I have been interested in Security Analytics for some time now. I wanted to pen a piece about the economics of, and business case for Security Analytics.


Achieving a robust security posture is complex and requires many elements operating together and in an optimal manner to successfully lower the risk to reasonable levels. It is very difficult for C-Suite to quantify the value of security investments. I have said on previous occasions that there is a huge opportunity to better quantify the value of the holistic and individual elements of security solutions.


As an example. Properly deployed Segmentation is a powerful security architecture foundation. However, it can be very expensive, logistically complex and slow to insert into an operational network. It then requires continuous focus to keep rule sets current and effective. To try to quantify its value is hard. It is reasonable to summarise it as being highly effective, but comes with a high cost and a slow deployment time.


Onto the topic of Security Analytics. For the last 20 years I have been vocal about the need for Security Visibility. If you don’t have some form of visibility into security events occurring in your organisation, you have basically failed from the start. When recent major  breaches have occurred, post mortems regularly find that the perpetrators were inside the network for extended periods without discovery. 


To highlight the crying need for quality Security Analytics, look no further than the recent Solar Winds incident. Solar Winds was widely deployed on a global basis and in many environments handling both high-value and highly sensitive information. While the Sunburst malware used was reasonably sophisticated, it did utilise a heartbeat to communicate to an external Command-and-Control server. How many organisations detected this? None that I have found! In my opinion, this is dreadful indictment on the effectiveness of the Security operations landscape. 


There are many different ways to achieve Security Visibility including several highly effective open-source tools. If you have no, or little budget, these can provide a good starting point and are certainly way better than nothing. However, these only go so far. They do require expertise and often a reasonable time investment. While the tool may be free, the time investment and expertise isn’t. Also, they generally perform poorly against sophisticated malware.


I have previously spoken about Zero Trust. One of the foundational concepts of Zero Trust is understanding key information assets. In any business case for security, it is important to understand the financial and/or business impact if those resources were compromised through an event such as ransomware or extortion threatening public disclosure. The impact for many affected organisation has been severe to catastrophic.


I am aware of numerous situations where boards and senior management would not adequately fund proactive security measures, but were later happy to pay out potentially millions of dollars to ransomware organisations in an attempt to retrieve their data with an at-best probably of 50%. In many cases it was simply impossible to recover. Or key files, usually the large and critical ones like databases, were rendered corrupt.


The most key business benefit of a Top-Tier Security Analytics system is its Time-to-Value. These systems can usually be deployed quickly with a modest investment (emphasis added)!


At a technical level the deployment can be as simple as providing port mirrors at strategic points-in-the-network, potentially the Internet Perimeter and/or the Data Centre Perimeter, possibly others. Result - a sophisticated level of visibility can be quickly obtained. This places the organisation in a dramatically better position to react and is a component of Zero Trust Architectures.


It can’t be stressed strongly enough that should your organisation be hit with a Ransomware attack, and you need to enact an Incident Response, it is too late at that point to be looking to deploy tooling. Put bluntly, if this is not in place ahead of time, you’re screwed! 


Ransomware attacks have become far more efficient. In that past, miscreants may have been in the network for months. Today, ransomware attacks are often completed start to finish in less than 24 hours. It is a well-oiled industry now. The point being that tooling which allows rapid and accurate detection is now critical. You must be able to quickly and accurately detect the threat and its propagation vector to stop it.


Some other benefits of Analytics;


  • Can help to Identify assets, including shadow IT. Gaps or inaccuracies in asset inventories are a big issue.
  • Provide an ability to identify and accurately quantify many security risks. This allows more robust business cases for security investment.
  • Furthermore, it can provide a foundation for a Security Metric driven approach.
  • Provides early warning. 
  • Provides an Incident Response tool which can be quickly leveraged to identify the attack, its type, sources, affected devices, trajectories, etc. 
  • Sophisticated Analytics make it easier for your staff. It is a well-recognised problem that quality security staff are both hard to find and overloaded. Making these staff more effective through analytics tooling, should be a no brainer. 


While several years ago the analytics scene was full of over-statement and marketing dribble in relation to the use of machine learning techniques. Today, the top-tier platforms are genuinely leveraging ML in meaningful and impactful ways. 


In summary, I believe the Top-Tier Security Analytics platforms punch well above their weight in terms of value. I believe they are hugely under adopted and would encourage organisation to look into this technology space further.







To everyone who attended my presentation on Friday 26 March 2021 at the Hilton Brisbane, thank you for the opportunity.

The presentation material can be downloaded from Deciphering Zero Trust .

Deciphering the Zero Trust Architecture - Video 1 – An Overview 

This video provides an overview of the Zero Trust Architecture. What is it about? What problems does it address? Why may it a be beneficial to my organisation? 



Deciphering the Zero Trust - Architecture - Video 2 – Architectures  

In a first video I attempted to decipher the Zero trust Architecture - what it was about and the benefits it provided. This second video in the series moves onto a deeper coverage of the potential architectural approaches.


I have always thought of Zero Trust (ZT) as a nonsensical term as it is simply not possible to operate any IT infrastructure without some level of trust. It is interesting to note that Gartner have also recently referred to Zero Trust as ‘misnamed’ and have developed their own framework – CARTA, which stands for Continuous Adaptive Risk and Trust Assessment. The fact that Gartner have taken this position endorses the fact that Zero Trust in principal, can bring very real benefits.

The intention of this post is to explain what Zero Trust means, the benefits it can provide, while also highlighting some of the practical considerations for those looking to implement a Zero Trust initiative. 

The term Zero Trust has very much become a buzzword even though many in the security industry struggle to articulate what it actually means. Zero Trust was initially conceived by John Kindervag during his time as Forrester Research (note that he is now at Palo Alto Networks continuing to promote it there).  While a number of perspectives of Zero Trust exist including many vendor marketing spins, fundamentally its about ensuring that trust relationships aren’t exploited. It is not about making an untrusted or high-risk environment trusted, or achieving a trusted state, some common misconceptions I hear. It’s about avoiding trust as a failure point.

Kindervag has argued that the root cause of virtually all intrusions is some violation of a trust relationship. This can mean; 

  • A miscreant gaining access to an openly accessible system through no or insufficient network segmentation 
  • A legitimate user exceeding their intended authority, i.e. privilege or access abuse 
  • A compromised system jumping from one system to another, i.e. east-west attack propagation
  • Compromised account credentials being used to easily facilitate the above scenarios. 

Hence Zero Trust proposed a framework which assumes of no level of trust in the design process. There is certainly good logic in that fundamental assumption, although it will come at a cost. 

In practice, implementing Zero Trust or CARTA requires very tight filtering and deep inspection of traffic flows coupled with a strong user identity function. Much of the deployment of Zero Trust is based on Network Segmentation and utilising network security technology such as Next Generation Firewalls to deeply inspect and enforce traffic flows crossing trust boundaries. Additionally, establishing a trusted Identity for both users and administrators through techniques such as Multi-Factor Authentication (MFA) is also a vital element.

Its here where the practical considerations start. I have seen many organisations struggling with their existing, usually dated segmentation models and tightly associated firewall rule bases. In the majority of cases this infrastructure has been in place for well over a decade (or longer) and has been expanded as the application infrastructure has grown organically (usually through several generations of administrators). Being polite, most have not grown well. In many cases, these messes are both complex and costly to operate often sucking valuable funds from stretched security budgets. In most cases they are no longer an effective solution, often only there to provide a false sense of security or a compliance tick-box.

Today most corporate IT infrastructures are large, support multiple business critical applications with have highly complex transaction flows and dependencies. Understanding this type of environment is a non-trivial task. Let alone re-engineering such an environment against near continuous uptime requirements.

So, what can be achieved? How can organisations proceed?

I’d suggest the place to begin is by identifying the organisations Ten (or so) most valuable information assets, or alternatively a set of potential candidates. Start small and don’t get too ambitious too quickly. Then monitor the traffic flows to those applications and understand them. A number of technologies and/or techniques can be used including an application-aware Next-Generation Firewall located in front of the candidate systems or applications. Monitoring tools including those which ingest Netfow can also be highly effective. I would strongly recommend whatever solution is used it should also be integrated with the organisations Identity system, be that Active Directory or other systems such as Cisco’s Identity Service Engine (ISE). Linking identity into the monitoring provides not just application visibility, but ‘context’ of ‘who’ is accessing the application. For example, why is a Building Management System accessing the Finance System?

Based on what is discovered, and assuming it isn’t to onerous (which may be a big assumption), then the applications can be located within their own security zone such as a Secure Enclave and tight application-level, Identity-Aware filtering constructed, both in and out. This is the heart of Zero Trust. The objective is to not just control what gets in, but also to ensure that data exfiltration from the key assets can’t occur. For example, how often do we hear of Credit Card Databases being easily FTP’ed out of an organisation? ZT typically recommends additional inspections such as IPS, Network AV and Day-Zero Malware interception are deployed at trust boundaries.

So far so good..

If you are fortunate enough to have only a small number of key assets to protect, then you can rinse and repeat this approach (which for the purpose of this post is fairly oversimplified). Tightly protecting your organisations crown jewels is a valuable initiative, if this can be achieved, you’re in a far better position.

However, most environments I see are not this fortunate and its here where things start to get a whole lot harder. 

Firstly, if you are embarking on a larger scale ZT initiative, then it is essential to invest in an Analytics solution which can provide visibility into the traffic flows between all systems/applications/workloads on scale. Maybe some ultra-well organised organisations have achieved this on a spreadsheet, but these are very few in my experience. Of those that have, it requires significant human resource, is always error prone and changes frequently.

OK, so above I recommended identifying and placing critical applications into security zones with tight filtering at trust boundaries. For larger and more complex environments, it’s the same fundamental principal – (1) Expanding it and (2) on-scale being the big differences. It’s here that the tooling becomes essential to identify application dependencies and subsequently create an optimal zone structure. In my experience this is a key area of any ZT design as the complexity of the trust boundary filtering will be dependent on the quality of the zone structure. You want to get this part right. 

A key design complexity is that just because two systems are talking to each other does not mean that the conversation is always benign. Techniques such as ‘Living off the Land’ attacks are designed to mimic legitimate conversations. You can’t just blindly build a set of access-controls on this basis. Human sanity checking is needed. It is this exact problem which has made it so hard for Machine Learning algorithms to identify nefarious activity – in a mass of good what do the small amount of bad conversation look like?

Anyhow, this post has grown larger than I intended. I would like to discuss the use of ML algorithms in solving the Optimal Zoning and Scale issues I noted above. I’ll leave that for a Part Two.


In the last week we have seen a spectacular report out of Bloomberg in relation to malicious hardware implants within Supermicro server motherboards. The implications of this report are potentially huge. However, the technical details disclosed are minimal and a large number of unanswered questions exist.

Personally, I subscribe to the adage of “where there’s smoke, there must be at least some amount of fire”. Subsequent reports have claimed that it was not just Supermicro motherboards affected, but that the problem could be far more widespread affecting other vendors as well. With all that said, I acknowledge that this whole situation has not been substantiated and there is a chance it could be inaccurate, grossly exaggerated, or completely false. However, for the purpose of this post let’s put that debate aside and assume that the reports are correct.

The first point I would like to make is that hardware inspection is a highly specialised field and there are currently very few vendor organisations either experienced or equipped to perform this work. This means that for the vast majority of organisations, hardware inspection is not going to be a viable option.

So, I want to discuss options for network monitoring and visibility. But first the problem.

From the information available to date, it has been suggested that the malicious modifications have been made to the management controller of server motherboards, Cisco calls this an IMC (Intelligent Management Controller), Dell call it a DRAC (Dell Remote Access Controller) and HPE calls this ILO (Integrated Lights Out). All of these devices are essentially a small computer that controls the computer. There is a long history of these devices being notoriously insecure. Furthermore, these management controllers have access to just about every aspect of the server’s hardware providing them more control over the hardware than the operating system itself.

Compromised hardware only takes the attacker so far. At some point the malicious hardware will need to communicate over the network to a Command and Control (C&C) server. Depending on the nature of the implant, malicious communication attempts could originate from either compromised management controller interface, from the server’s operating system, hosted virtual machines or any/all of the above.

In my mind this situation further makes a compelling case for the deployment of network monitoring and analytics. The key issue now is the ability to detect malicious traffic and respond quickly in the event of such an occurrence, whether that attack has stemmed from either a hardware implant, or through unrelated but still malicious activities.

What are my recommendations and the options.

A critical point is that server management controller interfaces should not be routable to the internet. I recommend that they are segmented and are only allowed to communicate with the minimum number of workstations needed to support the operation of those devices. i.e. how many people really need access to the management controller? If you can isolate the kill chain at this point, it is highly likely an attacker won’t be able to gain control and further progress an attack. If server management ports must connect to something on the big bad internet, then enable it very selectively. 

At a network level, I would recommend the deployment of a Sinkhole on the management network. A sinkhole is a part of the network that attracts all traffic which has no other legitimate destination. Sinkholes are an infrequently deployed but incredibly useful for attracting all sorts of traffic which could either be the result of misconfiguration, or, of key interest here, malicious traffic. Once traffic is routed into a sinkhole there are many tools which can be used for analysis. I realise that’s a bit light on in technical detail, but I will aim to publish a subsequent Blog post on Sinkholes in the next week or so.

Let’s now talk about available network based monitoring options. 

When we start talking about monitoring options, the first call out is firewall logs. Assuming the management network is segmented, then whatever firewall is in place will be capable of connection logging. There are many examples where detailed evidence of an attack has been collected in the firewall logs. If you aren’t collecting and archiving your firewall logs, then this is recommendation one. And if you think I’m ‘stating the bleeding obvious’ – you would not believe the number of organisation who fall into the category of ‘people who should know better’, who don’t do this. If this is your organisation and it gets compromised, any forensic investigation will be both exponentially harder and exponentially more expensive! Ignore this advice at your peril.

Netflow - I have been a huge fan of Netflow as a security tool for many years. Netflow is the networking equivalent of a telephony Call Detail Record (CDR). At an IP level it records who spoke to who, how much, and for how long. Like firewall logs, flow records can be exported, collected, analysed and archived. A ley point is that for security applications, you must use full-flow Netflow to capture all conversations at a point-in-the-network as opposed to sampled Netflow.

Analysis tools – Many both commercial and open source tools are available which can be used for both log and Netflow analysis. I won’t call out any commercial options or discuss SIEMs, but the Elasticstack (formerly the ELK) is a very robust and widely deployed open source option. If you have nothing, Elasticstack is a good place to start.

Full Packet Capture – This approach captures all traffic that passes some through some point-in-the-network. I’m not going to elaborate on it too much as it’s a costly approach and generally reserved for serious organisations. However, I will mention one approach I have seen some organisations deploy. It is the use of a full packet capture card that collects in the order of a day to a weeks data in a circular buffer. In the event of an incident being detected the available full packet capture can be copied and stored for investigation. 

What are we looking for?

If we use a Cyber Kill Chain as a foundation, then we wish to look for any evidence of those attack stages within an attack lifecycle. This can range from beacons to a C&C server, download of additional malware or most importantly achievement of the ultimate objective, exfiltration of data (at which point you’re probably pretty screwed). And we must also assume that any potential attack traffic is going to be encrypted. That is another more in-depth topic, but lets just say it makes monitoring the contents of a traffic stream very difficult. 

Geo-Location – Is a widely available feature. It can provide a very quick indication of the termination country of a connection’s remote endpoint. So, if you were to see a connection from inside your network, connecting to a suspicious country, that’s something that requires investigation.

Threat Intelligence – The sheer number of active threats in general including malicious destinations on the Internet is well beyond the vast majority of organisations to track. This is where the use of Threat Intelligence comes in. If anything inside your organisation (and that includes Cloud Infrastructure) speaks to a known malicious internet endpoint, then you want to know about it. Threat Intelligence comes in a variety of forms, including both Open-Source and commercial feeds. The key objective is to correlate the information received from a reputable feed (or feeds) with the traffic ingressing and egressing your network. The goal of Threat Intelligence usage is to quickly identify a malicious event within what will typically be a mountain of network traffic. 

Threat Intelligence works on the assumption that someone has seen an attack previously. So if this is a unique or first time attack, it probably won’t help, but there will be a lot of cases that have been seen before making it a valuable tool.

As the primary focus of this post is compromised server hardware, then monitoring the communication habits of management controller ports should be a key focus. If these devices start trying to talk to unexplained destinations (including trying to resolve unexplained destinations), then prompt investigation is required.