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May 9, 2023

Breaking Down "ICES": An Umbrella Term With Wide Variety

Integrated Cloud Email Security (ICES) can be an effective email security solution, but Darktrace/Email's self-learning AI should be your solution of choice.
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.
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Dan Fein
VP, Product
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09
May 2023

While organizing email security solutions into categories can help security teams understand the types of products available, it can also lead to generalizations that overlook important differences within those categories and can become like comparing apples to oranges.

This is true for the Integrated Cloud Email Security (ICES) category. Among the products that qualify, there are important variations in approach that can mean the difference between stopping a novel phishing attack on the first encounter and catching it as many as 13 days later.

These distinctions highlight that not all ICES products and not all AI tools are made equal, and it’s critical to look deeper than the “ICES” label when examining an email security solution. 

What is an ICES solution?

Gartner devised the term ICES in 2021 to describe an advanced email security that augments the native capabilities of email providers by using API access to analyze email content without requiring changing the MX record. 

In other words, ICES solutions integrate with an organization’s cloud email provider to filter out malicious emails.

ICES has risen in popularity as more and more organizations shift to cloud-based or hybrid email servers, and encounter new, more sophisticated threats. Organizations pair ICES with improved native capabilities of email providers. For example, in the 2023 Market Guide for Email Security, Gartner acknowledged that “Microsoft, in particular, continues to make significant investments in improving protection effectiveness and providing better configuration guidance.” 

Native capabilities can detect traditional indicators of compromise, while ICES products can detect nuanced attacks. They integrate directly with cloud-based email providers, meaning emails do not have to be rerouted for analysis, therefore reducing the time security teams would have to spend configuring and maintaining that connection or risking operational outage. 

ICES protects against sophisticated attacks

Before the rise of ICES, the mainstream email security solutions were Secure Email Gateways (SEGs), which can be characterized as tools that rely on historic data to create rules and signatures. This purely reactive approach cannot contend with the current email threat landscape, which includes attacks that abuse legitimate services, originate from compromised known senders, or are entirely novel. They also struggle to detect multi-stage attacks and insider threats

Instead, ICES products use natural language processing and natural language understanding to identify social engineering like business email compromises, spoofing, supply chain attacks, account takeovers, and more.  However, although ICES products can detect more sophisticated threats than SEGs, not all of them can stop entirely unknown attacks. 

Achieving bespoke security with AI that understands you

Even though several ICES products rely on machine learning to identify and stop malicious emails, not all AI is the same. Typically, other vendors’ AIs are trained on insights pulled from across their respective customer-bases and past attacks. However, this does not account for nuanced distinctions that arise from organizations’ sizes, industries, or even the individual employees working at each company. 

Instead, Darktrace understands you. Self-Learning AI™ focuses on the organization it is installed in, instead of generalizing across a wider pool. Darktrace even learns on a granular level, building profiles of every individual employee by analyzing behaviors like how they typically communicate, where and when they log in, the tone and sentiment of their emails, file and link sharing patterns, and hundreds of other signals. This level of specificity ensures that the email security is tailored to each specific organization. 

The ability to learn employee behavior allows Darktrace to detect what is not normal, therefore revealing sophisticated threats on the first encounter. It can detect all types of attacks, including BEC, account takeover, insider threat, compromised internal accounts, and even human error. 

But it’s the ability to stop novel attacks upon the first encounter that sets it apart. Darktrace/Email™ can detect novel email attacks an average of 13 days earlier than email security tools that are trained on knowledge of historical threats. 

Moreover, Darktrace can take precise action to respond to threats, beyond simply allowing or blocking a suspicious email. The AI makes micro-decisions to neutralize only the malicious components of emails. For example, it might flatten an attached PDF, rewrite a shared link, or file an email as junk. 

Darktrace/Email goes further than other ICES by considering the employee experience. With an employee-AI feedback loop, the AI can fine-tune security based on the employees while also providing inline security awareness training in real-time and with real-life examples. By engaging down to the employee level, Darktrace AI can even leverage personalized insights for productivity gains, sorting out graymail based on how each user prefers to interact with it. 

Putting the “I” in “ICES”

Many ICES vendors emphasize the “integrated” part of the acronym, however Darktrace excels at this. Since Darktrace can be installed anywhere a company has data, it can natively interact across the digital estate, saving the security team time and resources otherwise spent learning various dashboards and languages, correlating data across different areas, and manually monitoring daily activity. Darktrace/Email can also integrate with external tools, including SIEMs and SOARs, to further enhance workflows

Moreover, since combining ICES solutions with native security email capabilities creates a hardened security posture, Darktrace/Email benefits from its strong, established integration with Microsoft

Introducing flexibility to ICES deployments

Finally, the security and integration capabilities of Darktrace/Email deploy easily. In the 2023 Market Guide for Email Security, Gartner predicted that “by 2025, 20% of anti-phishing solutions will be delivered via API integration with the email platform, up from less than 5% today.” Darktrace/Email can be rolled out via API or API + Journaling in Microsoft 365, whichever better fits the organization’s needs.

While all ICES products are API-based, that does not mean they are AI-first, or are using the best AI approach. Even some SEGs can deploy via API. That means that the ability to deploy via API does not guarantee a level of security that can stop the most sophisticated threats. Security teams should look beyond deployment method and select the ICES and AI solutions that provide tailored, effective security. 

Finding nuance as an ICES solution

Email security continues to advance in tandem with the threat landscape and organizations’ digital infrastructures. ICES solutions are supplanting SEGs as the mainstream email security solutions, however that broad category includes a range of tools with varying applications of AI. These differences make it critical to not put all ICES products in the same basket. 

Darktrace/Email is the only ICES solution that uses Self-Learning AI to detect all types of email threats, including novel attacks, within seconds.

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
Dan Fein
VP, Product

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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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April 22, 2025

How NDR and Secure Access Service Edge (SASE) Work Together to Achieve Network Security Outcomes

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Modern networks are evolving rapidly, with traffic patterns, user behavior, and critical assets extending far beyond the boundaries of traditional network security tools. As organizations adopt hybrid infrastructures, remote working, and cloud-native services, it is essential to maintain visibility and protect this expanding attack surface.

Network Detection and Response (NDR) and Secure Access Service Edge (SASE) are two technologies commonly used to safeguard organizational networks. While both play crucial roles in enhancing security, one does not replace the other. Instead, NDR and SASE complement each other, taking on different roles to create a robust network security framework. This blog will unpack the relationship between NDR and SASE, including the component functionalities that comprise SASE, highlighting their unique contributions to maintaining a comprehensive and resilient network security strategy.

Network Detection and Response (NDR) and Secure Access Service Edge (SASE) explained

NDR solutions, such as Darktrace / NETWORK, are designed to detect, investigate, and respond to suspicious activities within any network. By leveraging machine learning and behavioral analytics, NDR continuously monitors network traffic to identify anomalies that could indicate potential threats and to contain those threats at machine speed. These solutions analyze both North-South traffic (between internal and external networks) and East-West traffic (within internal networks), providing comprehensive visibility into network activities.

SASE, on the other hand, comprises multiple solutions, focused on providing hybrid and remote users access to services while adhering to the Zero Trust principle of "never trust, always verify". Within SASE architectures, Zero Trust Network Access (ZTNA) solutions provide secure remote access to private applications and services the user has been explicitly granted, and Secure Web Gateways (SWG) provide Internet access, again based on policy groups. Unlike traditional security models that grant implicit trust to users within the network perimeter, ZTNA requires continuous verification of user identity and device health before granting access to resources. This approach minimizes the attack surface and reduces the risk of unauthorized access to sensitive data and internal applications. Similarly, SWGs filter web traffic based on the verified user identity and can block known malware, further reducing the attack surface for the client estate.

Limitations of SASE highlights the importance of NDR

While SASE, including ZTNA and SWG, is a powerful tool for enforcing secure access to company networks and resources as well as the Internet, it is not a comprehensive security solution, or a replacement for dedicated network monitoring and NDR capabilities. Some of the main limitations include:

  • Focused on policies rather than security: SASE delivers strong networking outcomes but provides policy-based protections, rather than a full suite of security features. It can provide simple alerting for disallowed actions, but it lacks the security context needed for comprehensive threat detection, such as knowing if user credentials have been compromised.
  • Can only detect known threats: SASE solutions cannot detect novel attacks such as zero-days and insider threats. This is because they rely on a rule-based approach that does not have a behavioral understanding of network entities that can detect anomalies or suspicious activity.
  • Limited response capabilities: Due to the limited detection capabilities of SASE solutions, it is not possible to automate response actions to threats that slip past existing policies.  While access to internal resources and the Internet can be revoked or severely limited as part of a response, this must be done after human investigation and analysis, allowing more time for the threat to continue before being contained.
  • Limited scope: SASE provides cloud-hosted secure networking, which lends itself much more toward the client estate of any organization. As a result, servers and unmanaged devices—whether IT/IoT/OT—are mostly out of scope and do not benefit from the policies SASE enforces.

The complementary roles of NDR and ZTNA

NDR solutions provide full visibility into network activity, with the ability to detect and respond to threats that may bypass initial access controls and filters. When combined, NDR and SASE create a layered security approach that addresses different aspects of network security, for example:

  • Detection of novel, unknown and insider threats: NDR solutions can monitor all network traffic using behavioral anomaly detection. This can identify suspicious activities, such as insider threats from authorized users who have passed policy checks, or novel attacks that have never been seen before.
  • Validation of policies: By continuously monitoring network traffic, NDR can validate the effectiveness of existing policies and identify any gaps in security that need addressing due to organizational changes or outdated rule sets.
  • Reducing risk and impact of threats: Together, SASE and NDR solutions shift toward proactive security by reducing the potential impact of a threat through predefined policies and by detecting and containing a threat in its earliest stages, even if it is novel or nuanced.
  • Enhanced contextual information: Alerts raised by SASE solutions can provide additional context into potential threats, which can be used by NDR solutions to increase investigation quality and context.
  • Containment of network threats: SASE solutions can prohibit access to resources on an internal company network or on the Internet if predefined access control criteria are not met or a site matches a threat signature. When combined with an NDR solution, organizations can go far beyond this, detecting and responding to a much wider variety of network threats to prevent attacks from escalating.

When implementing SASE and NDR solutions, it is also crucial to consider the best configurations to maximize interoperability, and integrations will often increase functionality. Well-designed implementations, combined with integrations, will strengthen both SASE and NDR solutions for organizations.

How Darktrace continues to secure SASE networks

With the latest 6.3 update, Darktrace continues to extend its capabilities with new innovations that support modern enterprise networks and the use of SASE across remote and hybrid worker devices. This expands on existing Darktrace integrations and partnerships with SASE vendors such as Netskope and Zscaler.

Traditional methods to contain remote access and internet-born threats are either signature or policy based, and response to nuanced threats requires manual, human-led investigation and decision-making. By the time security teams can react, the damage is often already done.

With Darktrace 6.3, customers using Zscaler can now configure Darktrace Autonomous Response to quarantine ZPA-connected user devices at machine speed. This provides a powerful new mechanism for containing remote threats at the earliest sign of suspicious activity, without disrupting broader operations.

By automatically shutting down ZPA access for compromised user accounts, Darktrace gives SOC teams valuable time to investigate and respond, while continuing to protect the rest of the organization. This integration enhances Darktrace’s ability to take actions for remote user devices, helping customers contain threats faster and keep the business running smoothly.

For organizations using SASE technologies to address the challenges of securing large, distributed networks across a range of geographies, SaaS applications and remote worker devices, Darktrace also now integrates with Netskope Cloud TAP to provide visibility into and analysis over tunneled traffic, reducing blind spots and enabling organizations to maintain detection capabilities across their expanding network perimeters.

Conclusion

While NDR and ZTNA serve distinct purposes, their integration is crucial for a comprehensive security strategy. ZTNA provides robust access controls, ensuring that only authorized users can access network resources. NDR, on the other hand, offers continuous visibility into network activities, detecting and responding to threats that may bypass initial access controls. By leveraging the strengths of both solutions, organizations can enhance their security posture and protect against a wide range of network security threats.

Understanding the complementary roles of NDR and ZTNA is essential for building a resilient security framework. As cyber threats continue to evolve, adopting a multi-layered, defense-in-depth security approach will be key to safeguarding organizational networks.

Click here for more information about the latest product innovations in Darktrace 6.3, or learn more about Darktrace / NETWORK here.

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About the author
Mikey Anderson
Product Marketing Manager, Network Detection & Response
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