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September 25, 2025

Announcing Unified Real-Time CDR and Automated Investigations to Transform Cloud Security Operations

Following the announcement of Darktrace / Forensic Acquisition & Investigation, we’re excited to share how Darktrace / CLOUD is evolving to deliver a truly unified approach to cloud security. For the first time, security teams can detect novel cloud threats in real time, automatically investigate them with forensic depth, and respond decisively — all within a single solution built for hybrid and multi-cloud environments.
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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25
Sep 2025

Fragmented Tools are Failing SOC Teams in the Cloud Era

The cloud has transformed how businesses operate, reshaping everything from infrastructure to application delivery. But cloud security has not kept pace. Most tools still rely on traditional models of logging, policy enforcement, and posture management; approaches that provide surface-level visibility but lack the depth to detect or investigate active attacks.

Meanwhile, attackers are exploiting vulnerabilities, delivering cloud-native exploits, and moving laterally in ways that posture management alone cannot catch fast enough. Critical evidence is often missed, and alerts lack the forensic depth SOC analysts need to separate noise from true risk. As a result, organizations remain exposed: research shows that nearly nine in ten organizations have suffered a critical cloud breach despite investing in existing security tools [1].

SOC teams are left buried in alerts without actionable context, while ephemeral workloads like containers and serverless functions vanish before evidence can be preserved. Point tools for logging or forensics only add complexity, with 82% of organizations using multiple platforms to investigate cloud incidents [2].

The result is a broken security model: posture tools surface risks but don’t connect them to active attacker behaviors, while investigation tools are too slow and fragmented to provide timely clarity. Security teams are left reactive, juggling multiple point solutions and still missing critical signals. What’s needed is a unified approach that combines real-time detection and response for active threats with automated investigation and cloud posture management in a single workflow.

Just as security teams once had to evolve beyond basic firewalls and antivirus into network and endpoint detection, response, and forensics, cloud security now requires its own next era: one that unifies detection, response, and investigation at the speed and scale of the cloud.

A Powerful Combination: Real-Time CDR + Automated Cloud Forensics

Darktrace / CLOUD now uniquely unites detection, investigation, and response into one workflow, powered by Self-Learning AI. This means every alert, from any tool in your stack, can instantly become actionable evidence and a complete investigation in minutes.

With this release, Darktrace / CLOUD delivers a more holistic approach to cloud defense, uniting real-time detection, response, and investigation with proactive risk reduction. The result is a single solution that helps security teams stay ahead of attackers while reducing complexity and blind spots.

  • Automated Cloud Forensic Investigations: Instantly capture and analyze volatile evidence from cloud assets, reducing investigation times from days to minutes and eliminating blind spots
  • Enhanced Cloud-Native Threat Detection: Detect advanced attacker behaviors such as lateral movement, privilege escalation, and command-and-control in real time
  • Enhanced Live Cloud Topology Mapping: Gain continuous insight into cloud environments, including ephemeral workloads, with live topology views that simplify investigations and expose anomalous activity
  • Agentless Scanning for Proactive Risk Reduction: Continuously monitor for misconfigurations, vulnerabilities, and risky exposures to reduce attack surface and stop threats before they escalate.

Automated Cloud Forensic Investigations

Darktrace / CLOUD now includes capabilities introduced with Darktrace / Forensic Acquisition & Investigation, triggering automated forensic acquisition the moment a threat is detected. This ensures ephemeral evidence, from disks and memory to containers and serverless workloads can be preserved instantly and analyzed in minutes, not days. The integration unites detection, response, and forensic investigation in a way that eliminates blind spots and reduces manual effort.

Figure 1: Easily view Forensic Investigation of a cloud resource within the Darktrace / CLOUD architecture map

Enhanced Cloud-Native Threat Detection

Darktrace / CLOUD strengthens its real-time behavioral detection to expose early attacker behaviors that logs alone cannot reveal. Enhanced cloud-native detection capabilities include:

• Reconnaissance & Discovery – Detects enumeration and probing activity post-compromise.

• Privilege Escalation via Role Assumption – Identifies suspicious attempts to gain elevated access.

• Malicious Compute Resource Usage – Flags threats such as crypto mining or spam operations.

These enhancements ensure active attacks are detected earlier, before adversaries can escalate or move laterally through cloud environments.

Figure 2: Cyber AI Analyst summary of anomalous behavior for privilege escalation and establishing persistence.

Enhanced Live Cloud Topology Mapping

New enhancements to live topology provide real-time mapping of cloud environments, attacker movement, and anomalous behavior. This dynamic visibility helps SOC teams quickly understand complex environments, trace attack paths, and prioritize response. By integrating with Darktrace / Proactive Exposure Management (PEM), these insights extend beyond the cloud, offering a unified view of risks across networks, endpoints, SaaS, and identity — giving teams the context needed to act with confidence.

Figure 3: Enhanced live topology maps unify visibility across architectures, identities, network connections and more.

Agentless Scanning for Proactive Risk Reduction

Darktrace / CLOUD now introduces agentless scanning to uncover malware and vulnerabilities in cloud assets without impacting performance. This lightweight, non-disruptive approach provides deep visibility into cloud workloads and surfaces risks before attackers can exploit them. By continuously monitoring for misconfigurations and exposures, the solution strengthens posture management and reduces attack surface across hybrid and multi-cloud environments.

Figure 4: Agentless scanning of cloud assets reveals vulnerabilities, which are prioritized by severity.

Together, these capabilities move cloud security operations from reactive to proactive, empowering security teams to detect novel threats in real time, reduce exposures before they are exploited, and accelerate investigations with forensic depth. The result is faster triage, shorter MTTR, and reduced business risk — all delivered in a single, AI-native solution built for hybrid and multi-cloud environments.

Accelerating the Evolution of Cloud Security

Cloud security has long been fragmented, forcing teams to stitch together posture tools, log-based monitoring, and external forensics to get even partial coverage. With this release, Darktrace / CLOUD delivers a holistic, unified approach that covers every stage of the cloud lifecycle, from proactive posture management and risk identification to real-time detection, to automated investigation and response.

By bringing these capabilities together in a single AI-native solution, Darktrace is advancing cloud security beyond incremental change and setting a new standard for how organizations protect their hybrid and multi-cloud environments.

With Darktrace / CLOUD, security teams finally gain end-to-end visibility, response, and investigation at the speed of the cloud, transforming cloud defense from fragmented and reactive to unified and proactive.

[related-resource]

Sources: [1], [2] Darktrace Report: Organizations Require a New Approach to Handle Investigations in the Cloud

Darktrace Innovation Launch: Automated Cloud Forensics

Discover the industry's first truly automated cloud forensics solution in this live broadcast with experts from AWS and Forrester.

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 rule  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.

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 Perfctl 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.

Perfctl 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. Perfctl 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.

Perfctl 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 perfctl 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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