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July 31, 2024

CDR is just NDR for the Cloud... Right?

As cloud adoption surges, the need for scalable, cloud-native security is paramount. This blog explores whether Cloud Detection and Response (CDR) is merely Network Detection and Response (NDR) tailored for the cloud, highlighting the unique challenges and essential solutions SOC teams require to secure dynamic cloud environments effectively.
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
Adam Stevens
Senior Director of Product, Cloud | Darktrace
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31
Jul 2024

The need for scalable cloud-native security

The cybersecurity landscape is undergoing a rapid transformation driven by the accelerated adoption of cloud computing, compelling organizations to reevaluate their security strategies. According to Forrester’s Infrastructure Cloud Survey, 2023, cloud decision-makers who are moving to a cloud computing infrastructure estimated they have already moved 39% of their application portfolio to the cloud and intend to move another 53% in the next two years [1].

This explosive growth underscores not only the increased dependency on cloud services, but also the evolving sophistication of cyber threats targeting these platforms, and the critical need for dedicated security measures tailored to cloud infrastructures — thereby making cloud security a pivotal focus for Security Operations Center (SOC) teams.

As organizations increasingly migrate to cloud environments and their reliance on cloud infrastructures deepens, they encounter new security challenges that require reevaluating their security strategies. Traditional measures like Network Detection and Response (NDR) are being reassessed in favor of more dynamic, scalable cloud-native solutions.

However, can we truly say that cloud detection and response (CDR) is fundamentally different? Or is it simply an evolution of NDR tailored for the cloud?

Cloud Detection and Response (CDR) vs Network Detection and Response (NDR)

Cloud Detection and Response (CDR) has emerged as a pivotal technology in the race against threat actors targeting cloud assets. CDR is typically centered around the same foundational principles as NDR. As such, NDR providers are well placed to provide these capabilities within dynamic cloud environments – particularly those providers that are built upon the foundation of understanding your business, its digital footprint, and leveraging that understanding to detect subtle deviations and highlighting anomalies as opposed to pre training or relying on rules and signatures.

However, there are unique challenges within cloud environments that require a wider, richer, context-aware approach.

Why SOC Teams Care

Widespread UseThe shift towards cloud services is no longer a trend but a standard practice across industries. Organizations increasingly rely on cloud infrastructures for essential operations across IaaS, PaaS, and SaaS platforms. According to Gartner, worldwide end-user spending on public cloud services is forecast to grow 20.4% to total $678.8 billion in 2024, up from $563.6 billion in 2023 [2]. This widespread adoption necessitates a security approach that can operate seamlessly across varied cloud environments, addressing both the scalability and the agility that these platforms offer.

Sophisticated AttacksCyber threats have evolved in sophistication, specifically targeting cloud platforms due to their growing prevalence. Attackers exploit the dynamic nature of cloud services, where traditional security measures often fall short. The cloud has emerged as a major target for threat actors who want to control access to, manipulate, and steal that data. This makes cloud resources a bigger target than ever for attackers. According to the IBM Cost of a Data Breach 2023 report, 82% of breaches involved data stored in the cloud [3]. Examples include data breaches initiated through misconfigured storage instances or through the exploitation of incomplete data deletion processes, highlighting the need for cloud-specific security responses.

Dynamic EnvironmentsCloud environments are inherently dynamic, characterized by the rapid provisioning and de-provisioning of resources, this fluidity presents a significant challenge for maintaining continuous security oversight, organizations need to be able to see what individual assets in the cloud look like at any given moment, who or what can access those, but also to be able to detect and respond to changes in real time. Unlike traditional infrastructure, detection and response in the cloud is challenging because of the ephemeral nature of some cloud assets and the velocity and volume of new app deployment – traditional signature-based detections will often struggle to work with such data.

What SOC Teams Need

Centralized VisibilityEffective security management requires a comprehensive, unified view spanning all operational environments including multi-cloud platforms and on-premises datacenters. Furthermore, in today's complex IT landscape, where organizations operate across both on-premises and various cloud environments, the need for centralized visibility becomes paramount. This comprehensive oversight is crucial for detecting anomalies and potential threats in real time, allowing SOC teams to manage security from a single source of truth, despite the dispersed nature of cloud assets and the heterogeneity of on-premises resources. By integrating these views, organizations can ensure a seamless security posture that encompasses all operational environments, enhancing their ability to respond swiftly to incidents and reduce security gaps.

AutomationGiven the vast scale and complexity of cloud operations, automation in detection and response processes is indispensable. Automated security solutions can instantly respond to threats, or adjust permissions across the cloud, enhancing both the efficiency and effectiveness of security measures.

Containment and RemediationThe capability for swift containment and remediation of security incidents is vital to minimize their impact on business operations. Automated response mechanisms that can isolate affected systems, revoke access, or reroute traffic until the threat is neutralized are essential components of modern CDR solutions.

Unpacking the Essentials: What Sets CDR Apart from NDR

While CDR and NDR share similar goals of threat mitigation, the context within cloud environments brings additional complexities:

Who: The identification of user roles and access patterns in cloud environments is crucial for detecting insider threats or compromised accounts. For example, an account behaving irregularly or accessing unusual data points may indicate a security breach.

What: Understanding what resources are deployed in the cloud (such as VMs, containers, and serverless functions) and the types of data they handle helps prioritize security efforts. Protecting data with varying sensitivity levels requires different security protocols.

Where: The geographic distribution of cloud datacenters affects regulatory compliance and data sovereignty. Security measures must consider these factors to ensure that data storage and processing comply with local laws and regulations.

How: Monitoring the configuration and usage of cloud services helps in identifying misconfigurations and anomalous usage patterns, which are common vectors for attacks. Tools that can automatically scan and rectify configurations in real time are particularly valuable in maintaining cloud security.

Key takeaways and benefits of CDR

As cloud adoption continues to surge, the strategic importance of CDR becomes increasingly evident. However, NDR vendors are well-positioned to provide these capabilities, especially those who deeply understand customer environments by learning the pattern of life of resources rather than relying on static rules and signatures.

Cloud environments, at their core, are still comprised of networks for communication. Interactions between cloud resources need to be monitored in real time, and access to these resources needs to be tracked and managed. As the cloud changes dynamically, the understanding and visualization of what is deployed and where needs to be updated quickly. Above all effective and proportional cloud-native response needs to be provided to mitigate threats and avoid business disruption.

Moreover, the ideal solutions will not only monitor network interactions but also bring in cloud contextual awareness. By combining these insights, SOC teams can gain a deeper understanding of permissions, assess risk vulnerabilities, and integrate all these elements into a single, cohesive platform. Importantly, SOC teams need to go beyond detection and response to actively mitigate potential misconfigurations and stay preventative. After all, proactive security is much better than reactive. By leveraging such comprehensive solutions, SOC teams can better equip themselves to tackle the modern cybersecurity landscape, ensuring robust, responsive, and adaptable defenses.

Learn more about Darktrace / CLOUD

Darktrace / CLOUD is intelligent cloud security powered by Self-Learning AI that delivers continuous, context-aware visibility and monitoring of cloud assets to unlock real-time detection and response​,​ and proactive cloud risk management. Read more about our cloud security solution here.

References

[1]  Gartner Forecasts Worldwide Public Cloud End-User Spending to Surpass $675 Billion in 2024

[2]  Public Cloud Market Insights, 2023 | Forrester

[3]  IBM Cost of a Data Breach 2023 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
Adam Stevens
Senior Director of Product, Cloud | Darktrace

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March 5, 2026

Inside Cloud Compromise: Investigating Attacker Activity with Darktrace / Forensic Acquisition & Investigation

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Investigating cloud attacks with Darktrace/ Forensic Acquisition & Investigation

Darktrace / Forensic Acquisition & Investigation™ is the industry’s first truly automated forensic solution purpose-built for the cloud. This blog will demonstrate how an investigation can be carried out against a compromised cloud server in minutes, rather than hours or days.

The compromised server investigated in this case originates from Darktrace’s Cloudypots system, a global honeypot network designed to observe adversary activity in real time across a wide range of cloud services. Whenever an attacker successfully compromises one of these honeypots, a forensic copy of the virtual server's disk is preserved for later analysis. Using Forensic Acquisition & Investigation, analysts can then investigate further and obtain detailed insights into the compromise including complete attacker timelines and root cause analysis.

Forensic Acquisition & Investigation supports importing artifacts from a variety of sources, including EC2 instances, ECS, S3 buckets, and more. The Cloudypots system produces a raw disk image whenever an attack is detected and stores it in an S3 bucket. This allows the image to be directly imported into Forensic Acquisition & Investigation using the S3 bucket import option.

As Forensic Acquisition & Investigation runs cloud-natively, no additional configuration is required to add a specific S3 bucket. Analysts can browse and acquire forensic assets from any bucket that the configured IAM role is permitted to access. Operators can also add additional IAM credentials, including those from other cloud providers, to extend access across multiple cloud accounts and environments.

Figure 1: Forensic Acquisition & Investigation import screen.

Forensic Acquisition & Investigation then retrieves a copy of the file and automatically begins running the analysis pipeline on the artifact. This pipeline performs a full forensic analysis of the disk and builds a timeline of the activity that took place on the compromised asset. By leveraging Forensic Acquisition & Investigation’s cloud-native analysis system, this process condenses hour of manual work into just minutes.

Successful import of a forensic artifact and initiation of the analysis pipeline.
Figure 2: Successful import of a forensic artifact and initiation of the analysis pipeline.

Once processing is complete, the preserved artifact is visible in the Evidence tab, along with a summary of key information obtained during analysis, such as the compromised asset’s hostname, operating system, cloud provider, and key event count.

The Evidence overview showing the acquired disk image.
Figure 3: The Evidence overview showing the acquired disk image.

Clicking on the “Key events” field in the listing opens the timeline view, automatically filtered to show system- generated alarms.

The timeline provides a chronological record of every event that occurred on the system, derived from multiple sources, including:

  • Parsed log files such as the systemd journal, audit logs, application specific logs, and others.
  • Parsed history files such as .bash_history, allowing executed commands to be shown on the timeline.
  • File-specific events, such as files being created, accessed, modified, or executables being run, etc.

This approach allows timestamped information and events from multiple sources to be aggregated and parsed into a single, concise view, greatly simplifying the data review process.

Alarms are created for specific timeline events that match either a built-in system rule, curated by Darktrace’s Threat Research team or an operator-defined created at the project level. These alarms help quickly filter out noise and highlight on events of interest, such as the creation of a file containing known malware, access to sensitive files like Amazon Web Service (AWS) credentials, suspicious arguments or commands, and more.

 The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.
Figure 4: The timeline view filtered to alarm_severity: “1” OR alarm_severity: “3”, showing only events that matched an alarm rule.

In this case, several alarms were generated for suspicious Base64 arguments being passed to Selenium. Examining the event data, it appears the attacker spawned a Selenium Grid session with the following payload:

"request.payload": "[Capabilities {browserName: chrome, goog:chromeOptions: {args: [-cimport base64;exec(base64...], binary: /usr/bin/python3, extensions: []}, pageLoadStrategy: normal}]"

This is a common attack vector for Selenium Grid. The chromeOptions object is intended to specify arguments for how Google Chrome should be launched; however, in this case the attacker has abused the binary field to execute the Python3 binary instead of Chrome. Combined with the option to specify command-line arguments, the attacker can use Python3’s -c option to execute arbitrary Python code, in this instance, decoding and executing a Base64 payload.

Selenium’s logs truncate the Arguments field automatically, so an alternate method is required to retrieve the full payload. To do this, the search bar can be used to find all events that occurred around the same time as this flagged event.

Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].
Figure 5: Pivoting off the previous event by filtering the timeline to events within the same window using timestamp: [“2026-02-18T09:09:00Z” TO “2026-02-18T09:12:00Z”].

Scrolling through the search results, an entry from Java’s systemd journal can be identified. This log contains the full, unaltered payload. GCHQ’s CyberChef can then be used to decode the Base64 data into the attacker’s script, which will ultimately be executed.[NJ9]

Decoding the attacker’s payload in CyberChef.
Figure 6: Decoding the attacker’s payload in CyberChef.

In this instance, the malware was identified as a variant of a campaign that has been previously documented in depth by Darktrace.

Investigating Perfectl Malware

This campaign deploys a malware sample known as ‘perfctl to the compromised host. The script executed by the attacker downloads a Go binary named “promocioni.php” from 200[.]4.115.1. Its functionality is consistent with previously documented perfctl samples, with only minor changes such as updated filenames and a new command-and-control (C2) domain.

Perctl is a stealthy malware that has several systems designed  to evade detection. The main binary is packed with UPX, with the header intentionally tampered with to prevent unpacking using regular tools. The binary also avoids executing any malicious code if it detects debugging or tracing activity, or if artifacts left by earlier stages are missing.

To further aid its evasive capabilities, perfctl features a usermode rootkit using an LD preload. This causes dynamically linked executables to load perfctl’s rootkit payload before other system modules, allowing it to override functions, such as intercepting calls to list files and hiding output from the returned list. Perctl uses this to hide its own files, as well as other files like the ld.so.preload file, preventing users from identifying that a rootkit is present in the first place.

This also makes it difficult to dynamically analyze, as even analysts aware of the rootkit will struggle to get around it due to its aggressiveness in hiding its components. A useful trick is to use the busybox-static utilities, which are statically linked and therefore immune to LD preloading.

Perctl will attempt to use sudo to escalate its permissions to root if the user it was executed as has the required privileges. Failing this, it will attempt to exploit the vulnerability CVE-2021-4034.

Ultimately, perfctl will attempt to establish a C2 link via Tor and spawn an XMRig miner to mine the Monero cryptocurrency. The traffic to the mining pool is encapsulated within Tor to limit network detection of the mining traffic.

Darktrace’s Cloudypots system has observed 1,959 infections of the perfectl campaign across its honeypot network in the past year, making it one of the most aggressive campaigns seen by Darktrace.

Key takeaways

This blog has shown how Darktrace / Forensic Acquisition & Investigation equips defenders in the face of a real-world attacker campaign. By using this solution, organizations can acquire forensic evidence and investigate intrusions across multiple cloud resources and providers, enabling defenders to see the full picture of an intrusion on day one. Forensic Acquisition & Investigation’s patented data-processing system takes advantage of the cloud’s scale to rapidly process large amounts of data, allowing triage to take minutes, not hours.

Darktrace / Forensic Acquisition & Investigation is available as Software-as-a-Service (SaaS) but can also be deployed on-premises as a virtual application or natively in the cloud, providing flexibility between convenience and data sovereignty to suit any use case.

Support for acquiring traditional compute instances like EC2, as well as more exotic and newly targeted platforms such as ECS and Lambda, ensures that attacks taking advantage of Living-off-the-Cloud (LOTC) strategies can be triaged quickly and easily as part of incident response. As attackers continue to develop new techniques, the ability to investigate how they use cloud services to persist and pivot throughout an environment is just as important to triage as a single compromised EC2 instance.

Credit to Nathaniel Bill (Malware Research Engineer)

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Nathaniel Bill
Malware Research Engineer

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February 19, 2026

CVE-2026-1731: How Darktrace Sees the BeyondTrust Exploitation Wave Unfolding

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Note: Darktrace's Threat Research team is publishing now to help defenders. We will continue updating this blog as our investigations unfold.

Background

On February 6, 2026, the Identity & Access Management solution BeyondTrust announced patches for a vulnerability, CVE-2026-1731, which enables unauthenticated remote code execution using specially crafted requests.  This vulnerability affects BeyondTrust Remote Support (RS) and particular older versions of Privileged Remote Access (PRA) [1].

A Proof of Concept (PoC) exploit for this vulnerability was released publicly on February 10, and open-source intelligence (OSINT) reported exploitation attempts within 24 hours [2].

Previous intrusions against Beyond Trust technology have been cited as being affiliated with nation-state attacks, including a 2024 breach targeting the U.S. Treasury Department. This incident led to subsequent emergency directives from  the Cybersecurity and Infrastructure Security Agency (CISA) and later showed attackers had chained previously unknown vulnerabilities to achieve their goals [3].

Additionally, there appears to be infrastructure overlap with React2Shell mass exploitation previously observed by Darktrace, with command-and-control (C2) domain  avg.domaininfo[.]top seen in potential post-exploitation activity for BeyondTrust, as well as in a React2Shell exploitation case involving possible EtherRAT deployment.

Darktrace Detections

Darktrace’s Threat Research team has identified highly anomalous activity across several customers that may relate to exploitation of BeyondTrust since February 10, 2026. Observed activities include:

Outbound connections and DNS requests for endpoints associated with Out-of-Band Application Security Testing; these services are commonly abused by threat actors for exploit validation.  Associated Darktrace models include:

  • Compromise / Possible Tunnelling to Bin Services

Suspicious executable file downloads. Associated Darktrace models include:

  • Anomalous File / EXE from Rare External Location

Outbound beaconing to rare domains. Associated Darktrace models include:

  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Agent Beacon (Long Period)
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Beacon to Young Endpoint
  • Anomalous Server Activity / Rare External from Server
  • Compromise / SSL Beaconing to Rare Destination

Unusual cryptocurrency mining activity. Associated Darktrace models include:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining

And model alerts for:

  • Compromise / Rare Domain Pointing to Internal IP

IT Defenders: As part of best practices, we highly recommend employing an automated containment solution in your environment. For Darktrace customers, please ensure that Autonomous Response is configured correctly. More guidance regarding this activity and suggested actions can be found in the Darktrace Customer Portal.  

Appendices

Potential indicators of post-exploitation behavior:

·      217.76.57[.]78 – IP address - Likely C2 server

·      hXXp://217.76.57[.]78:8009/index.js - URL -  Likely payload

·      b6a15e1f2f3e1f651a5ad4a18ce39d411d385ac7  - SHA1 - Likely payload

·      195.154.119[.]194 – IP address – Likely C2 server

·      hXXp://195.154.119[.]194/index.js - URL – Likely payload

·      avg.domaininfo[.]top – Hostname – Likely C2 server

·      104.234.174[.]5 – IP address - Possible C2 server

·      35da45aeca4701764eb49185b11ef23432f7162a – SHA1 – Possible payload

·      hXXp://134.122.13[.]34:8979/c - URL – Possible payload

·      134.122.13[.]34 – IP address – Possible C2 server

·      28df16894a6732919c650cc5a3de94e434a81d80 - SHA1 - Possible payload

References:

1.        https://nvd.nist.gov/vuln/detail/CVE-2026-1731

2.        https://www.securityweek.com/beyondtrust-vulnerability-targeted-by-hackers-within-24-hours-of-poc-release/

3.        https://www.rapid7.com/blog/post/etr-cve-2026-1731-critical-unauthenticated-remote-code-execution-rce-beyondtrust-remote-support-rs-privileged-remote-access-pra/

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About the author
Emma Foulger
Global Threat Research Operations Lead
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