make this blog to continue the discussion I started in my previous blog, though actually there was no discussion no counter arguments were exchanged – neither did I change my opinion, but to show how risk can / was / is used in projects is important. Specifically because the group of experts doing formal risk assessments is extremely small. Most assessments end up in a short list of potential cyber security risk without identifying the sources of this risk in an accurate manner. In those situations it is difficult understand which countermeasures and safeguards are most effective to mitigate the risk. It also would not provide the level of detail necessary for creating a risk register for managing cyber security based on risk.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site

ISA 62443-3-2 an unfettered opinion

Abstract

This blog is about the in April published new ISA 99 standard, where risk and securing process control and automation systems meet. My blog is an evaluation of part ISA 62443 3-2: Security risk assessment for system design – April 2020).

I write the blog because I struggle with several of the methods applied by the standard and apparent lack of input from the field. The standard seems to ignore practices successfully used in major projects today and replaces these by in my opinion incomplete and inferior alternatives. Practices that for example are used for process safety risk analysis.

Since I executed in recent years several very large risk assessments for greenfield refineries, chemical plants and national critical industry, my technical heart just can’t ignore this. So I wanted to address these issues, because I believe the end result of this standard does not meet the quality level appropriate for an ISA 62443 standard. Very hard conclusion I know, but I will explain in the blog why this is my opinion.

When criticizing the work of others, I don’t want to do this without offering alternatives, so also in this case where I think the standard should be improved I will give alternatives. Alternatives that worked fine in the field and where applied by asset owners with a great reputation in cyber security of their plants. If I am wrong, hopefully people can show me where I am wrong and convince me the ISA 62443 3-2 can be applied.

I have been struggling with the text of this blog for 3 weeks now, I found my response too negative and not appreciating all the work done by people in the task group primarily in their spare time. So let me, before continuing with my evaluation, express my appreciation for making the standard. It is important to have a standard on this subject and it is a lot of work to make it. Having a standard document is always a good step forward, even if just for target practicing. Never the less I also have to judge the content, therefore my evaluation.

It is a lengthy blog this time, even longer than usual. But not yet a book, for a book it lacks the details on how, it has a rather quick stop and not a happy end. Perhaps one day when I am retired and free of projects I will create such a book, this time just a lengthy blog to read. People that conduct or are interested in risk assessments for OT cyber security should read it, for all others it might be too much to digest. Just a warning.



Because I can imagine that not everyone reads or has read the ISA 62443-3-2, I provide a high level overview of the various steps. I can’t copy the text 1 on 1 from the standard, that would violate ISA’s copy right. So I have to do it using my own words, which are in general a little less formal than the standard’s text. Since making standards requires a lot of word smithing, I hope I don’t deviate too much from the intentions of the original text. For the discussion I focus on those areas in the standard that surprised me most.

The standard uses 7 steps between the start of a risk assessment project to the end.

  • First step is to identify what the standard calls the “system under consideration”. So basically making an inventory of the systems and its components that require protection;
  • Second step in the proposed process is an initial cyber security risk assessment. This step I will evaluate in more detail because I believe the approach here is wrong and I question if it really is a risk assessment;
  • Third step is to partition the system into zones and conduits. High level I agree with this part, though I do have some minor remarks;
  • Fourth step asks the question if the initial risk found in the second step exceeds tolerable risk? Because of my issues with step 2, I also have issues with the content of this step;
  • Fifth, if the risk exceeds tolerable risk a detailed risk assessment is required. I have a number of questions here, not so much the principle itself but the detail;
  • In the sixth step the results are documented in the form of security requirements, plus adding some assumptions and constraints. Such a result I would call a security design / security plan. The standard doesn’t provide much detail here, so only a few comments from my side;
  • And finally in the seventh step there is an asset owner approval. Too logical for debate.

High level these 7 steps represent a logical approach, it are the details within these steps that inspire my blog.

Let me first focus on some theoretical points considering risk, starting with the fundamental tasks that we need to do before being able to estimate risk and than check the standard how it approaches these tasks.


In order to perform a cyber security risk analysis, it is necessary to accomplish the following fundamental tasks:

  • Identify the assets in need of protection;
  • Identify the kind of risks (or threats) that may affect the assets;
  • Determine the risk criteria for both the risk levels as well as the actions to perform when a risk level is reached;
  • Determine the probability of the identified risk occurring;
  • And determine the impact or effect on the plant if a given loss occurs.

Let’s evaluate the first steps of the standard against these fundamental principles.


Which assets are in need of protection for an ICS/IACS?

The ISA 62443-3-2 standard document doesn’t define the term asset, so I have to read the IEC 62443-1-1 to understand what according to IEC/ISA 62443 an asset is. According to the IEC 62443-1-1 standard the asset is defined as – in less formal words as used by the standard – an asset is a “physical or logical object” owned by a plant. The standard is here less flexible than my words because an asset is not necessarily owned by a plant, but to keep things simple I take the most common case where the plant owns the assets. The core of the definition is, an asset is a physical or a logical object. So translated into technical language, an asset is either equipment or a software function.

IEC 62443-1-1 specifies an additional requirement for an asset, it needs to have either a perceived or actual value. Both equipment and a software function have an actual value. But there is in my opinion a third asset with a perceived value that needs protection. This is the channel, the communication protocol / data flow used to exchange data between the software functions. Not exactly a tangible object but still I think I can call at minimum an asset if I consider it a data flow using a specific protocol.

Protection of a channel is important, cyber security risk is for a large part linked to exposure of a vulnerability. Vulnerable channels, for example a data flow using the Modbus TCP / IP protocol (this protocol has several vulnerabilities that can be exploited), induce risk. So for me the system under consideration is:

  • The physical equipment (e.g. computer equipment, network equipment, and embedded devices);
  • The functions (software, for example SIS (Safety Instrumented System) and BPCS (Basic process Control System). But many more in today’s systems);
  • And the channels (the data flows, e.g. Modbus TCP/IP or a vendor proprietary protocol).

The ISA 62443-3-2 standard document doesn’t mention these three as explicitly as I do, but the text is also not in conflict with my definition of assets in need of protection. So no discussion here from my side. Before we can assess OT cyber security risk we need to have a good overview of these “assets”, the scope of the risk assessment.


The second step is an initial risk assessment, here I start to have issues. The standard asks us to identify the “worst case unmitigated cyber security risk” that could result from a cyber attack. It suggests to express this in terms of impact to health, safety, production loss, product quality, etc. This is what I call mission risk or business risk. The four primary factors that induce this risk are:

  • Process operations;
  • Process safety;
  • Asset integrity;
  • Cyber security;

Without process safety many accidents can occur, but even a plant in a perfect “safe” state can impact product quality and production loss. So we need to include process operations as well. Failing assets can also lead to production loss, or even impact to health. Asset integrity is the discipline that evaluates the maintenance schedules and required maintenance activities. Potential failures made by this discipline also add to the business / mission risk. And then we have cyber security. Cyber security can alter or halt the functionality of the various automation functions, and can alter data integrity, and even compromise the confidentiality of a plant’s intellectual property. All above are elements that can result in a loss and so induce mission risk. But cyber security can do more than this, it can make implemented safety integrity functions (SIF) for process safety ineffective, it can misuse the SIF logic to cause loss. Additionally cyber security can also cause excessive wear of process equipment not accounted for by asset integrity. Cyber security is an element that influences all.

For determining initial risk, the approach taken by the standard is to use the process hazard analysis (PHA) results as input for identifying the worst case impacts. And additional to this the standard requests us to consider information from the sector, governments, and other sources to get information on the threats.

I have several issues here. The first, can we have risk without likelihood? The PHA can define a likelihood in the PHA sheet, but this likelihood has no relationship with the likelihood of facing a cyber attack. So using it would would not result in cyber security risk.

Another point is that if we consider the impact, the PHA would offer us the worst case impact based upon the various deviations analyzed from a process safety perspective. But this is not necessarily the worse case impact from a business perspective.

See the definition for process safety: “The objective of process safety management is to ensure that potential hazards are identified and mitigation measures are in place to prevent unwanted release of energy or hazardous chemicals into locations that could expose employees and others to serious harm.”

The PHA would not necessarily analyze the impact of product quality for the company. Pharmaceutical business and food and beverage business can face major impact if its products would have a quality issue, while their production process can be relatively safe compared to a chemical plant.

If we would take the PHA as input, will it address the “worst case impact”? PHA will certainly be complete for the analysis of the process deviations (the structured approach of the PHA process enforces this) and complete for the influence of these deviations on process safety, so should also be complete for the consequences too if all process deviations are examined.

But the PHA might not be complete when it comes to the possible causes, because PHA generally doesn’t consider malicious intent. So there might be additional causes that are not considered as possible by the PHA.

Causes are very important because these result from functional deviations as result of the cyber attack. It is the link between the functional deviation and its physical effect on the production process that causes the process deviations and its consequence / impact.

If it is not guaranteed that the PHA covers all potential causes, the reverse path from “worst case impact” in the PHA to the “cyber security functional deviation” that causes a process deviation is interrupted. This interruption doesn’t only prevent us from getting a likelihood value, but also prevents us from identifying all mitigation options. Walking the event path in the reverse direction is not going to bring us the likelihood of the process deviation happening as result of a cyber attack, so we don’t have risk.

If I follow the methodology of analyzing risk using event paths, I have the following event path:

A threat actor executes a threat action to exploit a vulnerability resulting in some desired consequence, this consequence is a functional deviation causing a process deviation with some process consequence.

The process consequence has a specific impact for the business / mission, such as production loss, potential casualties, a legal violation, etc. This impact (expressed as loss) creates business risk.

The picture shows that the risk path between a cyber security breach resulting in mission impact requires several steps. The standard jumps right to the end (business impact) not considering intermediate consequences, by doing this the standard ignores options to reduce risk. But more on this later.

The path toward mission risk

So as an example of an event path: A nation sponsored organization (threat actor) gains unauthorized access into an ICS (threat action) by capturing the access credentials of an employee without two factor authentication (vulnerability), modifying the range of a tank level instrument (functional deviation), causing a too high level in the tank (process deviation) with as potential consequence overfilling the tank (process consequence) resulting in a loss of containment of a potentially flammable fluid causing toxic vapors requiring an evacuation resulting in potentially multiple casualties and an approximate $500.000 production and cleaning cost loss (business impact).

An extended event path in more detail

The likelihood that this event path, scenario, happens as result of a cyber attack is determined by the likelihood of the cyber security failure. The PHA might have considered a similar process deviation (High level in the tank) during the analysis, perhaps with as cause mentioned a failed level transmitter, and reached the same process consequence as potential loss of containment. All very simplified, don’t worry we do apply additional controls.

But the likelihood assigned to this process safety hazard would have been derived from a LOPA (Layers Of Protection Analysis) assignment based on an initiating frequency assignment and an IPL (Independent Protection Layer) reduction factor and MTBF factors of the instrument to estimate a SIL required for the safeguard. There is no relationship between the likelihood of the process deviation in the PHA and the cyber security likelihood.

Important is to realize that not all risk estimates are necessarily linked to a loss. Ideally this is so, because the loss justifies the investment in mitigation. But in many cases we can use what are called risk priority numbers, a risk score based on likelihood and severity for ranking purposes. A risk priority number is often enough for us to decide on mitigation and prioritizing mitigation. For design we only need business risk if the investment needs to be justified. The risk priority numbers already show the most important risk from a technical perspective.

However my conclusion is that the standard is not approaching the initial risk assessment by estimating cyber security risk, it seems to focus on two other aspects:

  • What is the worst impact (Expressed as a loss);
  • and what does the threat landscape look like.

Neither of them providing a risk value. I fully understand the limitation, because so early in a project there is not enough information available to estimate risk at a level of detail showed above.

So in my opinion an alternative approach is required, and such alternatives exist. Better they have been widely applied in the industry in recent years, but for some reason are ignored by the task group and replaced by something questionable in my opinion.

So how did projects resolve the lack of information and still get important information for understanding the business impact and threats to protect against? Following activities were performed in projects:

  • Create a threat profile by conducting a threat assessment;
  • Conduct a criticality assessment / business impact analysis.

What is a threat profile? The objective of a threat profile is to:

  • Identify the threat actors to be considered;
  • Identify and prioritize cyber security risk;
  • Align information security risk and OT security risk strategies within the company.

Identifying and prioritizing cyber security risk is done by studying the threat landscape based upon various reliable sources, such as information from a local CERT, MITRE, FIRST, ISF, and various commercial sources. These organizations show the developments in the threat landscape explaining the activities of threat actors and what they do.

Threat actors are identified and their relevance for the company can be rated based on criteria such as: intent, origin, history, motivation, capability, focus. Based on these criteria a threat strength and likelihood can be estimated. Various methods have been developed, for example the method developed by ISF is frequently used.

Based on the information on threat actors and their methods and their focus, a threat heat map is created. So the asset owner can decide on what the priorities are. This is an essential input for anyone responsible for the cyber security of a plant, but also important information for a cyber security risk assessment. Threat actors considered as relevant, play a major role in the required risk reduction for an appropriate protection level. If we don’t consider the threat actor we will quickly over-spend or under-spend on risk mitigation.

In the ISA 62443-3-2 context, the target security level (SL-T) is used as the link toward the threat actor. Because ISA security levels link to motivation, capability, and resources of the threat actor, a security level also identifies a threat actor. The idea is to identify a target security level for each security zone and use this to define the technical controls for the assets in the zone, specified as capability security levels (SL-C) in the IEC 62443-3-3. The IEC 62443-3-3 provides the security requirements that the security zones and conduits must meet to offer the required level of protection.

The ISA 62443-3-2 document does not explain how this SL-T is defined. But if the path is to have an SL-T per security zone, then we need to estimate zone risk. Zone risk is something very different from asset risk or threat based risk. The ANSSI standard provides a method to determine zone risk and uses the result to determine a security class (A,B, C) something similar as the ISA security levels.

I would expect a standard document on security risk assessment to explain the zone risk process, but the standard doesn’t. Because the methodology actually seems to continue with an asset based risk approach I assume the idea is that the asset with the highest risk level in a zone determines the overall zone risk level. This is a valid approach but more time consuming than the ANSSI approach.

For a standard / compliance based security strategy a zone risk approach would have been sufficient. The use of SL-T and SL-C and reference to IEC 62443-3-3 seems to suggest a standard’s / compliance based security approach.


How about the other method in use, the criticality assessment. What does it offer? The criticality assessment helps to establish the importance of each functional unit and business process as it relates to the production process. Illustrating which functions need to be recovered, how fast do they need to be recovered and what their overall importance is from both a business perspective as well as from a cyber security perspective. Which are two totally different perspectives. An instrument asset management system might have a low importance from a business point of view, but because of its connectivity to all field instrumentation it can be considered an important system to protect from a cyber security perspective.

So executing a criticality assessment as second step provides the criticality of the functions (importance and impact do correlate), and it provides us with information on the recovery timing.

OT cyber security risk should not exclusively focus on the identification of the risk related to the threats and how to mitigate it. Residual business risk is not only influenced by preventative and detective controls but also by the recovery potential and speed, because the speed of recovery determines business continuity and lack of business continuity can be translated to loss.

ISA 62443-3-2 doesn’t address the recovery aspect in any way. As the risk assessment is used to define the security requirements, we can not ignore recovery requirements. NIST CSF does acknowledge recovery as an important security aspect, I don’t understand why the ISA 62443-3-2 task group ignored recovery requirements as part of their design risk assessment.

It is important to know the recovery point objective (RPO), recovery time objective (RTO) and maximum tolerable downtime (MTD) for the ICS / IACS. Designing recovery for a potential cyber threat, for example a ransomware infection, differs quite a lot from data recovery from an equipment failure.

In a plant with its upstream and down stream dependencies and storage limitations, these parameters are important information for a security design. See below diagram for the steps in a typical cyber incident. Depending on their detailed procedures, these steps can be time consuming.

Response and recovery

The criticality assessment investigates Loss of Ability to Perform over a time span, for example how do we judge criticality after 4 hours, 8 hours, a day, a week, etc… This allows us to consider the dependencies of upstream and downstream processes, and storage capacity. But apart from looking at loss of ability to perform, loss of required performance and loss on confidentiality are also evaluated in a cyber security related criticality assessment. Specifically the loss of required performance links to the “worst impact” looked for by the ISA 62443-3-2.

We also need to consider recovery point objectives (RPO) and understand how the plant wants to recover, are we going to use the most recent controller checkpoint or are there requirements for a controller checkpoint that brings the control loops into an known start-up state.

We need to understand the requirements for the recovery time objective (RTO), this differs for cyber security compared to a “regular” failure. For cyber security we need to include the time taken by the incident response tasks, such as containment and eradication of the potential malware or intruder.

It makes a big difference in time if our recovery strategy opts for restoring a back-up to new hard drives, or if we decide to format the hard drives before we restore (and what type of reformatting would be required). Other choices to consider are back-up restore over the network from one or more central locations, or restore directly at computer level using USB drives. All of this and more has time and cost impact that the security design needs to take into account.

The role of the criticality assessment is much bigger than discussed here, but it is an essential exercise for the security design and as such for the risk assessment that also requires us to assess consequence severity. Consequence severity analysis is actually just an extension of the criticality analysis.

Another important aspect of criticality analysis is that it includes ICS / IACS functions not being related to any of the hazards identified by the PHA. For our security design we need to include all IACS systems, not limit our selves to systems at Purdue reference model level 0, 1 and 2.

A modern IACS has many functions, all ignored by the ISA 62443-3-2 standard if we start at the PHA. IACS includes not only the systems at the Purdue level 0, 1 and 2, (systems typically responsible for the PHA related hazards) but also the systems at level 3. Systems that can still be of vital importance for the plant. The methodology of the standard seems to ignore these.

Another role for the criticality assessment is directly related to the risk assessment. An important question in a large environment is do we assess risk per sub-system or for the whole system. Doing it for the whole system (IACS) with all its sub-systems (BPCS, SIS, MMS, …) and a large variation of different consequences and cross relations, or do we assess risk per function and consolidate these results for comparison in for example a risk assessment matrix.

The standard seems to go for the first approach, which in my opinion (based upon risk assessments for large installations) is a far too difficult and complex exercise. If we keep the analysis very general (and as a result superficial, often at an informal gut-feeling-risk level) it is probably possible, but the results often become very subjective and we miss out on the benefits that other methods offer.

As the base for a security design that is resilient to targeted attacks and its subsequent risk based security management (this would require a risk register) of the complete ICS/IACS, I believe it is an impossible task. All results of a risk assessment need to meet the sensitivity test, and the results need to be discriminitive enough to have value. This requires that methods applied, prevent any subjective inputs that steer the results into a specific direction.

If we select a risk assessment approach per function to allow for more detail, we have to take the difference in criticality of the function into account when comparing risk of different functions. This is of minor importance when we compare risk results from SIS (Safety Instrumented System) or BPCS (Basic Process Control System), because both are of vital importance in a criticality analysis. But we will already see differences in results when we would compare BPCS with MMS (Machine Monitoring System), IAMS (Instrument Asset Management System) or DAHS (Data Acquisition Historian System).


As I already mentioned in my previous blog, risk assessment methodologies have evolved and the method suggested by ISA 62443-3-2 seems to drive toward an approach that can’t handle the challenges of today’s IACS. Certainly not for the targeted attacks where threat actors with “IACS specific skills” ( SL 3, SL 4). To properly execute a risk assessment in an OT environment requires knowledge on the different methods for assessing risk, their strong and weak points, and above all a clear objective for the selected method.

So to conclude my assessment of the second step of the ISA 62443-3-2 process, “Initial risk assessment”, I feel the task group missed too much in this step. The result offers too little, is incomplete and actually providing very little useful information for the next steps, among which the “security zone partitioning”.

Now lets look at the zone partitioning step, to see how the standard and my field experience aligns here.


First of all what is the importance of security zone partitioning with regard to security risk assessment?

  • If we want to use zone risk we need to know the boundaries of the security zone;
  • For asset risk and threat based risk we need to know the exposure of the asset / channel and connectivity between zones over conduits is an important factor.

So it is an important step in a security risk assessment, even for none security standard based strategies. Let’s start with the overview of what project steps the standard specifies:

  • Establish zones and conduits;
  • Separate business and ICS/IACS assets;
  • Separate safety related assets;
  • Separate devices that are temporarily connected;
  • Separate wireless devices;
  • Separate devices connected via external networks.

Looks like a logical list to consider when creating security zones, but certainly not a complete list. The list seems to be driven by exposure, which is good. But there are other sources of exposure. We can have 24×7 manned and unmanned locations, important for yes / no a session lock of operator stations, so a security characteristic. We have to consider the strength of the zone boundary, is it a physical perimeter (e.g. network cable connected to the port of a firewall), a logical perimeter (e.g. a virtual LAN), or do we have a software defined perimeter (e.g. a hypervisor that separates virtual machines on virtual network segments).

The standard, and as far as I am aware none of the other ISA standards, consider virtualization. This is a surprise for me because virtualization seems to be core for the majority of greenfield projects, and even as part of brown field upgrade projects virtualization is a frequent choice today. Considering that the standard is issued April 2020, and ISA has a policy to refresh standards every 5 years, this is a major gap because software zone perimeters for security zones is an important topic.

Considering that virtualization is a technology used in many new installations, and considering the changes that technology like APL and IIoT are bringing us. Not addressing these technologies in a risk based design document that discusses zone partitioning makes the standard almost obsolete in the year it is issued.

Perhaps a very hard verdict, but a verdict based on my personal experience where 4 out of 5 large greenfield projects were based on virtualized systems a subject that should have been covered. Ignoring virtualization for zone partitioning is a major gap in 2020 and the years to come.

There is a whole new “world” today of virtual machine hosts, virtual machines, hardware clusters, and software defined perimeters. And this has nothing to do with the world of private clouds or Internet based clouds, virtualization is proven technology for at least 5+ years now, conquering ICS/IACS space with increasing speed. It should not have been missed.

The 62443-3-2 standard is not very specific with regard to the other subjects in this step, so little reason for me to criticize the remainder of the text. If I have to add a point, then I might say that the paragraph on separating safety and non-safety related assets is very thin. I would have expected a bit more in April 2020, plenty of unanswered design questions for this topic.


The next step the standard asks us to do is “risk comparison“, we have to compare initial risk (step 2) with residual risk, the risk after the zone partitioning step. There is the “little” issue that neither in the initial risk assessment step, nor in the zone partitioning step we estimate risk. Nor do we establish anywhere risk criteria, important information when we want to compare risk.

Zone partitioning does change the risk, we influence exposure through connectivity, but there is no risk estimated in the partitioning step. Perhaps the idea is to take the asset with the highest risk in the zone and use this for the SL-T / SL-C and identify missing security requirements, but this is not specified and would be an iterative process because also asset risk depends among others on exposure from connectivity.

I had expected something in the partitioning task that would estimate / identify zone risk and assign the zone a target security level using some transformation matrix from risk to security level. The standard doesn’t explain this process, it doesn’t seem to be an activity of the zone partitioning task, it doesn’t refer to another standard document for solving it. Which is an omission in my opinion.

But ok no problem, if we can’t accept the residual risk we are going to do the next step, the detailed risk assessment and keep iterating till we accept the residual risk. So perhaps I must read this more as a first step in an evaluation loop. Doesn’t take away that if I decide first time I am happy with the residual risk, I will have nothing else than what the initial risk assessment produced, and this was not cyber security risk.


The fifth step is the detailed risk assessment. Let’s see what we need to do:

  • Identify cyber security threats;
  • Identify vulnerabilities;
  • Determine consequences and impact;
  • Determine unmitigated likelihood;
  • Determine unmitigated cyber security risk;
  • Determine security level target to link to the IEC 62443-3-3 standard.

If the unmitigated risk exceeds tolerable risk we need to continue with mitigation. Following steps are defined:

  • We need to identify and evaluate existing countermeasures;
  • We are asked to reevaluate the likelihood based on these existing countermeasures;
  • Determine the new residual risk;
  • Compare residual risk against tolerable risk and reiterate the cycle if the residual risk is still too high;
  • If all residual risk is below the tolerable risk, we document the results in the risk assessment report.

To do all of the above we need to have risk criteria, these are not mentioned in the standard neither is mentioned what criteria there are. The standard seems to adopt the three risk levels often used for process safety: acceptable risk, tolerable risk, and unacceptable risk.

Unfortunately this is too simple for cyber security risk. When process safety risk is unacceptable, an accepted policy is too stop and fix it before continuing. For tolerable risk there would be a plan in place on how to improve it when possible.

Cyber security doesn’t work that way, I have seen many high cyber security risks, but only in a few cases noted that plant managers were willing to accept a loss (production stop) to fix it. An example where loss because of security risk was accepted was when Aramco and 2 weeks later Qatar gas were attacked by the Shamoon malware. At that time the regional governments instructed the plants to disconnect the ICS/IACS from their corporate network, this induces extra cost. We have seen similar decisions caused by ransomware infections, plants pro-actively stopping production to prevent an infection propagating.

Cyber security culture differs from process safety culture, this translates into risk criteria and the action-ability of risk. The less risk levels, the more critical the decision. As result, plants seem to have a preference for 5 or 6 risk levels. This allows them a bit more flexibility.

Tolerable risk is the “area” between risk appetite and risk tolerance. Risk appetite being the level we can continue production without actively pursuing further risk reduction, and risk tolerance being the limit above which we require immediate action. Risk criteria are important, in the annex ISA 62443-3-2 provides some examples in risk matrices. A proper discussion on risk criteria is missing. Likelihood levels, severity levels, impact levels, importance levels all need to be defined. It is important that if we say this is a high risk, all involved understand what this means. Also actions need to be defined for a risk level, risk needs to result into some action if it exceeds a level.

The standard limits itself to business risk, impact expressed as a loss. Business risk is great to justify investment but does very little for identifying the most important mitigation opportunities because it is a worst case risk. It is like saying if I am walking in a thunderstorm I can die from being struck by lightning, so I no longer need to analyze the risk using a zebra to cross the road.

Another point of criticism I have is why only risk reduction based on likelihood reduction is considered. The standard seems to ignore addressing opportunities on the impact side for taking away consequences? Reduction on the consequence side has proved to be far more effective. In the methodology chosen by the standard this is not possible because the only impact / consequence recognized is the ultimate business impact. The consequences leading to this impact, the functional deviation in IACS functions, are not considered.

Risk event path

The three step process described in above block diagram of risk and shown in more detail in my previous blog as the “event path” doesn’t exist for the ISA adopted method. Though it are the countermeasures and safeguards we use to reduce the cyber security risk.

For example there are many plants that do not allow the use of the Modbus TCP/IP protocol for switching critical process functions using PLCs that depend on Modbus communication. If such an action is required they hardwire the connection to prevent being vulnerable for various Modbus TCP/IP message injection and modification attacks. This is a safeguard taking a way a very critical consequence such as an unauthorized start or stop of a motor, compressor or other by injecting a Modbus message.

Another point we are asked to do is to determine the security level target (SL-T). Well assuming there is some transformation matrix converting risk into security level (not in the ISA 62443-3-2) we can do this, but how?

It is a repeating issue, the standard doesn’t explain if I need to use zone risk like ANSSI does, or determine zone risk as the asset with the maximum risk in a zone. And when I have risk what would be the SL-T?

Once we have an SL-T we can compare this with the security level capability (SL-C) to get the security requirements from the IEC 62443-3-3. ISA 62443-3-2 seems to be restrict to the standard based security strategy. A good point to start but not a solution for critical infrastructure.

ISA 62443 3-2 is a standards-based security strategy.

Another surprise I have is the focus on the unmitigated risk, why not include the existing countermeasures immediately? Why are we addressing risk mitigation exclusively by addressing likelihood. Where do we include the assets to protect (equipment, function, channel)? I think I know the answer, the risk methodology adopted doesn’t support it. The task group either didn’t investigate the various risk estimation methodologies available or worked for some reason toward applying a methodology that is not capable of estimating risk for multiple countermeasures / safeguards. Which is strange choice because in process safety this methodology is successfully applied through LOPA.


So how to summarize this pile of criticism? First of all I want to say that this is the standard document I criticize the most, maybe because it is the subject that comes closest to my work. There are always small points where opinions can deviate, but in this case I have the feeling the standard doesn’t offer what it should bring, it seems to struggle with the very concept of risk analysis. Which is amazing because of the progress made by both science and asset owners in recent years.

Because risk is such an essential concept for cyber security I am disappointed in the result, despite all the editing of this blog and the many versions that were deleted I think the blog still shows this disappointment.

It is my feeling that the task group didn’t investigate the available risk methodologies sufficiently, didn’t study the subject of risk analysis, and they didn’t seem to compare results of the different methods. They aimed for one method and wrote the standard around it. That is a pity because it will take another 5 years before we see an update and 5 years in cyber security are an eternity.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site

Playing chess on an ICS board


Abstract

This week’s blog discusses what a Hazard and Operability study (HAZOP) is and some of the challenges (and benefits) it offers when applying the method for OT cyber security risk. I discuss the different methods available, and introduce the concept of counterfactual hazard identification and risk analysis. I will also explain what all of this has to do with the title of the blog, and I will introduce “stage-zero-thinking”, something often ignored but crucial for both assessing risk and protecting Industrial Control Systems (ICS).


What inspired me this week? Well one reason – a response from John Cusimano on last week’s Wake-up call blog.

John’s comment: “I firmly disagree with your statement that ICS cybersecurity risk cannot be assessed in a workshop setting and your approach is to “work with tooling to capture all the possibilities, we categorize consequences and failure modes to assign them a trustworthy severity value meeting the risk criteria of the plant.”.  So, you mean to say that you can write software to solve a problem that is “impossible” for people to solve.  Hm. Computers can do things faster, true. But generally speaking, you need to program them to do what you want. A well facilitated workshop integrates the knowledge of multiple people, with different skills, backgrounds and experience. Sure, you could write software to document and codify some of their knowledge but, today, you can’t write a program to “think” through these complex topics anymore that you could write a program to author your blogs.”

Not that I disagree with the core of John’s statement, but I do disagree with the role of the computer in risk assessment. LinkedIn is a nice medium, but responses always are a bit incomplete, and briefness isn’t one of my talents. So a blog is the more appropriate place to explain some of the points raised. Why suddenly an abstract? Well this was an idea of a UK blog fan.

I write my blogs not for a specific public, though because of the content, my readers most likely are involved in securing ICS. I don’t think the “general public” public can digest my story easily, so they probably quickly look for other information when my blog lands in their window or they read it till the end and think what was this all about. But there is a space between the OT cyber security specialist, and the general public. I call this space “sales” technical guys but at a distance, and with the thought in mind that “if you know the art of being happy with simple things, then you know the art of having maximum happiness with minimum effort”, I facilitate the members of this space by offering a content filter rule – the abstract.


The process safety HAZOP or Process Hazard Analysis as non-Europeans call the method, was a British invention in the mid-sixties of the previous century. The method accomplished a terrific breakthrough in process safety and made the manufacturing industry a much safer place to work.

How does the method work? To explain this I need to explain some of the terminology I use. A production process, for example a refinery process, is designed creating successive steps of detail. We start with what is called a block flow diagram (BFD), each block represents a single piece of equipment or a complete stage in the process. Block diagrams are useful for showing simple processes or high level descriptions of complex processes.

For complex processes the BFD use is limited to showing the overall process, broken down into its principal stages. Examples of blocks are a furnace, a cooler, a compressor, or a distillation column. When we add more detail on how these blocks connect, the diagram is called a process flow diagram. A process flow diagram (PFD) shows the various product flows in the production process, an example of a PFD is the next text book diagram of a nitric acid process.

Process Flow Diagram. (Source Chemical Engineering Design)

We can see the various blocks in a standardized format. The numbers in the diagram indicate the flows, these are specified in more detail in a separate table for composition, temperature, pressure, … We can group elements in what we call process units, logical groups of equipment that accomplish together a specific process stage. But what we are missing here is the process automation part, what do we measure, how do we control the flow, how do we control pressure? This type of information is documented in what is called a piping and instrument diagram (P&ID).

The P&ID shows the equipment numbers, valves, the line numbers of the pipes, the control loops and instruments with an identification number, pumps, etc. Just like for PFDs we also used use standard symbols in P&IDs to describe what it is, to show the difference between a control valve and a safety valve using different symbols. The symbols for the different types of valves already covers more than a page. If we look at the P&ID of the nitric acid process and zoom into the vaporizer unit we see that more detail is added. Still it is a simplified diagram because the equipment numbers and tag names are removed, alarms have been removed, and there are no safety controls in the diagram.

The vaporizer part of the P&ID (Source Chemical Engineering Design)

On the left of the picture we see a flow loop indicated with FIC (the F from flow, the I from indicator, and the C from control), on the right we see a level control loop indicated with (LIC). We can see which transmitters are used to measure the flow (FT) or the level (LT). We can see the that control valves are used (the rounded top of the symbol). Though above is an incomplete diagram, it shows very well the various elements of a vaporizer unit.

Similar diagrams, different symbols and of course a totally different process, exist for power.

When we engineer a production / automation process P&IDs are always created to describe every element in the automation process. When starting an engineering job in the industry, one of the first things to learn is this “alphabet” of P&ID symbols the communication language for documenting the relation between the automation system (the ICS) and the physical system. For example the FIC loop will be configured in a process controller, there will be “tagnames” assigned to each loop, graphic displays created so the process operator can track what is going on and intervene when needed. Control loops are not configured in a PLC, process controllers and PLCs are different functions and have a different role in an automation process.


So far the introduction for discussing the HAZOP / PHA process. The idea behind a HAZOP is that we want to investigate: What can go wrong; What the consequence of this would be for the production process; And how we can enforce that if it goes wrong the system is “moved” to a safe state (using a safeguard).

There are various analysis methods available, I discuss the classical method because this is similar to what is called a computer HAZOP and like the method John suggests. The one that is really different, counterfactual analysis, and is especially used for complex problems like OT cyber security for ICS I discuss last.

A process safety HAZOP is conducted in a series of workshop sessions with participation of subject matter experts of different disciplines (Operations, safety, maintenance, automation, ..) and led by a HAZOP “leader”, someone not necessarily a subject matter expert on the production process but a specialist in the HAZOP process it self. The results of HAZOPs are as good as the participants and even with very knowledgeable subject matter experts and an inexperienced HAZOP leader results might be bad. Experience is a key factor in the success of a HAZOP.

The inputs for the HAZOP sessions are the PFDs and P&IDs. P&IDs typically represent a process unit but if this is not the case, the HAZOP team selects a part of the P&ID to zoom into. HAZOP discussions focus on process units, equipment and control elements that perform a specific task in the process. Our vaporizer could be a very small unit with a P&ID. The HAZOP team could analyze the various failure modes of the feed flow using what are called “guide words” to guide the analysis in the topics to analyze. Guide words are just a list of topics used to check a specific condition / state. For example there is a guide word High, and another Low, or No, and Reverse. This triggers the HAZOP team to investigate if it is possible to have No flow, is it possible to have High flow, Low flow, Reverse flow, etc. If the team decides that it is possible to have this condition, for example No Flow, they write down the possible causes that can create the condition. What can cause No flow, well perhaps a cause is a valve failure or a pump failure.

When we have the cause we also need to determine the consequence of this “failure mode”, what happens if we have No flow or Reverse flow. If the consequence is not important we can analyze the next, otherwise we need to decide what to do if we have No flow. We certainly can’t keep heating our vaporizer, so if there is no flow so we need to do something (the safeguard).

Perhaps the team decides on creating a safety instrumented function (SIF) that is activated on a low flow value and shuts down the heating of the vaporizer. These are the safeguards, initially high level specified in the process safety sheet but later in the design process detailed. A safeguard can be executed by a safety instrumented system (SIS) using a SIF and are implemented as mechanical devices. Often multiple layers of protection exist, the SIS being only one of them. A cyber security attack can impact the SIS function (modify it, disable it, initiate it), but this is something else as impacting process safety. Process safety typically doesn’t depend on a single protection layer.

Process safety HAZOPs are a long, tedious, and costly process that can take several months to complete for a new plant. And of course if not done in a very disciplined and focused manner, errors can be made. Whenever changes are made in the production process the results need to be reviewed for their process safety impact. For estimating risk a popular method is to use Layers Of Protection Analysis (LOPA). With the LOPA technique, a semi-quantitative method, we can analyze the safeguards and causes and get a likelihood value. I discuss the steps later in the blog when applied for cyber security risk.

Important to understand is that the HAZOP process doesn’t take any form of malicious intent into account, the initiating events (causes) happen accidentally not intentionally. The HAZOP team might investigate what to do when a specific valve fails closed with as consequence No Flow, but will not investigate the possibility that a selected combination of valves fail simultaneously. A combination of malicious failures that might create a whole new scenario not accounted for.

A cyber threat actor (attacker) might have a specific preference on how the valves need to fail to achieve his objective and the threat actor can make them fail as part of the attack. Apart from the cause being initiated by the threat actor, also the safeguards can be manipulated. Perhaps safeguards defined in the form of safety instrumented functions (SIF) executed by a SIS or interlocks and permissives configured in the basic process control system (BPCS). Once the independence of SIS and BPCS is lost the threat actor has many dangerous options available. There are multiple failure scenarios that can be used in a cyber attack that are not considered in the analysis process of the process safety HAZOP. Therefore the need for a separate cyber security HAZOP to detect this gap and address it. But before I discuss the cyber security HAZOP, I will briefly discuss what is called the “Computer HAZOP” and introduce the concept of Stage-Zero-Thinking.

A Computer HAZOP investigates the various failure modes of the ICS components. It looks at the power distribution, operability, processing failures, network, fire, and sometimes at a high level security (can be both physical as well as cyber security). It might consider malware, excessive network traffic, a security breach. Generally very high level, very few details, incomplete. All of this is done using the same method as used for the process safety HAZOP, but the guide words are changed. In a computer HAZOP we work now with guide words such: “Fire”, Power distribution” “Malware infection”, etc. But still document the cause, consequence, and consider safeguards in a similar manner as for the process safety HAZOP. Consequences are specified at high level such as loss of view, loss of control, loss of communications, etc.

At a level we can judge their overall severity but not link it to detailed consequences for the production process. Cyber security analysis at this level would not have foreseen such advanced attack scenarios as used in the Stuxnet attack, it remains at a higher level of attack scenarios. The process operator at the Natanz facility also experienced a “Loss of View”, a very specific one the loss of accurate process data for some very specific process loops. Cyber security attacks can be very granular, requiring more detail than consequences as “Loss of View” and “Loss of Control” offer, for spotting the weak link in the chain and fix it. If we look in detail how an operator HMI function works we soon end up with quite a number of scenarios. The path between the finger tips of an operator typing a new setpoint and the resulting change of the control valve position is a long one with several opportunities to exploit for a threat actor. But while threat modelling the design of the controller during its development many of these “opportunities” have been addressed.

The more complex the number of scenarios we need to analyze the less appropriate the execution of the HAZOP method in the traditional way is because of the time it takes and because of the dependence on subject matter experts. Even the best cyber security subject matter specialists can miss scenarios when it is complex, or don’t know about these scenarios because they don’t have the knowledge of the internal workings of the functions. But before looking at a different, computer supported method, first an introduction of “stage-zero-thinking”.


Stage-zero refers to the ICS kill chain I discussed in an earlier blog where I tried to challenge if an ICS kill chain always has two stages. A stage 1 where the threat actor collects the specific data he needs for preparing an attack on the site’s physical system, and a second stage where actual attack is executed. We have seen these stages in the Trisis / Triton attack , where the threat actors attacked the plant two years before the actual attempt collect information in order to attack a safety controller for modifying the SIS application logic.

What is missing in all descriptions of TRISIS attack so far is stage 0, the stage where the threat actor made his plans to cause a specific impact on the chemical plant. Though the “new” application logic created by the threat actors must be known (part of the malware), it is nowhere discussed what the differences were between the malicious application logic and the existing application logic. This is a missed opportunity because we can learn very much from understanding rational behind the attackers objective. Generally objectives can be reached over multiple paths, fixing the software in the Triconex safety controller might have blocked one path but it is far from certain if all paths leading to the objective are blocked.

For Stuxnet we know the objective thanks to the extensive analysis of Ralph Langner, the objective was manipulation of the centrifuge speed to cause excessive wear of the bearings. It is important to understand the failure mode (functional deviation) used because this helps us to detect it or prevent it. For the attack on the Ukraine power grid, the objective was clear … causing a power outage .. the functional deviation was partially unauthorized operation of the breaker switches and partially the corruption of protocol converter firmware to prevent the operator to remotely correct the action. This knowledge provides us with several options to improve the defense. Another attack, the attack on the German Steel mill the actual method used is not known. They gained access using a phishing attack but in what way the attacker caused the uncontrolled shutdown is never published. The objective is clear but the path to it not, so we are missing potential ways to prevent it in future. Just preventing unauthorized access is only blocking one path, it might still be possible to use malware to do the same. In risk analysis we call this the event path, the longer we oversee this event path the stronger our defense can be.

Attacks on cyber physical systems have a specific objective, some are very simple (like the ransomware objective) some are more complex to achieve like the Stuxnet objective or in power the Aurora objective. Stage-zero-thinking is understanding which functional deviations in the ICS are required to cause the intended loss on the physical side. The threat actor starts at the end of the attack and plans an event path in the reverse direction. For a proper defense the blue team, the defenders, needs to think like the red team. If they don’t they will always be reactive and often too late.

The first consideration of the Stuxnet threat actor team must have been how to impact the uranium enrichment plant to stop doing what ever they were doing. Since this was a nation state level attack there were of course kinetic options, but they selected the cyber option with all consequences for the threat landscape of today. Next they must have been studying the production process and puzzling how to sabotage it. In the end they decided that the centrifuges were an attractive target, time consuming to replace and effectively reducing the plant’s capacity. Than they must have considered the different ways to do this, and decided on making changes in the frequency converter to cause the speed variations responsible for the wear of the bearings. Starting at the frequency converter they must have worked their way back toward how to modify the PLC code, how to hide the resulting speed variations from the process operator, etc, etc. A chain of events on this long event path.

in the scenario I discussed in my Trisis blog I created the hypothetical damage through modifying a compressor shutdown function and subsequently initiating a shutdown causing a pressure surge that would damage the compressor. Others suggested the objective was a combined attack on the control function and process safety function. All possible scenarios, the answer is in the SIS program logic not revealed. So no lesson learned to improve our protection.

My point here is that when analyzing attacks on cyber physical systems we need to include the analysis of the “action” part. We need to try extending the functional deviation to the process equipment. For many process equipment we know the dangerous failure modes, but we should not reveal them if we can learn from them to improve the protection. This because OT cyber security is not limited to implementing countermeasures but includes considering safeguards. In IT security, there is a focus on the data part for example: the capturing of access credentials; credit card numbers; etc.

In OT security need to understand the action, the relevant failure modes. As explained in prior blogs, these actions are in the two categories I have mentioned several times: Loss of Required Performance (deviating from design or operations intent) and Loss of Ability to Perform (the function is not available). I know that many people like to hang on to the CIA or AIC triad, or want to extend, the key element in OT cyber security are these functional deviations that cause the process failures to address these on both the likelihood and impact factors we need to consider the function and than CIA or AIC is not very useful. The definitions used by the asset integrity discipline offer us far more.

Both loss of required performance and loss of ability to perform are equally important. Causing the failure modes linked to loss of required performance the threat actor can initiate the functional deviation that is required to impact the physical system, with failure modes associated with the loss of ability to perform the threat actor can prevent detection and / or correction of a functional deviation or deviation in the physical state of the production process.

The level of importance is linked to loss and both categories can cause this loss, it is not that Loss of Performance (kind of equivalent of the IT integrity term) or Loss of Ability to Perform (The IT availability term) cause different levels of loss. The level of loss depends on how the attacker uses these failure modes to cause the loss, a loss of ability can easily result in a runaway reaction without the need of manipulation of the process function, some production processes are intrinsically unstable.

All we can say is that loss of confidentiality is in general the least important loss if we consider sabotage, but can of course lead to enabling the other two if it concerns confidential access credentials or design information.

Let’s leave the stage-zero-thinking for a moment and discuss the use of the HAZOP / PHA technique for OT cyber security.


I mentioned it in previous blogs, a cyber attack scenario can be defined as:

A THREAT ACTOR initiates a THREAT ACTION exploiting a VULNERABILITY to achieve a certain CONSEQUENCE.

This we can call an event path, a sequence of actions to achieve a specific objective. A threat actor can chain event paths, for example in the initial event path he can conduct a phishing attack to capture login credentials, followed-up by an event path accessing the ICS and causing an uncontrolled shut down of a blast furnace. The scenario discussed in the blog on the German steel mill attack. I extend this concept in the following picture by adding controls detailing the consequence.

Event path

In order to walk the event path a threat actor has to overcome several hurdles, the protective controls used by the defense team to reduce the risk. There are countermeasures acting on the likelihood side (for instance firewalls, antivirus, application white listing, etc.) and we have safeguards / barriers acting on the consequence side to reduce consequence severity by blocking consequences to happen or detect them in time to respond.

In principal we can evaluate risk for event paths if we assign an initiating event frequency to the threat event, have a method to “measure” risk reduction, and have a value for consequence severity. The method to do this is equivalent to the method used in process safety Layer Of Protection Analysis (LOPA).

In LOPA the risk reduction is among others a factor of the probability of demand (PFD) factor we assign to each safeguard, there are tables that provide the values, the “credit” we take for implementing them. The multiplication of safeguard PFDs in the successive protection layers provides a risk reduction factor (RRF). If multiplied with the initiating event frequency we get the mitigated event frequency (MEF). We can have multiple layers of protection allowing us to reduce the risk. The inverse of the MEF is representative for the likelihood and we can use it for the calculation of residual risk. In OT cyber security the risk estimation method is similar, also here we can benefit from multiple protection layers. But maybe in a future blog more detail on how this is done and how detection comes into the picture to get a consistent and repeatable manner for deriving the likelihood factor.


To prevent questions, I probably already explained in a previous blog, but for risk we have multiple estimation methods. We can use risk to predict an event to happen, this is called temporal risk, we need statistical information to get a likelihood. We might get this one day if we have every day an attack on ICS, but today there is not enough statistical data for ICS cyber attacks to estimate temporal risk. So we need another approach, and this is what is called a risk priority number.

Risk priority numbers allow us to rank risk, we can’t predict but we can show which risk is more important than another and we can indicate which hazard is more likely to occur than another. This is done by creating a formula to estimate the likelihood of the event path to reach its destination, the consequence.

If we have sufficient independent variables to score for likelihood, we get a reliable difference in likelihood between different event paths.

So it is far from the very subjective assignment method of a likelihood factor by a subject matter expert as explained by a NIST risk specialist in a recent presentation organized by the ICSJWG. Such a method would lead to a very subjective result. But enough about estimating risk this is not the topic today, it is about the principles used.


Counterfactual hazard identification and risk analysis is the method we can use for assessing OT cyber security risk in a high level of detail. Based on John Cusimano’s reaction it looks like an unknown approach. Though the method is at least 10+ years in every proper book on risk analysis and in use. So what is it?

I explained the concept of the event path in the diagram, counterfactual risk analysis (CRA) is not much more than building a large repository with as many event paths as we can think of and then processing them in a specific way.

How do we get these event paths? One way is to study the activities of our “colleagues” working in threat_community inc. They potentially learn us in each attack they execute one or more new event paths. Another way to add event paths is by threat modelling, at least than we become proactive. Since cyber security also entered the development processes of ICS in a much more formal manner, many new products today are being threat modeled. We can benefit of those results. And finally we can threat model ourselves at system level, the various protocols (channels) in use, the network equipment, the computer platforms.

Does such a repository cover all threats, absolutely not but if we do this for a while with a large team of subject matter experts in many projects the repository of event paths grows very quickly. Learning curves become very steep in large expert communities.

How does CRA make use of such a repository? I made a simplified diagram to explain.

The Threat Actor (A) that wants to reach a certain consequence / objective (O), has 4 Threat Actions (TA) at his disposal. Based on A’s capabilities he can execute one or more. Maybe a threat actor with IEC 62443 SL 2 capabilities can only execute 1 threat action, while an SL 3 has the capabilities to execute all threat actions. The threat action attempts to exploit a Vulnerability (V), however sometimes the vulnerability is protected with a countermeasure(s) (C). On the event path the threat actor needs to overcome multiple countermeasures if we have defense in depth, and he needs to overcome safeguards. Based on which countermeasures and safeguards are in place event paths are yes or no available to reach the objective, for example a functional deviation / failure mode. We can assign a severity level to these failure modes (HIGH, MEDIUM, etc)

In a risk assessment the countermeasures are always considered perfect, there reliability, effectiveness and detection efficiency is included in their PFD. In a threat risk assessment, where also a vulnerability assessment is executed, it becomes possible to account for countermeasure flaws. The risk reduction factor for a firewall that starts with the rule permit any any will certainly not score high on risk reduction.

I think it is clear that if we have an ICS with many different functions (so different functional deviations / consequences, looking at the detailed functionality), different assets executing these functions, many different protocols with their vulnerabilities, operating systems with their vulnerabilities, and different threat actors with different capabilities, the number of event paths grows quickly.

To process this information a CRA hazard analysis tool is required. A tool that creates a risk model for the functions and their event paths in the target ICS. A tool takes the countermeasures and safeguards implemented in the ICS into account, a tool that accounts for the static and dynamic exposure of vulnerabilities, and a tool that accounts for the severity of the consequences. If we combine this with the risk criteria defining the risk appetite / risk tolerance we can estimate risk and can quickly show which hazards have an acceptable risk, tolerable risk, or unacceptable risk.

So a CRA tool builds the risk model through configuring the site specific factors, for the attacks it relies on the repository of event paths. Based on the site specific factors some event paths are impossible, others might be possible with various degrees of risk. More over such a CRA tool makes it possible to show additional risk reduction by enabling more countermeasures. Various risk groupings become possible, for example it becomes possible to estimate risk for the whole ICS if we take the difference in criticality between the functions into account. We might want to group malware related risk by filtering on threat actions based on malware attacks or other combinations of threat actions.

Such a tool can differentiate risk for each threat actor with a defined set of TTP. So it becomes possible to compare SL 2 threat actor risk with SL 3 threat actor risk. Once we have a CRA model many points of view become available, could even see risk vary for the same configuration if the repository grows.

So there is a choice, either a csHAZOP process with a workshop where the subject matter experts discuss the various threats. Or using a CRA approach where the workshop is used to conduct a criticality assessment, consequence analysis, and determine the risk criteria. It is my opinion that the CRA approach offers more value.


So finally what has this all to do with the title “playing chess on the ICS board”? Well apart from a OT security professional I was also a chess player, playing chess in times there was no computer capable of playing a good game.

The Dutch former world champion Max Euwe (also professor Informatics) was of the opinion that computers can’t play chess at a level to beat the strongest human chess players. He thought human ingenuity can’t be put in a machine, this is about 50 years ago.

However large sums of money were invested in developing game theory and programs to show that computers computers can beat humans. The first time that this happened was when an IBM computer program “Deep Blue” won from then reigning world champion Gary Kasparov in 1997. The computers approached the problem brute force in those days, generating for each position all the possible moves, analyzing the position after the move and going to the next level for a new move for the move or moves that scored best. Computers could do this so efficiently that looked 20/30 moves (plies) ahead, far more than any human could do. Humans had to use their better understanding of the position and its weaknesses and defensive capabilities.

But the deeper a computer could look and the better its assessment of the position became the stronger it became. And twenty years ago it was quite normal that machines could beat humans at chess, including the strongest players. This was the time that chess games could not be adjourned anymore because a computer could analyse the position. Computers were used by all top players to check their analysis in the preparation of games, it considerably changed the way chess was played.

Than recently we had the next generation based on AI (E.g. Alpha Zero) and again the AI machines proofed stronger, stronger then the machines making use of the brute force method. But these AI machines offered more, the additional step was that humans started to learn from the machine. The loss was no longer caused by our brains not being able to analyze so many variations, but the computer actually understood the position better. Based upon all the games played by people the computers recognized patterns that were successful and patterns that would ultimately lead to failure. Plans that were considered very dubious by humans were suddenly shown to be very good. So grandmasters learned and adopted this new knowledge even by today’s world champion Magnus Carlsen.

So contrary John’s claim if we are able to model the problem we create a path where computers can conquer complex problems and ultimately be better than us.

CRA is not brute force – randomly generating threat paths – but processing the combined knowledge of OT security specialists with detailed knowledge of the inner workings of the ICS functions contained in a repository. Kind of the patterns recognized by the AI computer.

CRA is not making chess moves on a chess board, but verifying if an event path to a consequence (Functional deviation / failure mode) is available. An event path is a kind of move, it is a plan to a profitable consequence.

Today CRA uses a repository made and maintained by humans, but I don’t exclude it that tomorrow AI assisting us to consider which threats might work and which not. Maybe science fiction, but I saw it happen with chess, Go, and many other games. Once you model a problem computers have proofed to be great assistants and even proofed to be better than humans. CRA exists today, an AI based CRA may exist tomorrow.


So in my opinion the HAZOP method in the form applied to process safety and in computer HAZOPs leads to a generalization of the threats when applied for cyber security because of the complexity of the analysis. Generalization leads to results comparable with security standard-based or security-compliance-based strategies. For some problems we just don’t need risk, if I cross a street I don’t have to estimate the risk. Crossing in a straight line – shortest path – will reduce the risk. The risk would be mainly how busy the road is.

For achieving the benefits of a risk based approach in OT cyber security we need tooling to process all the hazards (event paths) identified by threat modelling. The more event paths we have in our brain, the repository, the more value the analysis produces. Counter fact risk analysis is the perfect solution for achieving this, it provides a consistent detailed result allowing for looking at risk from many different viewpoints. So computer applications offer significant value, by offering a more in depth analysis, for risk analysis if we apply the right risk methodology.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site

A wake-up call


Process safety practices and formal safety management systems have been in place in the industry for many years. Process safety management has been widely credited for reductions in the number of major accidents, proactively saving hundreds of lives and improving industry performance.

OT cyber security, the cyber security of process automation systems such as used by the industry, has a lot in common with the management of process safety and we can learn very much from the experience of formal safety management, build over more than 60 years. Last week I saw a lengthy email chain on a question “if the ISA 99 workgroup (the developers of the IEC 62443 standard) should look for a closer cooperation with the ISO 27001 developers to better align the standards”. Of course such a question results in discussions addressing the importance of ISO 27001 and others emphasizing the difficulties to apply the standard in the industry.

If there is a need for ISA to cooperate with another organization for aligning its standard, than in my opinion they should have a more close cooperation with the AIChE, the ISA of the chemical engineering professionals. The reason for this is that there is a lot to learn from process safety and though IEC 62443 is supposed to be a standard for industrial control systems, there is still a lot of “IT methodology” in the standard.

In this week’s blog I like to address the link between process safety and cyber security again, and discuss some of the lessons in process safety we can (actually should in my opinion) learn from. Not for adding safety to the security triad as some suggest, this is in my opinion for multiple reasons wrong, but because process safety management and OT cyber security management have many things in common when we compare their design and management processes and process safety management is much further in its development than OT cyber security management.

I accomplished in my career several cyber security certifications such as: CISSP, CISM, CRISC, ISO 27001 LA and many more with a pure technical focus. Did all this course material ever discuss industrial control systems (ICS)? No they didn’t, still they where very valuable for developing my knowledge. As an employee working for a major vendor of ICS solutions, my task became more to adopt what was applicable, learn from IT and park those other bits of knowledge for which I saw no immediate application. As my insights further developed I started to combine bits and pieces from other disciplines more easily. In the OT cyber security world, which is relatively immature, we can learn a lot from more mature disciplines such as process safety management. Such learning generally requires us to make adaptions to address the differences.

But despite these differences we can learn from studying the accomplishments of the process safety discipline, this will certainly steepen the learning curve of OT cyber security to make it more mature. If we want to learn from process safety, where better to start than the many publications of CCPS (Center for Chemical Process Safety) and the AIChE.


Process safety starts at risk, process safety studies the problem first before they attempt to solve the problem. Process safety recognizes that all hazards and risk are not equal, consequently it focuses more resources on higher hazards and risks. Does this also apply to cyber security, in my opinion very sparingly.

More mature asset owners in the industry adopted a risk approach in their security strategy, but the majority of asset owners is still very solution driven. They decide on purchasing solutions before they inventoried the cyber security hazards and prioritized them.

What are the advantages of a risk based approach? Risk allows for optimally apportioning limited resources to improve security performance. Risk also provides a better insight in where the problems are and what options there are to solve a problem. Both OT cyber security risk and process safety risk are founded on four pillars:

  • Commit to cyber security and process safety – A workforce that is convinced that their management fully supports a discipline as part of its core values will tend to follow process even when no one else is checking this.
  • Understand hazards and risk – This is the foundation of a risk based approach, it provides the required insight to make justifiable decisions and apply limited resources in an effective way. This fully applies for both OT cyber security and process safety.
  • Manage risk – Plants must operate and maintain the processes that pose risk, keep changes to those processes within the established risk tolerances, and prepare for / respond to / manage incidents that do occur. Nothing in here that doesn’t apply for process safety as well as OT cyber security.
  • Learn from experience – If we want to improve, and because of the constantly changing threat landscape we need to improve, we need to learn. Learning we do by observing and challenging what we do. Metrics can help us here, preferably metrics that provide us with leading indicators so we see the problem coming. Also this pillar applies for both disciplines, where process safety tracks near misses OT cyber security can track parameters such as AV engines detecting malware, or firewall rules bouncing off traffic attempting to enter the control network.

Applying these four pillars for OT cyber security would in my opinion significantly improve OT cyber security over time. Based upon what I see in the field, I estimate that less than 10 percent of the asset owners adopted a risk based methodology for cyber security, while more than 50 percent adopted a risk based methodology for process safety or asset integrity.

If OT cyber security doesn’t want to learn from process safety, it will take another 15 years to reach the same level of maturity. If this happens we are bound to see many serious accidents in future, including accidents with casualties. OT cyber security is about process automation lets use the knowledge other process disciplines build over time.


The alternative for a risk based approach is a compliance based approach, well known examples are for North America the NERC CIP standard, and for Europe the French ANSSI standard for cyber security or if we look at process safety the OSHA regulations in the US. All compliance driven initiatives. A compliance driven approach can lead to:

  • Decisions based upon ” If it isn’t a regulatory requirement, we are not going to do it”.
  • The wrong assumption that stopping the more frequent and easier to measure incidents (like for example the mentioned malware detection) discussed in standards will also stop the low-frequency / high consequence incidents.
  • Inconsistent interpretation and application of the practices described in the standard. Standards are often a compromise between conflicting opinions, resulting in soft requirements open for different interpretations.
  • Overemphasized focus on the management system, forgetting about the technical aspects of the underlying problems.
  • Poor communication between the technically driven staff and the business driven senior management, resulting in management not understanding the importance of the messages they receive and subsequently fail to act.
  • High auditing costs, where audits focus on symptoms instead of underlying causes.
  • Not moving with the flow of time. Technology is continuously changing, posing new risk to address. Risk that is not identified by a standard developed even as recent as 5 years ago.

This criticism on a compliance approach doesn’t mean I am against standards and their development. Merely I am against standards as an excuse to switch off our brain, close our eyes and ignore where we differ from the average. Risk based processes offer us the foundation to stay aware of all changes in our environment while still using standards as a checklist to make certain we don’t forget the obvious.

The four available strategies

Like I mentioned for cyber security the majority of the asset owners would fall in the category standards-based or compliance-based. It is a step forward compared to 10 years ago, when OT cyber security was ignored by many, but it is a long way off from where asset owners are for process safety.

Where we see in process safety the number of accidents decline, we see in cyber security that both the threat event frequency and the threat capability of the threat community rise. To keep up with the growing threat, critical infrastructure should adopt a risk based strategy to keep track with the threat community. Unfortunately many governments are driving for a compliance based strategy because they can more easily audit this and doing this they are setting the requirements too low for a proper protection against the growing threat.

A risk based approach doesn’t exclude compliance with a standard, it just makes the extra step predicting the performance of the various cyber security aspects, independent of any loss events, and improving its security. As such it adds pro-activity to the defense and allows us to keep track with the threat community.

The process safety community recognized the bottlenecks of a compliance based strategy and jumped forward by introducing a risk based approach allowing them to further reduce the number of process safety accidents after several serious accidents happened in the 1980s. Accidents caused by failure of the compliance based management systems.

Because of the malicious aspects inherent to cyber security, because of the fast growing threat capabilities of the threat community and because of an increase in threat events, not jumping to a risk based strategy like the process safety community did is waiting for the first casualties to occur as a result of a cyber attack. TRISIS had the potention be the first attack causing loss of life, we were lucky it failed. But the threat actors have undoubtedly learned from their failure and work on an improved version.

I don’t include the alleged attack on a Siberian pipeline in 1982 as a cyber event as some do. If such an event would happen due to a cyber attack this would be an act of war. So for me we have been lucky so far that cyber impact was mainly a monetary value, but this can change either willingly or accidentally.


It would become a very lengthy blog if I would discuss each of the twenty elements of the risk based safety program or reliability program. But each of these elements has a strong resemblance with what would be appropriate for a cyber security program.

The element I like to jump to is the Hazard Identification and Risk Analysis (HIRA) element. HIRA is the term used to bundle all activities involved in identifying hazards and evaluating the risk induced by these hazards. In my previous blog on risk I showed a more detailed diagram for risk, splitting it in three different forms of risk. For this blog I like to focus on the the hazard part using the following simplified diagram for the same three forms of risk.

Simplified risk model

On the left side we have the consequence of the cyber security attack, some functional deviation of the automation system. This is what was what was categorized as loss of required performance and loss of ability to perform. The 3rd category, loss of confidentiality, will not lead directly to a process risk so I ignore it here. Loss of required performance caused the automation system to either execute an action that should not have been possible (not meeting design intent) or an action that does not perform as it should (not meeting operation intent). In the case of loss of ability to perform, the automation system could not execute one or more of its functions.

So perhaps the automation system’s configuration was changed in a way that the logical dimensions configured in the automation system no longer represent the physical dimensions of the equipment in the field. For example if the threat actor increases the level range of a tank this does not result into a bigger physical tank volume, so a possibility exists that the tank is overfilled without the operator noticing this in his process displays. The logical representation of the physical system (its operating window) should fit the physical dimensions of the process equipment in the plant. If this is not the case this would be the failure mode “Integrity Operating Window (IOW) deviation” in the “Loss of Required Performance” category.

Similar the threat actor might prevent the operator to stop or start a digital output, the failure mode “Loss of Controllability” in the category “Loss of Ability to Perform”. Not being able to stop or start a digital output might translate to the inability to stop or start a pump in the process system. At least stopping or starting by using the automation system. We might have implemented an electrical switch (safeguard) to do it manually if the automation system would fail.

Not being able to modify a control parameter would give rise to a whole other category of issues for the production process. Each failure mode has a different consequence for the process system equipment and the production process.

Cyber security hazards are a description of a threat actor (threat community) executing a threat event (threat action exploiting a vulnerability) resulting in a specific consequence (the functional deviation) entering a specific failure mode for the automation system function. What the consequence is for the production process and its equipment depends on the automation system function affected and the characteristics of the production system equipment and production process. This area is investigated by the process (safety) hazards. Safety is here between brackets because not every functional deviation results in a consequence for process safety, there can also be consequences for product quality or production loss not impacting process safety at all. If the affected function would be the safety instrumented system (SIS), a deviation in functionality would always affect process safety.

The HIRA for process risk would focus on how the functional deviations influence the production process and the asset integrity of its equipment. As such the HIRA has a wider scope than it would have in a typical process safety hazard analysis / hazop. For cyber security it combines what we call the computer hazop, the analysis of how failures in the automation system impact the production system and the process safety hazop.

On the other hand from a safeguard perspective of the safety hazop / PHA the scope is smaller because we can only influence the functionality of the “functional safety” functions provided by the SIS. Safety has multiple layers of protection and multiple safeguards and barriers that contain a dangerous situation. A cyber security attack can only impact the programmable electronic components (e.g. SIS) of the process safety protection functions.

This is the reason why I protest if people talk about “loss of safety” in the context of cyber security, there are in general more protection mechanism implemented, so safety is not necessarily lost. Adding safety to the triad is also incorrect in my opinion, this should be at minimum adding functional safety because that is the only safety layer that can be impacted by a cyber threat event, but functional safety is also already covered within the definition of loss of required performance.

IEC 62443’s loss of system integrity is not covering all the failure modes covered by loss of required performance. The IEC 62443-1-1 defines integrity as: “Quality of a system reflecting the logical correctness and reliability of the operating system, the logical completeness of the hardware and software implementing the protection mechanisms, and the consistency of the data structures and occurrence of the stored data.”

This definition is fully ignoring the functional aspects in an automation system, therefore it is a too limited cyber security objective for an automation system. For example where do we find in the definition that an automation action needs to be performed on the right moment in the right sequence and appropriately coordinated with other functions.

Consider for example the coordination / collaboration between a conveyor and filling mechanism or a robot. The IEC 62443 seven foundation requirements don’t cover all aspects of an automation function / industrial control system. The combined definitions used by risk based asset integrity management and risk based process safety management do cover these aspects, an example of a missed chance to learn something from an industry that has considerably more experience in its domain than the OT cyber security community has in its own field.


Can we conduct the HIRA process for cyber security in a similar way as we do for process safety? My only answer here is a firm NO!. The malicious aspects of cyber security make it impossible to work in the same way as we do for process safety. The job would just not be repeatable (so results are not consistent) and too big (so extremely time consuming). The number of possible threat events, vulnerabilities, and consequences is just too big to approach this in a workshop setting as we do for process hazard analysis (PHA) / safety hazop.

So in cyber security we work with tooling to capture all the possibilities, we categorize consequences and failure modes to assign them a trustworthy severity value meeting the risk criteria of the plant. But in the end, we end with a risk priority number just like we have in risk based process safety or risk based asset integrity to rank the hazards.

The formula for cyber security risk is more complex because we not only have to account for occurrence (threat x vulnerability) and consequence, but also for detection, and the risk reduction provided by countermeasures, safeguards and barriers. But these are normal deviations, also risk based asset integrity management and risk based process safety management differ at detail level.


The following key principles need to be addressed when we develop, evaluate, or improve any management system for risk:

  • Maintain a dependable and consistent practice – So the practice should be documented, the objectives of the benefits must be in terms that demonstrate to management and employees the value of the activities;
  • Identify hazards and evaluate risks – Integrate HIRA activities into the life cycle of the ICS. Both design and security operations should be driven by risk based decisions;
  • Assess risks and make risk based decisions – Clearly define the analytical scope of HIRAs and assure adequate coverage. A risk system should address all the types of cyber security risk that management wants to control;
  • Define the risk criteria and make risk actionable – It is crucial that all understand what a HIGH risk means, and that it is defined what the organization will do when something attains this level of risk. Risk appetite differs depending on the production process or process units within that process;
  • Follow through on risk assessment results – Involve competent personnel, make a consistent risk judgement so we can follow through without too much debate if results require this;

Risk diagrams to express process risk generally have less risk levels as a risk assessment diagram for cyber security. This because it has a more direct relationship with the business / mission risk, so actions have a direct business justification. An example risk assessment diagram for process risk is shown in the following diagram:

Risk assessment diagram for process risk example

The ALARP acronym stands for As Low As Reasonably Practicable a commonly used criterion for process related risk. Once we have the cyber security hazards and their process consequence we can assign a business impact to each hazard and create risk assessment matrices for each impact category as explained in my blog on OT cyber security risk using the impact diagram as example. or if preferred the different impact categories can be shown in a single risk assessment matrix.

Mission impact example

So far this discussion about the parallels between risk based process safety, risk based asset integrity, and risk based OT cyber security. I noticed in responses to previous blogs, that for many this is an uncharted terrain because they might not be familiar with all three disciplines and the terminology used. Most risk methods used for cyber security have an IT origin. This results in ignoring the action part of an OT system, OT being Data + Action driven where IT is Data driven only. Another reason to more closely look at other risk based management processes applied in a plant.


There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 42 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them.


Author: Sinclair Koelemij

OTcybersecurity web site