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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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    October 15, 2025

    How a Major Civil Engineering Company Reduced MTTR across Network, Email and the Cloud with Darktrace

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    Asking more of the information security team

    “What more can we be doing to secure the company?” is a great question for any cyber professional to hear from their Board of Directors. After successfully defeating a series of attacks and seeing the potential for AI tools to supercharge incoming threats, a UK-based civil engineering company’s security team had the answer: Darktrace.

    “When things are coming at you at machine speed, you need machine speed to fight it off – it’s as simple as that,” said their Information Security Manager. “There were incidents where it took us a few hours to get to the bottom of what was going on. Darktrace changed that.”

    Prevention was also the best cure. A peer organization in the same sector was still in business continuity measures 18 months after an attack, and the security team did not want to risk that level of business disruption.

    Legacy tools were not meeting the team’s desired speed or accuracy

    The company’s native SaaS email platform took between two and 14 days to alert on suspicious emails, with another email security tool flagging malicious emails after up to 24 days. After receiving an alert, responses often took a couple of days to coordinate. The team was losing precious time.

    Beyond long detection and response times, the old email security platform was no longer performing: 19% of incoming spam was missed. Of even more concern: 6% of phishing emails reached users’ inboxes, and malware and ransomware email was also still getting through, with 0.3% of such email-borne payloads reaching user inboxes.

    Choosing Darktrace

    “When evaluating tools in 2023, only Darktrace had what I was looking for: an existing, mature, AI-based cybersecurity solution. ChatGPT had just come out and a lot of companies were saying ‘AI this’ and ‘AI that’. Then you’d take a look, and it was all rules- and cases-based, not AI at all,” their Information Security Manager.

    The team knew that, with AI-enabled attacks on the horizon, a cybersecurity company that had already built, fielded, and matured an AI-powered cyber defense would give the security team the ability to fend off machine-speed attacks at the same pace as the attackers.

    Darktrace accomplishes this with multi-layered AI that learns each organization’s normal business operations. With this detailed level of understanding, Darktrace’s Self-Learning AI can recognize unusual activity that may indicate a cyber-attack, and works to neutralize the threat with precise response actions. And it does this all at machine speed and with minimal disruption.

    On the morning the team was due to present its findings, the session was cancelled – for a good reason. The Board didn’t feel further discussion was necessary because the case for Darktrace was so conclusive. The CEO described the Darktrace option as ‘an insurance policy we can’t do without’.

    Saving time with Darktrace / EMAIL

    Darktrace / EMAIL reduced the discovery, alert, and response process from days or weeks to seconds .

    Darktrace / EMAIL automates what was originally a time-consuming and repetitive process. The team has recovered between eight and 10 working hours a week by automating much of this process using / EMAIL.

    Today, Darktrace / EMAIL prevents phishing emails from reaching employees’ inboxes. The volume of hostile and unsolicited email fell to a third of its original level after Darktrace / EMAIL was set up.

    Further savings with Darktrace / NETWORK and Darktrace / IDENTITY

    Since its success with Darktrace / EMAIL, the company adopted two more products from the Darktrace ActiveAI Security Platform – Darktrace / NETWORK and Darktrace / IDENTITY.

    These have further contributed to cost savings. An initial plan to build a 24/7 SOC would have required hiring and retaining six additional analysts, rather than the two that currently use Darktrace, costing an additional £220,000 per year in salary. With Darktrace, the existing analysts have the tools needed to become more effective and impactful.

    An additional benefit: Darktrace adoption has lowered the company’s cyber insurance premiums. The security team can reallocate this budget to proactive projects.

    Detection of novel threats provides reassurance

    Darktrace’s unique approach to cybersecurity added a key benefit. The team’s previous tool took a rules-based approach – which was only good if the next attack featured the same characteristics as the ones on which the tool was trained.

    “Darktrace looks for anomalous behavior, and we needed something that detected and responded based on use cases, not rules that might be out of date or too prescriptive,” their Information Security Manager. “Our existing provider could take a couple of days to update rules and signatures, and in this game, speed is of the essence. Darktrace just does everything we need - without delay.”

    Where rules-based tools must wait for a threat to emerge before beginning to detect and respond to it, Darktrace identifies and protects against unknown and novel threats, speeding identification, response, and recovery, minimizing business disruption as a result.

    Looking to the future

    With Darktrace in place, the UK-based civil engineering company team has reallocated time and resources usually spent on detection and alerting to now tackle more sophisticated, strategic challenges. Darktrace has also equipped the team with far better and more regularly updated visibility into potential vulnerabilities.

    “One thing that frustrates me a little is penetration testing; our ISO accreditation mandates a penetration test at least once a year, but the results could be out of date the next day,” their Information Security Manager. “Darktrace / Proactive Exposure Management will give me that view in real time – we can run it daily if needed - and that’s going to be a really effective workbench for my team.”

    As the company looks to further develop its security posture, Darktrace remains poised to evolve alongside its partner.

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    October 14, 2025

    Inside Akira’s SonicWall Campaign: Darktrace’s Detection and Response

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    Introduction: Background on Akira SonicWall campaign

    Between July and August 2025, security teams worldwide observed a surge in Akira ransomware incidents involving SonicWall SSL VPN devices [1]. Initially believed to be the result of an unknown zero-day vulnerability, SonicWall later released an advisory announcing that the activity was strongly linked to a previously disclosed vulnerability, CVE-2024-40766, first identified over a year earlier [2].

    On August 20, 2025, Darktrace observed unusual activity on the network of a customer in the US. Darktrace detected a range of suspicious activity, including network scanning and reconnaissance, lateral movement, privilege escalation, and data exfiltration. One of the compromised devices was later identified as a SonicWall virtual private network (VPN) server, suggesting that the incident was part of the broader Akira ransomware campaign targeting SonicWall technology.

    As the customer was subscribed to the Managed Detection and Response (MDR) service, Darktrace’s Security Operations Centre (SOC) team was able to rapidly triage critical alerts, restrict the activity of affected devices, and notify the customer of the threat. As a result, the impact of the attack was limited - approximately 2 GiB of data had been observed leaving the network, but any further escalation of malicious activity was stopped.

    Threat Overview

    CVE-2024-40766 and other misconfigurations

    CVE-2024-40766 is an improper access control vulnerability in SonicWall’s SonicOS, affecting Gen 5, Gen 6, and Gen 7 devices running SonicOS version 7.0.1 5035 and earlier [3]. The vulnerability was disclosed on August 23, 2024, with a patch released the same day. Shortly after, it was reported to be exploited in the wild by Akira ransomware affiliates and others [4].

    Almost a year later, the same vulnerability is being actively targeted again by the Akira ransomware group. In addition to exploiting unpatched devices affected by CVE-2024-40766, security researchers have identified three other risks potentially being leveraged by the group [5]:

    *The Virtual Office Portal can be used to initially set up MFA/TOTP configurations for SSLVPN users.

    Thus, even if SonicWall devices were patched, threat actors could still target them for initial access by reusing previously stolen credentials and exploiting other misconfigurations.

    Akira Ransomware

    Akira ransomware was first observed in the wild in March 2023 and has since become one of the most prolific ransomware strains across the threat landscape [6]. The group operates under a Ransomware-as-a-Service (RaaS) model and frequently uses double extortion tactics, pressuring victims to pay not only to decrypt files but also to prevent the public release of sensitive exfiltrated data.

    The ransomware initially targeted Windows systems, but a Linux variant was later observed targeting VMware ESXi virtual machines [7]. In 2024, it was assessed that Akira would continue to target ESXi hypervisors, making attacks highly disruptive due to the central role of virtualisation in large-scale cloud deployments. Encrypting the ESXi file system enables rapid and widespread encryption with minimal lateral movement or credential theft. The lack of comprehensive security protections on many ESXi hypervisors also makes them an attractive target for ransomware operators [8].

    Victimology

    Akira is known to target organizations across multiple sectors, most notably those in manufacturing, education, and healthcare. These targets span multiple geographic regions, including North America, Latin America, Europe and Asia-Pacific [9].

    Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].
    Figure 1: Geographical distribution of organization’s affected by Akira ransomware in 2025 [9].

    Common Tactics, Techniques and Procedures (TTPs) [7][10]

    Initial Access
    Targets remote access services such as RDP and VPN through vulnerability exploitation or stolen credentials.

    Reconnaissance
    Uses network scanning tools like SoftPerfect and Advanced IP Scanner to map the environment and identify targets.

    Lateral Movement
    Moves laterally using legitimate administrative tools, typically via RDP.

    Persistence
    Employs techniques such as Kerberoasting and pass-the-hash, and tools like Mimikatz to extract credentials. Known to create new domain accounts to maintain access.

    Command and Control
    Utilizes remote access tools including AnyDesk, RustDesk, Ngrok, and Cloudflare Tunnel.

    Exfiltration
    Uses tools such as FileZilla, WinRAR, WinSCP, and Rclone. Data is exfiltrated via protocols like FTP and SFTP, or through cloud storage services such as Mega.

    Darktrace’s Coverage of Akira ransomware

    Reconnaissance

    Darktrace first detected of unusual network activity around 05:10 UTC, when a desktop device was observed performing a network scan and making an unusual number of DCE-RPC requests to the endpoint mapper (epmapper) service. Network scans are typically used to identify open ports, while querying the epmapper service can reveal exposed RPC services on the network.

    Multiple other devices were also later seen with similar reconnaissance activity, and use of the Advanced IP Scanner tool, indicated by connections to the domain advanced-ip-scanner[.]com.

    Lateral movement

    Shortly after the initial reconnaissance, the same desktop device exhibited unusual use of administrative tools. Darktrace observed the user agent “Ruby WinRM Client” and the URI “/wsman” as the device initiated a rare outbound Windows Remote Management (WinRM) connection to two domain controllers (REDACTED-dc1 and REDACTED-dc2). WinRM is a Microsoft service that uses the WS-Management (WSMan) protocol to enable remote management and control of network devices.

    Darktrace also observed the desktop device connecting to an ESXi device (REDACTED-esxi1) via RDP using an LDAP service credential, likely with administrative privileges.

    Credential access

    At around 06:26 UTC, the desktop device was seen fetching an Active Directory certificate from the domain controller (REDACTED-dc1) by making a DCE-RPC request to the ICertPassage service. Shortly after, the device made a Kerberos login using the administrative credential.

    Figure 3: Darktrace’s detection of the of anomalous certificate download and subsequent Kerberos login.

    Further investigation into the device’s event logs revealed a chain of connections that Darktrace’s researchers believe demonstrates a credential access technique known as “UnPAC the hash.”

    This method begins with pre-authentication using Kerberos’ Public Key Cryptography for Initial Authentication (PKINIT), allowing the client to use an X.509 certificate to obtain a Ticket Granting Ticket (TGT) from the Key Distribution Center (KDC) instead of a password.

    The next stage involves User-to-User (U2U) authentication when requesting a Service Ticket (ST) from the KDC. Within Darktrace's visibility of this traffic, U2U was indicated by the client and service principal names within the ST request being identical. Because PKINIT was used earlier, the returned ST contains the NTLM hash of the credential, which can then be extracted and abused for lateral movement or privilege escalation [11].

    Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12].
    Figure 4: Flowchart of Kerberos PKINIT pre-authentication and U2U authentication [12]
    Figure 5: Device event log showing the Kerberos Login and Kerberos Ticket events

    Analysis of the desktop device’s event logs revealed a repeated sequence of suspicious activity across multiple credentials. Each sequence included a DCE-RPC ICertPassage request to download a certificate, followed by a Kerberos login event indicating PKINIT pre-authentication, and then a Kerberos ticket event consistent with User-to-User (U2U) authentication.

    Darktrace identified this pattern as highly unusual. Cyber AI Analyst determined that the device used at least 15 different credentials for Kerberos logins over the course of the attack.

    By compromising multiple credentials, the threat actor likely aimed to escalate privileges and facilitate further malicious activity, including lateral movement. One of the credentials obtained via the “UnPAC the hash” technique was later observed being used in an RDP session to the domain controller (REDACTED-dc2).

    C2 / Additional tooling

    At 06:44 UTC, the domain controller (REDACTED-dc2) was observed initiating a connection to temp[.]sh, a temporary cloud hosting service. Open-source intelligence (OSINT) reporting indicates that this service is commonly used by threat actors to host and distribute malicious payloads, including ransomware [13].

    Shortly afterward, the ESXi device was observed downloading an executable named “vmwaretools” from the rare external endpoint 137.184.243[.]69, using the user agent “Wget.” The repeated outbound connections to this IP suggest potential command-and-control (C2) activity.

    Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.
    Figure 6: Cyber AI Analyst investigation into the suspicious file download and suspected C2 activity between the ESXI device and the external endpoint 137.184.243[.]69.
    Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.
    Figure 7: Packet capture (PCAP) of connections between the ESXi device and 137.184.243[.]69.

    Data exfiltration

    The first signs of data exfiltration were observed at around 7:00 UTC. Both the domain controller (REDACTED-dc2) and a likely SonicWall VPN device were seen uploading approximately 2 GB of data via SSH to the rare external endpoint 66.165.243[.]39 (AS29802 HVC-AS). OSINT sources have since identified this IP as an indicator of compromise (IoC) associated with the Akira ransomware group, known to use it for data exfiltration [14].

    Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.
    Figure 8: Cyber AI Analyst incident view highlighting multiple unusual events across several devices on August 20. Notably, it includes the “Unusual External Data Transfer” event, which corresponds to the anomalous 2 GB data upload to the known Akira-associated endpoint 66.165.243[.]39.

    Cyber AI Analyst

    Throughout the course of the attack, Darktrace’s Cyber AI Analyst autonomously investigated the anomalous activity as it unfolded and correlated related events into a single, cohesive incident. Rather than treating each alert as isolated, Cyber AI Analyst linked them together to reveal the broader narrative of compromise. This holistic view enabled the customer to understand the full scope of the attack, including all associated activities and affected assets that might otherwise have been dismissed as unrelated.

    Overview of Cyber AI Analyst’s investigation, correlating all related internal and external security events across affected devices into a single pane of glass.
    Figure 9: Overview of Cyber AI Analyst’s investigation, correlating all related internal and external security events across affected devices into a single pane of glass.

    Containing the attack

    In response to the multiple anomalous activities observed across the network, Darktrace's Autonomous Response initiated targeted mitigation actions to contain the attack. These included:

    • Blocking connections to known malicious or rare external endpoints, such as 137.184.243[.]69, 66.165.243[.]39, and advanced-ip-scanner[.]com.
    • Blocking internal traffic to sensitive ports, including 88 (Kerberos), 3389 (RDP), and 49339 (DCE-RPC), to disrupt lateral movement and credential abuse.
    • Enforcing a block on all outgoing connections from affected devices to contain potential data exfiltration and C2 activity.
    Autonomous Response actions taken by Darktrace on an affected device, including the blocking of malicious external endpoints and internal service ports.
    Figure 10: Autonomous Response actions taken by Darktrace on an affected device, including the blocking of malicious external endpoints and internal service ports.

    Managed Detection and Response

    As this customer was an MDR subscriber, multiple Enhanced Monitoring alerts—high-fidelity models designed to detect activity indicative of compromise—were triggered across the network. These alerts prompted immediate investigation by Darktrace’s SOC team.

    Upon determining that the activity was likely linked to an Akira ransomware attack, Darktrace analysts swiftly acted to contain the threat. At around 08:05 UTC, devices suspected of being compromised were quarantined, and the customer was promptly notified, enabling them to begin their own remediation procedures without delay.

    A wider campaign?

    Darktrace’s SOC and Threat Research teams identified at least three additional incidents likely linked to the same campaign. All targeted organizations were based in the US, spanning various industries, and each have indications of using SonicWall VPN, indicating it had likely been targeted for initial access.

    Across these incidents, similar patterns emerged. In each case, a suspicious executable named “vmwaretools” was downloaded from the endpoint 85.239.52[.]96 using the user agent “Wget”, bearing some resemblance to the file downloads seen in the incident described here. Data exfiltration was also observed via SSH to the endpoints 107.155.69[.]42 and 107.155.93[.]154, both of which belong to the same ASN also seen in the incident described in this blog: S29802 HVC-AS. Notably, 107.155.93[.]154 has been reported in OSINT as an indicator associated with Akira ransomware activity [15]. Further recent Akira ransomware cases have been observed involving SonicWall VPN, where no similar executable file downloads were observed, but SSH exfiltration to the same ASN was. These overlapping and non-overlapping TTPs may reflect the blurring lines between different affiliates operating under the same RaaS.

    Lessons from the campaign

    This campaign by Akira ransomware actors underscores the critical importance of maintaining up-to-date patching practices. Threat actors continue to exploit previously disclosed vulnerabilities, not just zero-days, highlighting the need for ongoing vigilance even after patches are released. It also demonstrates how misconfigurations and overlooked weaknesses can be leveraged for initial access or privilege escalation, even in otherwise well-maintained environments.

    Darktrace’s observations further reveal that ransomware actors are increasingly relying on legitimate administrative tools, such as WinRM, to blend in with normal network activity and evade detection. In addition to previously documented Kerberos-based credential access techniques like Kerberoasting and pass-the-hash, this campaign featured the use of UnPAC the hash to extract NTLM hashes via PKINIT and U2U authentication for lateral movement or privilege escalation.

    Credit to Emily Megan Lim (Senior Cyber Analyst), Vivek Rajan (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), and Sam Lister (Specialist Security Researcher)

    Appendices

    Darktrace Model Detections

    Anomalous Connection / Active Remote Desktop Tunnel

    Anomalous Connection / Data Sent to Rare Domain

    Anomalous Connection / New User Agent to IP Without Hostname

    Anomalous Connection / Possible Data Staging and External Upload

    Anomalous Connection / Rare WinRM Incoming

    Anomalous Connection / Rare WinRM Outgoing

    Anomalous Connection / Uncommon 1 GiB Outbound

    Anomalous Connection / Unusual Admin RDP Session

    Anomalous Connection / Unusual Incoming Long Remote Desktop Session

    Anomalous Connection / Unusual Incoming Long SSH Session

    Anomalous Connection / Unusual Long SSH Session

    Anomalous File / EXE from Rare External Location

    Anomalous Server Activity / Anomalous External Activity from Critical Network Device

    Anomalous Server Activity / Outgoing from Server

    Anomalous Server Activity / Rare External from Server

    Compliance / Default Credential Usage

    Compliance / High Priority Compliance Model Alert

    Compliance / Outgoing NTLM Request from DC

    Compliance / SSH to Rare External Destination

    Compromise / Large Number of Suspicious Successful Connections

    Compromise / Sustained TCP Beaconing Activity To Rare Endpoint

    Device / Anomalous Certificate Download Activity

    Device / Anomalous SSH Followed By Multiple Model Alerts

    Device / Anonymous NTLM Logins

    Device / Attack and Recon Tools

    Device / ICMP Address Scan

    Device / Large Number of Model Alerts

    Device / Network Range Scan

    Device / Network Scan

    Device / New User Agent To Internal Server

    Device / Possible SMB/NTLM Brute Force

    Device / Possible SMB/NTLM Reconnaissance

    Device / RDP Scan

    Device / Reverse DNS Sweep

    Device / Suspicious SMB Scanning Activity

    Device / UDP Enumeration

    Unusual Activity / Unusual External Data to New Endpoint

    Unusual Activity / Unusual External Data Transfer

    User / Multiple Uncommon New Credentials on Device

    User / New Admin Credentials on Client

    User / New Admin Credentials on Server

    Enhanced Monitoring Models

    Compromise / Anomalous Certificate Download and Kerberos Login

    Device / Initial Attack Chain Activity

    Device / Large Number of Model Alerts from Critical Network Device

    Device / Multiple Lateral Movement Model Alerts

    Device / Suspicious Network Scan Activity

    Unusual Activity / Enhanced Unusual External Data Transfer

    Antigena/Autonomous Response Models

    Antigena / Network / External Threat / Antigena File then New Outbound Block

    Antigena / Network / External Threat / Antigena Suspicious Activity Block

    Antigena / Network / External Threat / Antigena Suspicious File Block

    Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

    Antigena / Network / Insider Threat / Antigena Network Scan Block

    Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block

    Antigena / Network / Manual / Quarantine Device

    Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

    Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

    Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

    Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block

    Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

    Antigena / Network / Significant Anomaly / Antigena Significant Server Anomaly Block

    Antigena / Network / Significant Anomaly / Repeated Antigena Alerts

    List of Indicators of Compromise (IoCs)

    ·      66.165.243[.]39 – IP Address – Data exfiltration endpoint

    ·      107.155.69[.]42 – IP Address – Probable data exfiltration endpoint

    ·      107.155.93[.]154 – IP Address – Likely Data exfiltration endpoint

    ·      137.184.126[.]86 – IP Address – Possible C2 endpoint

    ·      85.239.52[.]96 – IP Address – Likely C2 endpoint

    ·      hxxp://85.239.52[.]96:8000/vmwarecli  – URL – File download

    ·      hxxp://137.184.126[.]86:8080/vmwaretools – URL – File download

    MITRE ATT&CK Mapping

    Initial Access – T1190 – Exploit Public-Facing Application

    Reconnaissance – T1590.002 – Gather Victim Network Information: DNS

    Reconnaissance – T1590.005 – Gather Victim Network Information: IP Addresses

    Reconnaissance – T1592.004 – Gather Victim Host Information: Client Configurations

    Reconnaissance – T1595 – Active Scanning

    Discovery – T1018 – Remote System Discovery

    Discovery – T1046 – Network Service Discovery

    Discovery – T1083 – File and Directory Discovery

    Discovery – T1135 – Network Share Discovery

    Lateral Movement – T1021.001 – Remote Services: Remote Desktop Protocol

    Lateral Movement – T1021.004 – Remote Services: SSH

    Lateral Movement – T1021.006 – Remote Services: Windows Remote Management

    Lateral Movement – T1550.002 – Use Alternate Authentication Material: Pass the Hash

    Lateral Movement – T1550.003 – Use Alternate Authentication Material: Pass the Ticket

    Credential Access – T1110.001 – Brute Force: Password Guessing

    Credential Access – T1649 – Steal or Forge Authentication Certificates

    Persistence, Privilege Escalation – T1078 – Valid Accounts

    Resource Development – T1588.001 – Obtain Capabilities: Malware

    Command and Control – T1071.001 – Application Layer Protocol: Web Protocols

    Command and Control – T1105 – Ingress Tool Transfer

    Command and Control – T1573 – Encrypted Channel

    Collection – T1074 – Data Staged

    Exfiltration – T1041 – Exfiltration Over C2 Channel

    Exfiltration – T1048 – Exfiltration Over Alternative Protocol

    References

    [1] https://thehackernews.com/2025/08/sonicwall-investigating-potential-ssl.html

    [2] https://www.sonicwall.com/support/notices/gen-7-and-newer-sonicwall-firewalls-sslvpn-recent-threat-activity/250804095336430

    [3] https://psirt.global.sonicwall.com/vuln-detail/SNWLID-2024-0015

    [4] https://arcticwolf.com/resources/blog/arctic-wolf-observes-akira-ransomware-campaign-targeting-sonicwall-sslvpn-accounts/

    [5] https://www.rapid7.com/blog/post/dr-akira-ransomware-group-utilizing-sonicwall-devices-for-initial-access/

    [6] https://www.ic3.gov/AnnualReport/Reports/2024_IC3Report.pdf

    [7] https://www.cisa.gov/news-events/cybersecurity-advisories/aa24-109a

    [8] https://blog.talosintelligence.com/akira-ransomware-continues-to-evolve/

    [9] https://www.ransomware.live/map?year=2025&q=akira

    [10] https://attack.mitre.org/groups/G1024/
    [11] https://labs.lares.com/fear-kerberos-pt2/#UNPAC

    [12] https://www.thehacker.recipes/ad/movement/kerberos/unpac-the-hash

    [13] https://www.s-rminform.com/latest-thinking/derailing-akira-cyber-threat-intelligence)

    [14] https://fieldeffect.com/blog/update-akira-ransomware-group-targets-sonicwall-vpn-appliances

    [15] https://arcticwolf.com/resources/blog/arctic-wolf-observes-july-2025-uptick-in-akira-ransomware-activity-targeting-sonicwall-ssl-vpn/

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    About the author
    Emily Megan Lim
    Cyber Analyst
    Your data. Our AI.
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