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February 6, 2024

Cyber Security Threat Trends of 2023: Analysis of the Last Six Months

Darktrace's comprehensive report on the threats faced by businesses examines the trends our Threat Research team saw across our customer fleet in the second half of 2023.
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
The Darktrace Threat Research Team
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06
Feb 2024

Darktrace Threat Report

Darktrace’s distinctive approach to threat analysis yields us a unique perspective on the threat landscape. In our End of Year Threat Report, we built on the work of our First 6: Half-Year Threat Report, sharing the insights we've garnered throughout the latter half of 2023.  

We have observed not only the continuing development and evolution of identified threats in the malware and ransomware spaces, but also changes brought about by the innovation of cyber security tools.  

Amid these challenges, the breadth, scope, and complexity of threats to organizations has grown, underscoring the importance of employing behavioral analysis, anomaly detection, and AI for cyber security.  

Threat Research Across the Customer Fleet

Malware-as-a-Service (MaaS) and Ransomware-as-a-Service (RaaS) together represent the majority of malicious tools across the cyber threat landscape and were the most consistently identified threats affecting Darktrace customers in the second half of 2023. These malicious tools have a variety of capabilities, with many including tailorable or bespoke elements alterable from campaign to campaign.  

Figure 1: The diagram represents Darktrace detections containing indicators of compromise (IoCs) that have been associated with particular MaaS and RaaS threats. The size of the bubble displayed relates to the frequency of detections observed across the Darktrace fleet.

The Darktrace Threat Research team found that within MaaS and RaaS offerings detected across the customer fleet, loader malware was the most observed threat category, accounting for 77% of all investigated threats.  

MaaS initial access offerings were often observed harvesting data, which could then be sold, and loading or enabling subsequent infections by second and third-stage payloads, resulting in more damaging malware attacks and even ransomware.

Similar to how the MaaS and RaaS tools were often customized in an attempt to land an attack, Darktrace observed the cross-functional adaptation of many other malware strains, such as remote access trojans (RATs) and information-stealing malware, along with existing tools like Cobalt Strike.  

The ability to remix known strains of malware can increase the difficulty of detection by combining kill chain elements and utilizing overlapping compromised infrastructure. Malware developers achieve this by using open-source repositories, leaked code, and multi-faceted tooling.

SOC Team Insights on Major Trends

The Darktrace Security Operations Center (SOC), which helps customers investigate threats, observed two significant trends in the second half of 2023.

1. Enhanced Defense Evasion Methods

Darktrace's SOC saw an increase in usage of a variety of defense evasion methods, such as the session cookie abuse to evade multi-factor authentication (MFA), the targeting of ESXi servers for ransomware encryption to evade host-based security measures, and the use of tunnelling services such as Cloudflare Tunnel to hide command-and-control (C2) infrastructure.  

Malicious actors' increased usage of these defense evasion methods is a probable result of prominence of endpoint solutions within the security industry.

2. Ransomware

Ransomware continued to be the most common compromise. Darktrace's SOC observed ransomware actors compromising Internet-facing servers, such as Exchange, Citrix Netscaler, Ivanti Sentry, Remote Desktop Services (RDS) hosts, VPN appliances, and Confluence, in order to gain entry to target networks. Once inside, ransomware actors abused Remote Monitoring and Management (RMM) tools such as Splashtop, Atera, AnyDesk, and Action1, to gain access to target systems.  

A variety of ransomware strains were observed, with LockBit, ALPHV (i.e, BlackCat), Play, and Akira being the most common.

Top Critical Vulnerabilities

New critical vulnerabilities (CVEs), like Log4J and ProxyLogon, regularly enter the public domain within a short time of discovery, meaning the average time to exploitation is shorter than ever. As such, organizations must be able to promptly identify whether they are susceptible to new vulnerabilities and understand mitigation techniques.  

In the second half of 2023, there were five major vulnerabilities observed by Darktrace across its customer fleet, as determined by the number of affected assets.

1. CVE-2022-42889 is a critical vulnerability in the Apache Commons Text Library which has been compared to Log4Shell, albeit not as widespread. Apache Commons Text performs variable interpolation, allowing properties to be dynamically evaluated and expanded. Affected versions are vulnerable to remote code execution or unintentional exposure to remote servers if untrusted configuration values are used.

2. CVE-2023-25690 is a critical vulnerability which enables HTTP request smuggling attacks on Apache HTTP Server. If exploited, it could be used by an attacker to bypass access constraints in proxy servers, route undesired URLs to existing origin servers and perform cache poisoning.

3. Two critical vulnerabilities were observed in Git that would enable attackers to execute arbitrary code after successfully exploiting heap-based buffer overflow weaknesses. CVE-2022-41903 would allow an attacker to trigger a heap-based memory corruption during clone or pull operations, resulting in remote code execution, while CVE-2022-23521 could enable code execution during an archive operation, which is commonly performed by Git forges.

4. CVE-2023-2982 is an authentication bypass vulnerability disclosed in miniOrange's Social Login and Register plugin for WordPress that could enable a malicious actor to log in as any user, provided that they know the corresponding email address.

5. CVE-2023-46747 is a critical vulnerability rooted in the configuration of BIG-IP that could result in unauthenticated remote code execution. This vulnerability allows malicious actors to gain unauthorized access to networks through the management port and/or self-IP addresses to execute arbitrary system commands.

Stay Ahead of Threats with AI-Powered Cyber Security

After tracking threat trends across its customer fleet in the second half of 2023, Darktrace found that MaaS like loader malware, ransomware and especially RaaS, and enhanced defense evasion methods were top threats.  

As threats continue to evolve, it’s more important than ever to have cyber security tools that can detect and respond in real time, even when dealing with remixed and novel attacks.  

Darktrace’s approach to cyber security allows it to do just that. The Darktrace platform uses AI that learns from each organization’s specific data to understand ‘normal’ in order to recognize activity that is abnormal and indicative of a cyber-attack.  

As a result, Darktrace can detect and respond to attacks, including customized strains of malware and ransomware, even if they have been altered from previously known instances. Since it is powered by AI, Darktrace can take action within seconds.

Darktrace can also help organizations address new CVEs. Darktrace/Newsroom, a capability included with Darktrace’s attack surface management (ASM) tool, continuously monitors open-source intelligence (OSINT) sources for new CVEs and assesses each organization’s exposure through its in-depth knowledge of the unique external attack surface. It then presents a detailed summary of the vulnerability, highlighting the affected software and how many assets run this software on the customer’s network.

With AI that is trained on your organization’s data, Darktrace protects against the trending threats of today and the emerging threats of tomorrow.  

Learn more about the latest threat trends in the full report

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
The Darktrace Threat Research Team

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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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About the author
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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