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October 3, 2024

Introducing Real-Time Multi-Cloud Detection & Response Powered by AI

This blog announces the general availability of Microsoft Azure support for Darktrace / CLOUD, enabling real-time cloud detection and response across dynamic multi-cloud environments. Read more to discover how Darktrace is pioneering AI-led real-time cloud detection and response.
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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03
Oct 2024

We are delighted to announce the general availability of Microsoft Azure support for Darktrace / CLOUD, enabling real-time cloud detection and response across dynamic multi-cloud environments. Built on Self-Learning AI, Darktrace / CLOUD leverages Microsoft’s new virtual network flow logs (VNet flow) to offer an agentless-first approach that dramatically simplifies detection and response within Azure, unifying cloud-native security with Darktrace’s innovative ActiveAI Security Platform.

As organizations increasingly adopt multi-cloud architectures, the need for advanced, real-time threat detection and response is critical to keep pace with evolving cloud threats. Security teams face significant challenges, including increased complexity, limited visibility, and siloed tools. The dynamic nature of multi-cloud environments introduces ever-changing blind spots, while traditional security tools struggle to provide real-time insights, often offering static snapshots of risk. Additionally, cloud security teams frequently operate in isolation from SOC teams, leading to fragmented visibility and delayed responses. This lack of coordination, especially in hybrid environments, hinders effective threat detection and response. Compounding these challenges, current security solutions are split between agent-based and agentless approaches, with agentless solutions often lacking real-time awareness and agent-based options adding complexity and scalability concerns. Darktrace / CLOUD helps to solve these challenges with real-time detection and response designed specifically for dynamic cloud environments like Azure and AWS.

Pioneering AI-led real-time cloud detection & response

Darktrace has been at the forefront of real-time detection and response for over a decade, continually pushing the boundaries of AI-driven cybersecurity. Our Self-Learning AI uniquely positions Darktrace with the ability to automatically understand and instantly adapt to changing cloud environments. This is critical in today’s landscape, where cloud infrastructures are highly dynamic and ever-changing.  

Built on years of market-leading network visibility, Darktrace / CLOUD understands ‘normal’ for your unique business across clouds and networks to instantly reveal known, unknown, and novel cloud threats with confidence. Darktrace Self-Learning AI continuously monitors activity across cloud assets, containers, and users, and correlates it with detailed identity and network context to rapidly detect malicious activity. Platform-native identity and network monitoring capabilities allow Darktrace / CLOUD to deeply understand normal patterns of life for every user and device, enabling instant, precise and proportionate response to abnormal behavior - without business disruption.

Leveraging platform-native Autonomous Response, AI-driven behavioral containment neutralizes malicious activity with surgical accuracy while preventing disruption to cloud infrastructure or services. As malicious behavior escalates, Darktrace correlates thousands of data points to identify and instantly respond to unusual activity by blocking specific connections and enforcing normal behavior.

Figure 1: AI-driven behavioral containment neutralizes malicious activity with surgical accuracy while preventing disruption to cloud infrastructure or services.

Unparalleled agentless visibility into Azure

As a long-term trusted partner of Microsoft, Darktrace leverages Azure VNet flow logs to provide agentless, high-fidelity visibility into cloud environments, ensuring comprehensive monitoring without disrupting workflows. By integrating seamlessly with Azure, Darktrace / CLOUD continues to push the envelope of innovation in cloud security. Our Self-learning AI not only improves the detection of traditional and novel threats, but also enhances real-time response capabilities and demonstrates our commitment to delivering cutting-edge, AI-powered multi-cloud security solutions.

  • Integration with Microsoft Virtual network flow logs for enhanced visibility
    Darktrace / CLOUD integrates seamlessly with Azure to provide agentless, high-fidelity visibility into cloud environments. VNet flow logs capture critical network traffic data, allowing Darktrace to monitor Azure workloads in real time without disrupting existing workflows. This integration significantly reduces deployment time by 95%1 and cloud security operational costs by up to 80%2 compared to traditional agent-based solutions. Organizations benefit from enhanced visibility across dynamic cloud infrastructures, scaling security measures effortlessly while minimizing blind spots, particularly in ephemeral resources or serverless functions.
  • High-fidelity agentless deployment
    Agentless deployment allows security teams to monitor and secure cloud environments without installing software agents on individual workloads. By using cloud-native APIs like AWS VPC flow logs or Azure VNet flow logs, security teams can quickly deploy and scale security measures across dynamic, multi-cloud environments without the complexity and performance overhead of agents. This approach delivers real-time insights, improving incident detection and response while reducing disruptions. For organizations, agentless visibility simplifies cloud security management, lowers operational costs, and minimizes blind spots, especially in ephemeral resources or serverless functions.
  • Real-time visibility into cloud assets and architectures
    With real-time Cloud Asset Enumeration and Dynamic Architecture Modeling, Darktrace / CLOUD generates up-to-date architecture diagrams, giving SecOps and DevOps teams a unified view of cloud infrastructures. This shared context enhances collaboration and accelerates threat detection and response, especially in complex environments like Kubernetes. Additionally, Cyber AI Analyst automates the investigation process, correlating data across networks, identities, and cloud assets to save security teams valuable time, ensuring continuous protection and efficient cloud migrations.
Figure 2: Real-time visibility into Azure assets and architectures built from network, configuration and identity and access roles.

Unified multi-cloud security at scale

As organizations increasingly adopt multi-cloud strategies, the complexity of managing security across different cloud providers introduces gaps in visibility. Darktrace / CLOUD simplifies this by offering agentless, real-time monitoring across multi-cloud environments. Building on our innovative approach to securing AWS environments, our customers can now take full advantage of robust real-time detection and response capabilities for Azure. Darktrace is one of the first vendors to leverage Microsoft’s virtual network flow logs to provide agentless deployment in Azure, enabling unparalleled visibility without the need for installing agents. In addition, Darktrace / CLOUD offers automated Cloud Security Posture Management (CSPM) that continuously assesses cloud configurations against industry standards.  Security teams can identify and prioritize misconfigurations, vulnerabilities, and policy violations in real-time. These capabilities give security teams a complete, live understanding of their cloud environments and help them focus their limited time and resources where they are needed most.

This approach offers seamless integration into existing workflows, reducing configuration efforts and enabling fast, flexible deployment across cloud environments. By extending its capabilities across multiple clouds, Darktrace / CLOUD ensures that no blind spots are left uncovered, providing holistic, multi-cloud security that scales effortlessly with your cloud infrastructure. diagrams, visualizes cloud assets, and prioritizes risks across cloud environments.

Figure 3: Unified view of AWS and Azure cloud posture and compliance over time.

The future of cloud security: Real-time defense in an unpredictable world

Darktrace / CLOUD’s support for Microsoft Azure, powered by Self-Learning AI and agentless deployment, sets a new standard in multi-cloud security. With real-time detection and autonomous response, organizations can confidently secure their Azure environments, leveraging innovation to stay ahead of the constantly evolving threat landscape. By combining Azure VNet flow logs with Darktrace’s AI-driven platform, we can provide customers with a unified, intelligent solution that transforms how security is managed across the cloud.

Unlock advanced cloud protection

Darktrace / CLOUD solution brief screenshot

Download the Darktrace / CLOUD solution brief to discover how autonomous, AI-driven defense can secure your environment in real-time.

  • Achieve 60% more accurate detection of unknown and novel cloud threats.
  • Respond instantly with autonomous threat response, cutting response time by 90%.
  • Streamline investigations with automated analysis, improving ROI by 85%.
  • Gain a 30% boost in cloud asset visibility with real-time architecture modeling.
  • Learn More:

    References

    1. Based on internal research and customer data

    2. Based on internal research

    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 11, 2026

    NetSupport RAT: How Legitimate Tools Can Be as Damaging as Malware

    NetSupport RAT: How Legitimate Tools Can Be as Damaging as MalwareDefault blog imageDefault blog image

    What is NetSupport Manager?

    NetSupport Manager is a legitimate IT tool used by system administrators for remote support, monitoring, and management. In use since 1989, NetSupport Manager enables users to remotely access and navigate systems across different platforms and operating systems [1].

    What is NetSupport RAT?

    Although NetSupport Manager is a legitimate tool that can be used by IT and security professionals, there has been a rising number of cases in which it is abused to gain unauthorized access to victim systems. This misuse has become so prevalent that, in recent years, security researchers have begun referring to NetSupport as a Remote Access Trojan (RAT), a term typically used for malware that enables a threat actor to remotely access or control an infected device [2][3][4].

    NetSupport RAT activity summary

    The initial stages of NetSupport RAT infection may vary depending on the source of the initial compromise. Using tactics such as the social engineering tactic ClickFix, threat actors attempt to trick users into inadvertently executing malicious PowerShell commands under the guise of resolving a non-existent issue or completing a fake CAPTCHA verification [5]. Other attack vectors such as phishing emails, fake browser updates, malicious websites, search engine optimization (SEO) poisoning, malvertising and drive-by downloads are also employed to direct users to fraudulent pages and fake reCAPTCHA verification checks, ultimately inducing them to execute malicious PowerShell commands [5][6][7]. This leads to the successful installation of NetSupport Manager on the compromised device, which is often placed in non-standard directories such as AppData, ProgramData, or Downloads [3][8].

    Once installed, the adversary is able to gain remote access to the affected machine, monitor user activity, exfiltrate data, communicate with the command-and-control (C2) server, and maintain persistence [5]. External research has also highlighted that post-exploitation of NetSupport RAT has involved the additional download of malicious payloads [2][5].

    Attack flow diagram highlighting key events across each phase of the attack phase
    Figure 1: Attack flow diagram highlighting key events across each phase of the attack phase [2][5].

    Darktrace coverage

    In November of 2025, suspicious behavior indicative of the malicious abuse of NetSupport Manager was observed on multiple customers across Europe, the Middle East, and Africa (EMEA) and the Americas (AMS).

    While open-source intelligence (OSINT) has reported that, in a recent campaign, a threat actor impersonated government entities to trick users in organizations in the Information Technology, Government and Financial Services sectors in Central Asia into downloading NetSupport Manager [8], approximately a third of Darktrace’s affected customers in November were based in the US while the rest were based in EMEA. This contrast underscores how widely NetSupport Manager is leveraged by threat actors and highlights its accessibility as an initial access tool.  

    The Darktrace customers affected were in sectors including Information and Communication, Manufacturing and Arts, entertainment and recreation.

    The ClickFix social engineering tactic typically used to distribute the NetSupport RAT is known to target multiple industries, including Technology, Manufacturing and Energy sectors [9]. It also reflects activity observed in the campaign targeting Central Asia, where the Information Technology sector was among those affected [8].

    The prevalence of affected Education customers highlights NetSupport’s marketing focus on the Education sector [10]. This suggests that threat actors are also aware of this marketing strategy and have exploited the trust it creates to deploy NetSupport Manager and gain access to their targets’ systems. While the execution of the PowerShell commands that led to the installation of NetSupport Manager falls outside of Darktrace's purview in cases identified, Darktrace was still able to identify a pattern of devices making connections to multiple rare external domains and IP addresses associated with the NetSupport RAT, using a wide range of ports over the HTTP protocol. A full list of associated domains and IP addresses is provided in the Appendices of this blog.

    Although OSINT identifies multiple malicious domains and IP addresses as used as C2 servers, signature-based detections of NetSupport RAT indicators of compromise (IoCs) may miss broader activity, as new malicious websites linked to the RAT continue to appear.

    Darktrace’s anomaly‑based approach allows it to establish a normal ‘pattern of life’ for each device on a network and identify when behavior deviates from this baseline, enabling the detection of unusual activity even when it does not match known IoCs or tactics, techniques and procedures (TTPs).

    In one customer environment in late 2025, Darktrace / NETWORK detected a device initiating new connections to the rare external endpoint, thetavaluemetrics[.]com (74.91.125[.]57), along with the use of a previously unseen user agent, which it recognized as highly unusual for the network.

    Darktrace’s detection of HTTP POST requests to a suspicious URI and new user agent usage.
    Figure 2: Darktrace’s detection of HTTP POST requests to a suspicious URI and new user agent usage.

    Darktrace identified that user agent present in connections to this endpoint was the ‘NetSupport Manager/1.3’, initially suggesting legitimate NetSupport Manager activity. Subsequent investigation, however, revealed that the endpoint was in fact a malicious NetSupportRAT C2 endpoint [12]. Shortly after, Darktrace detected the same device performing HTTP POST requests to the URI fakeurl[.]htm. This pattern of activity is consistent with OSINT reporting that details communication between compromised devices and NetSupport Connectivity Gateways functioning as C2 servers [11].

    Conclusion

    As seen not only with NetSupport Manager but with any legitimate or open‑source software used by IT and security professionals, the legitimacy of a tool does not prevent it from being abused by threat actors. Open‑source software, especially tools with free or trial versions such as NetSupport Manager, remains readily accessible for malicious use, including network compromise. In an age where remote work is still prevalent, validating any anomalous use of software and remote management tools is essential to reducing opportunities for unauthorized access.

    Darktrace’s anomaly‑based detection enables security teams to identify malicious use of legitimate tools, even when clear signatures or indicators of compromise are absent, helping to prevent further impact on a network.


    Credit to George Kim (Analyst Consulting Lead – AMS), Anna Gilbertson (Senior Cyber Analyst)

    Edited by Ryan Traill (Analyst Content Lead)

    Appendices

    Darktrace Model Alerts

    ·       Compromise / Suspicious HTTP and Anomalous Activity

    ·       Compromise / New User Agent and POST

    ·       Device / New User Agent

    ·       Anomalous Connection / New User Agent to IP Without Hostname

    ·       Anomalous Connection / Posting HTTP to IP Without Hostname

    ·       Anomalous Connection / Multiple Failed Connections to Rare Endpoint

    ·       Anomalous Connection / Application Protocol on Uncommon Port

    ·       Anomalous Connection / Multiple HTTP POSTs to Rare Hostname

    ·       Compromise / Beaconing Activity To External Rare

    ·       Compromise / HTTP Beaconing to Rare Destination

    ·       Compromise / Agent Beacon (Medium Period)

    ·       Compromise / Agent Beacon (Long Period)

    ·       Compromise / Quick and Regular Windows HTTP Beaconing

    ·       Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

    ·       Compromise / POST and Beacon to Rare External

    Indicators of Compromise (IoCs)

    Indicator           Type     Description

    /fakeurl.htm URI            NetSupportRAT C2 URI

    thetavaluemetrics[.]com        Connection hostname              NetSupportRAT C2 Endpoint

    westford-systems[.]icu            Connection hostname              NetSupportRAT C2 Endpoint

    holonisz[.]com                Connection hostname              NetSupportRAT C2 Endpoint

    heaveydutyl[.]com      Connection hostname              NetSupportRAT C2 Endpoint

    nsgatetest1[.]digital   Connection hostname              NetSupportRAT C2 Endpoint

    finalnovel[.]com            Connection hostname              NetSupportRAT C2 Endpoint

    217.91.235[.]17              IP             NetSupportRAT C2 Endpoint

    45.94.47[.]224                 IP             NetSupportRAT C2 Endpoint

    74.91.125[.]57                 IP             NetSupportRAT C2 Endpoint

    88.214.27[.]48                 IP             NetSupportRAT C2 Endpoint

    104.21.40[.]75                 IP             NetSupportRAT C2 Endpoint

    38.146.28[.]242              IP             NetSupportRAT C2 Endpoint

    185.39.19[.]233              IP             NetSupportRAT C2 Endpoint

    45.88.79[.]237                 IP             NetSupportRAT C2 Endpoint

    141.98.11[.]224              IP             NetSupportRAT C2 Endpoint

    88.214.27[.]166              IP             NetSupportRAT C2 Endpoint

    107.158.128[.]84          IP             NetSupportRAT C2 Endpoint

    87.120.93[.]98                 IP             Rhadamanthys C2 Endpoint

    References

    1. https://mspalliance.com/netsupport-debuts-netsupport-24-7/
    2. https://blogs.vmware.com/security/2023/11/netsupport-rat-the-rat-king-returns.html
    3. https://redcanary.com/threat-detection-report/threats/netsupport-manager/
    4. https://www.elastic.co/guide/en/security/8.19/netsupport-manager-execution-from-an-unusual-path.html
    5. https://rewterz.com/threat-advisory/netsupport-rat-delivered-through-spoofed-verification-pages-active-iocs
    6. https://thehackernews.com/2025/11/new-evalusion-clickfix-campaign.html
    7. https://corelight.com/blog/detecting-netsupport-manager-abuse
    8. https://thehackernews.com/2025/11/bloody-wolf-expands-java-based.html
    9. https://unit42.paloaltonetworks.com/preventing-clickfix-attack-vector
    10. https://www.netsupportsoftware.com/education-solutions
    11. https://www.esentire.com/blog/unpacking-netsupport-rat-loaders-delivered-via-clickfix
    12. https://threatfox.abuse.ch/browse/malware/win.netsupportmanager_rat/
    13. https://www.virustotal.com/gui/url/5fe6936a69c786c9ded9f31ed1242c601cd64e1d90cecd8a7bb03182c47906c2

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    About the author
    George Kim
    Analyst Consulting Lead – AMS

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    March 5, 2026

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

    Forensic Acquisition and investigationDefault blog imageDefault blog image

    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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    About the author
    Nathaniel Bill
    Malware Research Engineer
    Your data. Our AI.
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