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March 25, 2021

SANS ICS Security Summit 2021 recap: Industry on the move

This blog provides a concise overview of the key points from SANS Summit 2021. Knowing ‘self’ both defends against the growing tide of external threats and allows organizations to gain visibility into new vulnerable areas as ICS evolves.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
David Masson
VP, Field CISO
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25
Mar 2021

Shining a light into the murky world of industrial cyber security — where major incidents can be kept hush, and information is often not made publicly available — the SANS Institute held its 16th annual ICS Security Summit in March. With virtual events across APAC, EMEA, and the US, the round-the-clock summit stressed the importance of having good visibility and a strong understanding of industrial networks for anomaly detection and incident response. Speakers at the event also emphasized how automation can be used in industrial security to address budget restraints and skill shortages.

The summit also detailed the direction of developments in both industrial technologies and the surrounding threat landscape, including the adoption of cloud technologies for Industrial Control Systems, the broadening scope of threat actors, and the inherent limitations of patching and vulnerability management.

In addition to framing the key points of the summit, this blog will hone in on the program’s most salient points: namely, how building an in-depth understanding of ‘self’ for an ICS ecosystem can help fend off the rising tide of threat actors, and at the same time allow organizations to embrace new technologies in the face of their associated risks. Ultimately, by ‘knowing thyself,’ organizations will be able to simultaneously fight external threats, and also gain visibility into new areas of vulnerability that arise inside an organization as it evolves its industrial environment.

SANS Summit 2021: An overview

The following provides a high-level overview of the major topics discussed throughout the SANS summit:

Attacker TTPs

Threat Trend: MITRE ATT&CK for ICS provides details of known attack tradecraft.

Industry Challenge: There has been a historic lack of sharing lessons learned within the community.

Recommendation: Understand attack TTPs and align your defences with those techniques.

Industry Trend: MITRE ATT&CK for ICS offers a big step forward for the community to learn from previous attacks.

Visibility

Threat Trend: The SolarWinds attack has emphasized the vulnerability of ICS e.g. exploiting SNMP communications in BMS.

Industry Challenge: The absence of logging and event management has hindered SolarWinds investigations in CNI.

Recommendation: Use active network monitoring for log generation, and increase network and host visibility.

Industry Trend: The SolarWinds attack has emphasized the importance of CNI cyber security to the Biden administration.

Test your defenses

Threat Trend: Common TTPs — misuse of valid accounts, abuse of remote services, phishing/spear phishing.

Industry Challenge: Vulnerability tracking is not adequate to defend ICS networks — vulnerability reporting is far from comprehensive, and attackers are exploiting legitimate tools to gain access.

Recommendation: Test your defenses and your defenders using lab environments, external pentests, and adversary simulations.

Industry Trend: Pentesting of ICS environments is being performed remotely as a result of lockdown restrictions.

Know thyself

Threat Trend: The barrier to hacking ICS is lowering — threat actors are expanding, from nation states to cyber-criminals e.g. EKANS.

Industry Challenge: OT security teams suffer from a skills shortage and tight budgets.

Recommendation: Make use of the defender’s home turf advantages — defense-in-depth, learn ‘normal’ network behavior, gain visibility over internal comms.

Industry Trend: Digital solutions, such as cloud and virtualization, are being used to solve many ICS challenges.

New solutions bring new risks

Threat Trend: Third-party risks, such as OEMs and remote access points, are being exploited to gain direct access into ICS environments.

Industry Challenge: New digital solutions bring new challenges — supply chain risk, IT/OT convergence, compliance obligations, vendor lock-in.

Recommendation: If you can’t see the network, you can’t defend the network — improve visibility, identify crown jewels, boost incident response capability, and validate network segmentation.

Industry Trend: Renewable Energy industry is a big adopter of innovative ICS solutions, such as cloud, remote management, and ICSaaS. The decision to migrate to these solutions increasingly seems to be when, not if.

‘Know thyself’: Learning ‘self’ to identify emerging threats

A wide variety of threat actors are making their debut in the global ICS threat landscape. First, new state-sponsored advanced persistant threat groups (APTs) are targeting industrial ecosystems every year. 2020 also saw the addition of organized crime groups targeting ICS with new ransomware strains such as EKANS.

Accordingly, cyber-attacks on industrial systems are no longer the sole domain of nation states. With ransomware-as-a-service becoming increasingly available on the Dark Web, the barrier of entry for attacking critical infrastructure and manufacturing is demonstrably lowering. In light of this, experts at the SANS conference recommend gaining a detailed understanding of your network and making use of the defender’s home advantage with defence-in-depth.

With attacks growing in scale and sophistication, there is a growing recognition that defenses that sit at the border of organizations and attempt to keep threats out are no longer enough. Organizations must move to a model that assumes a breach, and adopt technologies that can identify cyber-threats once they are inside. This can only be achieved with a real-time, granular understanding of ‘normal’ behavior for every device and controller.

By learning, from scratch, the normal ‘pattern of life’ for all devices, users, and peer groups across industrial networks, Darktrace’s Industrial Immune System builds a sense of self for everything seen in an ICS ecosystem, as well as the digital environment as a whole. In this way, Darktrace allows organizations to ‘know thyself’ to a unparalleled degree, building a dynamic understanding of normal rather than relying on static baselines.

New solutions bring new risks

Throughout the summit, speakers discussed how they have used digital solutions such as cloud and virtualization to solve problems and cut costs. In particular, the renewable energy sector is a big adopter of cloud solutions, or “ICS as a Service” (ICSaaS). A wind farm in California, for example, might be remotely controlled by engineers on the east coast, or a vendor might maintain and run equipment for a hydroelectric plant in Latin America from their European headquarters.

As customers move to adopt these kinds of digital solutions — and with these decisions typically being made at board-level, rather than by the engineers — it seems more a question of when, not if, we see wider adoption of these technologies in the ICS community.

As OT converges with IT in the cloud, so do their associated risks. These new risks create headwinds to change, but some sectors are still adopting these new solutions and making big savings. Unified visibility across IT, OT, and the cloud have thus become a necessity for organizations seeking to accelerate digital transformation while also managing the risks of digitization and of their increasingly dynamic workforces.

A changing landscape

In the face of a new era of cyber-threats, the focus for OT specialists should not be on reactive measures, but embracing new self-learning technologies that develop an evolving understanding of ‘normal’ across industrial systems, the corporate network, cloud environments, and beyond.

By adapting to changes in the digital infrastructure, AI-powered defenses can detect and respond to zero-day threats, while alleviating the burden of security teams by automating much of the manual processes required in post-incident investigation. And by unifying insights across a range of different technologies, organizations can benefit from an enterprise-wide approach to security rather than relying on siloed defenses that lack the context for accurate decision-making.

In this age of advanced cyber-criminal rings and state-sponsored attacks, critical infrastructure and other industrial environments are now the focal point for cyber espionage and intrusions seeking to disrupt operations. The SANS ICS Security Summit reminds us of the need for defenders to face this new landscape with new and adaptive technologies that can disrupt the early signs of a threat, whether known or unknown.

Thanks to Darktrace analyst Oakley Cox for his insights.

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
David Masson
VP, Field CISO

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April 24, 2025

The Importance of NDR in Resilient XDR

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As threat actors become more adept at targeting and disabling EDR agents, relying solely on endpoint detection leaves critical blind spots.

Network detection and response (NDR) offers the visibility and resilience needed to catch what EDR can’t especially in environments with unmanaged devices or advanced threats that evade local controls.

This blog explores how threat actors can disable or bypass EDR-based XDR solutions and demonstrates how Darktrace’s approach to NDR closes the resulting security gaps with Self-Learning AI that enables autonomous, real-time detection and response.

Threat actors see local security agents as targets

Recent research by security firms has highlighted ‘EDR killers’: tools that deliberately target EDR agents to disable or damage them. These include the known malicious tool EDRKillShifter, the open source EDRSilencer, EDRSandblast and variants of Terminator, and even the legitimate business application HRSword.

The attack surface of any endpoint agent is inevitably large, whether the software is challenged directly, by contesting its local visibility and access mechanisms, or by targeting the Operating System it relies upon. Additionally, threat actors can readily access and analyze EDR tools, and due to their uniformity across environments an exploit proven in a lab setting will likely succeed elsewhere.

Sophos have performed deep research into the EDRShiftKiller tool, which ESET have separately shown became accessible to multiple threat actor groups. Cisco Talos have reported via TheRegister observing significant success rates when an EDR kill was attempted by ransomware actors.

With the local EDR agent silently disabled or evaded, how will the threat be discovered?

What are the limitations of relying solely on EDR?

Cyber attackers will inevitably break through boundary defences, through innovation or trickery or exploiting zero-days. Preventive measures can reduce but not completely stop this. The attackers will always then want to expand beyond their initial access point to achieve persistence and discover and reach high value targets within the business. This is the primary domain of network activity monitoring and NDR, which includes responsibility for securing the many devices that cannot run endpoint agents.

In the insights from a CISA Red Team assessment of a US CNI organization, the Red Team was able to maintain access over the course of months and achieve their target outcomes. The top lesson learned in the report was:

“The assessed organization had insufficient technical controls to prevent and detect malicious activity. The organization relied too heavily on host-based endpoint detection and response (EDR) solutions and did not implement sufficient network layer protections.”

This proves that partial, isolated viewpoints are not sufficient to track and analyze what is fundamentally a connected problem – and without the added visibility and detection capabilities of NDR, any downstream SIEM or MDR services also still have nothing to work with.

Why is network detection & response (NDR) critical?

An effective NDR finds threats that disable or can’t be seen by local security agents and generally operates out-of-band, acquiring data from infrastructure such as traffic mirroring from physical or virtual switches. This means that the security system is extremely inaccessible to a threat actor at any stage.

An advanced NDR such as Darktrace / NETWORK is fully capable of detecting even high-end novel and unknown threats.

Detecting exploitation of Ivanti CS/PS with Darktrace / NETWORK

On January 9th 2025, two new vulnerabilities were disclosed in Ivanti Connect Secure and Policy Secure appliances that were under malicious exploitation. Perimeter devices, like Ivanti VPNs, are designed to keep threat actors out of a network, so it's quite serious when these devices are vulnerable.

An NDR solution is critical because it provides network-wide visibility for detecting lateral movement and threats that an EDR might miss, such as identifying command and control sessions (C2) and data exfiltration, even when hidden within encrypted traffic and which an EDR alone may not detect.

Darktrace initially detected suspicious activity connected with the exploitation of CVE-2025-0282 on December 29, 2024 – 11 days before the public disclosure of the vulnerability, this early detection highlights the benefits of an anomaly-based network detection method.

Throughout the campaign and based on the network telemetry available to Darktrace, a wide range of malicious activities were identified, including the malicious use of administrative credentials, the download of suspicious files, and network scanning in the cases investigated.

Darktrace / NETWORK’s autonomous response capabilities played a critical role in containment by autonomously blocking suspicious connections and enforcing normal behavior patterns. At the same time, Darktrace Cyber AI Analyst™ automatically investigated and correlated the anomalous activity into cohesive incidents, revealing the full scope of the compromise.

This case highlights the importance of real-time, AI-driven network monitoring to detect and disrupt stealthy post-exploitation techniques targeting unmanaged or unprotected systems.

Unlocking adaptive protection for evolving cyber risks

Darktrace / NETWORK uses unique AI engines that learn what is normal behavior for an organization’s entire network, continuously analyzing, mapping and modeling every connection to create a full picture of your devices, identities, connections, and potential attack paths.

With its ability to uncover previously unknown threats as well as detect known threats using signatures and threat intelligence, Darktrace is an essential layer of the security stack. Darktrace has helped secure customers against attacks including 2024 threat actor campaigns against Fortinet’s FortiManager , Palo Alto firewall devices, and more.  

Stay tuned for part II of this series which dives deeper into the differences between NDR types.

Credit to Nathaniel Jones VP, Security & AI Strategy, FCISO & Ashanka Iddya, Senior Director of Product Marketing for their contribution to this blog.

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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April 22, 2025

Obfuscation Overdrive: Next-Gen Cryptojacking with Layers

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Out of all the services honeypotted by Darktrace, Docker is the most commonly attacked, with new strains of malware emerging daily. This blog will analyze a novel malware campaign with a unique obfuscation technique and a new cryptojacking technique.

What is obfuscation?

Obfuscation is a common technique employed by threat actors to prevent signature-based detection of their code, and to make analysis more difficult. This novel campaign uses an interesting technique of obfuscating its payload.

Docker image analysis

The attack begins with a request to launch a container from Docker Hub, specifically the kazutod/tene:ten image. Using Docker Hub’s layer viewer, an analyst can quickly identify what the container is designed to do. In this case, the container is designed to run the ten.py script which is built into itself.

 Docker Hub Image Layers, referencing the script ten.py.
Figure 1: Docker Hub Image Layers, referencing the script ten.py.

To gain more information on the Python file, Docker’s built in tooling can be used to download the image (docker pull kazutod/tene:ten) and then save it into a format that is easier to work with (docker image save kazutod/tene:ten -o tene.tar). It can then be extracted as a regular tar file for further investigation.

Extraction of the resulting tar file.
Figure 2: Extraction of the resulting tar file.

The Docker image uses the OCI format, which is a little different to a regular file system. Instead of having a static folder of files, the image consists of layers. Indeed, when running the file command over the sha256 directory, each layer is shown as a tar file, along with a JSON metadata file.

Output of the file command over the sha256 directory.
Figure 3: Output of the file command over the sha256 directory.

As the detailed layers are not necessary for analysis, a single command can be used to extract all of them into a single directory, recreating what the container file system would look like:

find blobs/sha256 -type f -exec sh -c 'file "{}" | grep -q "tar archive" && tar -xf "{}" -C root_dir' \;

Result of running the command above.
Figure 4: Result of running the command above.

The find command can then be used to quickly locate where the ten.py script is.

find root_dir -name ten.py

root_dir/app/ten.py

Details of the above ten.py script.
Figure 5: Details of the above ten.py script.

This may look complicated at first glance, however after breaking it down, it is fairly simple. The script defines a lambda function (effectively a variable that contains executable code) and runs zlib decompress on the output of base64 decode, which is run on the reversed input. The script then runs the lambda function with an input of the base64 string, and then passes it to exec, which runs the decoded string as Python code.

To help illustrate this, the code can be cleaned up to this simplified function:

def decode(input):
   reversed = input[::-1]

   decoded = base64.decode(reversed)
   decompressed = zlib.decompress(decoded)
   return decompressed

decoded_string = decode(the_big_text_blob)
exec(decoded_string) # run the decoded string

This can then be set up as a recipe in Cyberchef, an online tool for data manipulation, to decode it.

Use of Cyberchef to decode the ten.py script.
Figure 6: Use of Cyberchef to decode the ten.py script.

The decoded payload calls the decode function again and puts the output into exec. Copy and pasting the new payload into the input shows that it does this another time. Instead of copy-pasting the output into the input all day, a quick script can be used to decode this.

The script below uses the decode function from earlier in order to decode the base64 data and then uses some simple string manipulation to get to the next payload. The script will run this over and over until something interesting happens.

# Decode the initial base64

decoded = decode(initial)
# Remove the first 11 characters and last 3

# so we just have the next base64 string

clamped = decoded[11:-3]

for i in range(1, 100):
   # Decode the new payload

   decoded = decode(clamped)
   # Print it with the current step so we

   # can see what’s going on

   print(f"Step {i}")

   print(decoded)
   # Fetch the next base64 string from the

   # output, so the next loop iteration will

   # decode it

   clamped = decoded[11:-3]

Result of the 63rd iteration of this script.
Figure 7: Result of the 63rd iteration of this script.

After 63 iterations, the script returns actual code, accompanied by an error from the decode function as a stopping condition was never defined. It not clear what the attacker’s motive to perform so many layers of obfuscation was, as one round of obfuscation versus several likely would not make any meaningful difference to bypassing signature analysis. It’s possible this is an attempt to stop analysts or other hackers from reverse engineering the code. However,  it took a matter of minutes to thwart their efforts.

Cryptojacking 2.0?

Cleaned up version of the de-obfuscated code.
Figure 8: Cleaned up version of the de-obfuscated code.

The cleaned up code indicates that the malware attempts to set up a connection to teneo[.]pro, which appears to belong to a Web3 startup company.

Teneo appears to be a legitimate company, with Crunchbase reporting that they have raised USD 3 million as part of their seed round [1]. Their service allows users to join a decentralized network, to “make sure their data benefits you” [2]. Practically, their node functions as a distributed social media scraper. In exchange for doing so, users are rewarded with “Teneo Points”, which are a private crypto token.

The malware script simply connects to the websocket and sends keep-alive pings in order to gain more points from Teneo and does not do any actual scraping. Based on the website, most of the rewards are gated behind the number of heartbeats performed, which is likely why this works [2].

Checking out the attacker’s dockerhub profile, this sort of attack seems to be their modus operandi. The most recent container runs an instance of the nexus network client, which is a project to perform distributed zero-knowledge compute tasks in exchange for cryptocurrency.

Typically, traditional cryptojacking attacks rely on using XMRig to directly mine cryptocurrency, however as XMRig is highly detected, attackers are shifting to alternative methods of generating crypto. Whether this is more profitable remains to be seen. There is not currently an easy way to determine the earnings of the attackers due to the more “closed” nature of the private tokens. Translating a user ID to a wallet address does not appear to be possible, and there is limited public information about the tokens themselves. For example, the Teneo token is listed as “preview only” on CoinGecko, with no price information available.

Conclusion

This blog explores an example of Python obfuscation and how to unravel it. Obfuscation remains a ubiquitous technique employed by the majority of malware to aid in detection/defense evasion and being able to de-obfuscate code is an important skill for analysts to possess.

We have also seen this new avenue of cryptominers being deployed, demonstrating that attackers’ techniques are still evolving - even tried and tested fields. The illegitimate use of legitimate tools to obtain rewards is an increasingly common vector. For example,  as has been previously documented, 9hits has been used maliciously to earn rewards for the attack in a similar fashion.

Docker remains a highly targeted service, and system administrators need to take steps to ensure it is secure. In general, Docker should never be exposed to the wider internet unless absolutely necessary, and if it is necessary both authentication and firewalling should be employed to ensure only authorized users are able to access the service. Attacks happen every minute, and even leaving the service open for a short period of time may result in a serious compromise.

References

1. https://www.crunchbase.com/funding_round/teneo-protocol-seed--a8ff2ad4

2. https://teneo.pro/

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About the author
Nate Bill
Threat Researcher
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