How AI Detected A Hacker Hiding in Energy Grid Within Hours
Darktrace's AI swiftly detected a hacker infiltrating an energy grid within hours. Learn about how AI identified the threat and uncovered anomalous behavior.
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
Max Heinemeyer
Global Field CISO
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08
Oct 2020
A cyber-criminal had already made the first steps of a critical intrusion at a European energy organization when the company deployed AI for cyber defense. Despite the attacker already lurking in the system, Darktrace was able to recognize that their activity deviated from the learned ‘pattern of life’ of the rest of the organization.
The hacker had compromised a desktop and established Command & Control (C2), downloading executable files disguised as harmless PNG files. But Darktrace autonomously grouped the desktop into a ‘peer group’ of similar devices, recognizing that it’s behavior was anomalous in comparison to the wider group.
The intrusion used many common evasion techniques to bypass traditional tools, including ‘Living off the Land’ techniques and masquerading malware behind commonly used file types. Upon Darktrace’s detection, later analysis of these ‘harmless’ files suggests they could lead to possible remote access of the compromised device, with use of the Metasploit framework.
Attack details
Figure 1: A timeline of the attack
Immediately upon installation, Darktrace began monitoring the behavior of around 5,000 devices, establishing their ‘pattern of life’, as well as that of their peer groups, and the wider organization. Just two hours into this learning process, an adminstator’s desktop was observed making suspicious connections to multiple domains hosted on IP 78.142.XX.XXX. The regular nature of these connections suggests that the infection was already established on the device.
The next day, the desktop was observed downloading a suspicious executable file named d.png, and multiple similar downloads subsequently occurred.
Executable files are often masqueraded as other file types in order to help bypass security measures, however the mismatched file extension here was immediately detected by Darktrace and flagged for further investigation.
A lack of OSINT for the download source at the time of this activity meant other security measures may have missed the suspicious HTTP connections. However, the rarity of the IP on the network alongside the unusual behavior in comparison to other network devices led Darktrace to quickly detect this malicious beaconing.
An overview of the infected device
After the first model breach, Darktrace continued to monitor the infected device, graphically representing the regular connections to the malicious endpoint w.gemlab[.]top. The device made several connections to this endpoint at precise, 3-hour intervals, suggesting some automated activity. No other devices in the peer group displayed this sort of behavior.
Figure 2: Darktrace presenting the connections in a graph, with model breaches represented by orange dots
Darktrace detected the suspicious nature of these HTTP connections, clearly surfacing the model breach for the security team to review and remediate.
Figure 3: Darktrace surfacing high-level details of the model breach
Figure 4: The device event log
Detecting a threat already inside
This example of a sophisticated attack shows an attempt to ‘blend in’ to the noise of regular traffic. However, Darktrace’s Immune System was still able to identify the signs of malintent, given its ability to auto-detect and cluster ‘peer groups’ of users and devices, thereby still recognizing abnormal behavior on the single compromised device. Despite only being active for a few hours, Darktrace immediately flagged the activity for further investigation.
Without Darktrace’s real-time detections and alerts – and a quick response from the security team to contain the threat — the potential ramifications of this intrusion can’t be understated. With effective command and control and sufficient privileges granted, cyber-criminals have been known to disrupt entire energy grids leading to mass blackouts in Ukraine and Estonia. Alternatively, hackers could have held large volumes of sensitive files to ransom, causing huge financial and reputational damage to the firm in question.
This isn’t the first time Darktrace has identified existing infections in customer environments – and it’s unlikely to be the last. A self-learning approach to cyber defence is not limited to identifying changes in the environment, but can detect existing compromises as well as novel and advanced attacks that evade traditional rules and signatures.
Thanks to Darktrace analyst Emma Foulger for her insights on the above threat find.
IoCs:IoCCommentcloud.apcdn[.]ruMultiple downloads of file from this endpoint URI: /d.png Hash: 82e1c9727ae04a19c8a155559e1855349e528244w.gemlab[.]topFirst observed C2 connection was seen to this hostnamecloud.gemlab[.]top img.gemlab[.]top img.apcdn[.]ruOther C2 communication seen to these hostnames
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.
Out of Character: Detecting Vendor Compromise and Trusted Relationship Abuse with Darktrace
What is Vendor Email Compromise?
Vendor Email Compromise (VEC) refers to an attack where actors breach a third-party provider to exploit their access, relationships, or systems for malicious purposes. The initially compromised entities are often the target’s existing partners, though this can extend to any organization or individual the target is likely to trust.
Itsits at the intersection of supply chain attacks and business email compromise (BEC), blending technical exploitation with trust-based deception. Attackers often infiltrate existing conversations, leveraging AI to mimic tone and avoid common spelling and grammar pitfalls. Malicious content is typically hosted on otherwise reputable file sharing platforms, meaning any shared links initially seem harmless.
While techniques to achieve initial access may have evolved, the goals remain familiar. Threat actors harvest credentials, launch subsequent phishing campaigns, attempt to redirect invoice payments for financial gain, and exfiltrate sensitive corporate data.
Why traditional defenses fall short
These subtle and sophisticated email attacks pose unique challenges for defenders. Few busy people would treat an ongoing conversation with a trusted contact with the same level of suspicion as an email from the CEO requesting ‘URGENT ASSISTANCE!’ Unfortunately, many traditional secure email gateways (SEGs) struggle with this too. Detecting an out-of-character email, when it does not obviously appear out of character, is a complex challenge. It’s hardly surprising, then, that 83% of organizations have experienced a security incident involving third-party vendors [1].
This article explores how Darktrace detected four different vendor compromise campaigns for a single customer, within a two-week period in 2025. Darktrace / EMAIL successfully identified the subtle indicators that these seemingly benign emails from trusted senders were, in fact, malicious. Due to the configuration of Darktrace / EMAIL in this customer’s environment, it was unable to take action against the malicious emails. However, if fully enabled to take Autonomous Response, it would have held all offending emails identified.
How does Darktrace detect vendor compromise?
The answer lies at the core of how Darktrace operates: anomaly detection. Rather than relying on known malicious rules or signatures, Darktrace learns what ‘normal’ looks like for an environment, then looks for anomalies across a wide range of metrics. Despite the resourcefulness of the threat actors involved in this case, Darktrace identified many anomalies across these campaigns.
Different campaigns, common traits
A wide variety of approaches was observed. Individuals, shared mailboxes and external contractors were all targeted. Two emails originated from compromised current vendors, while two came from unknown compromised organizations - one in an associated industry. The sender organizations were either familiar or, at the very least, professional in appearance, with no unusual alphanumeric strings or suspicious top-level domains (TLDs). Subject line, such as “New Approved Statement From [REDACTED]” and “[REDACTED] - Proposal Document” appeared unremarkable and were not designed to provoke heightened emotions like typical social engineering or BEC attempts.
All emails had been given a Microsoft Spam Confidence Level of 1, indicating Microsoft did not consider them to be spam or malicious [2]. They also passed authentication checks (including SPF, and in some cases DKIM and DMARC), meaning they appeared to originate from an authentic source for the sender domain and had not been tampered with in transit.
All observed phishing emails contained a link hosted on a legitimate and commonly used file-sharing site. These sites were often convincingly themed, frequently featuring the name of a trusted vendor either on the page or within the URL, to appear authentic and avoid raising suspicion. However, these links served only as the initial step in a more complex, multi-stage phishing process.
Figure 1: A legitimate file sharing site used in phishing emails to host a secondary malicious link.
Figure 2: Another example of a legitimate file sharing endpoint sent in a phishing email and used to host a malicious link.
If followed, the recipient would be redirected, sometimes via CAPTCHA, to fake Microsoft login pages designed to capturing credentials, namely http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html and https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html#.
The latter made use of homoglyphs to deceive the user, with a link referencing ‘s3cure0line’, rather than ‘secureonline’. Post-incident investigation using open-source intelligence (OSINT) confirmed that the domains were linked to malicious phishing endpoints [3] [4].
Figure 3: Fake Microsoft login page designed to harvest credentials.
Figure 4: Phishing kit with likely AI-generated image, designed to harvest user credentials. The URL uses ‘s3cure0line’ instead of ‘secureonline’, a subtle misspelling intended to deceive users.
Darktrace Anomaly Detection
Some senders were unknown to the network, with no previous outbound or inbound emails. Some had sent the email to multiple undisclosed recipients using BCC, an unusual behavior for a new sender.
Where the sender organization was an existing vendor, Darktrace recognized out-of-character behavior, in this case it was the first time a link to a particular file-sharing site had been shared. Often the links themselves exhibited anomalies, either being unusually prominent or hidden altogether - masked by text or a clickable image.
Crucially, Darktrace / EMAIL is able to identify malicious links at the time of processing the emails, without needing to visit the URLs or analyze the destination endpoints, meaning even the most convincing phishing pages cannot evade detection – meaning even the most convincing phishing emails cannot evade detection. This sets it apart from many competitors who rely on crawling the endpoints present in emails. This, among other things, risks disruption to user experience, such as unsubscribing them from emails, for instance.
Darktrace was also able to determine that the malicious emails originated from a compromised mailbox, using a series of behavioral and contextual metrics to make the identification. Upon analysis of the emails, Darktrace autonomously assigned several contextual tags to highlight their concerning elements, indicating that the messages contained phishing links, were likely sent from a compromised account, and originated from a known correspondent exhibiting out-of-character behavior.
Figure 5: Tags assigned to offending emails by Darktrace / EMAIL.
Figure 6: A summary of the anomalous email, confirming that it contained a highly suspicious link.
Out-of-character behavior caught in real-time
In another customer environment around the same time Darktrace / EMAIL detected multiple emails with carefully crafted, contextually appropriate subject lines sent from an established correspondent being sent to 30 different recipients. In many cases, the attacker hijacked existing threads and inserted their malicious emails into an ongoing conversation in an effort to blend in and avoid detection. As in the previous, the attacker leveraged a well-known service, this time ClickFunnels, to host a document containing another malicious link. Once again, they were assigned a Microsoft Spam Confidence Level of 1, indicating that they were not considered malicious.
Figure 7: The legitimate ClickFunnels page used to host a malicious phishing link.
This time, however, the customer had Darktrace / EMAIL fully enabled to take Autonomous Response against suspicious emails. As a result, when Darktrace detected the out-of-character behavior, specifically, the sharing of a link to a previously unused file-sharing domain, and identified the likely malicious intent of the message, it held the email, preventing it from reaching recipients’ inboxes and effectively shutting down the attack.
Figure 8: Darktrace / EMAIL’s detection of malicious emails inserted into an existing thread.*
*To preserve anonymity, all real customer names, email addresses, and other identifying details have been redacted and replaced with fictitious placeholders.
Legitimate messages in the conversation were assigned an Anomaly Score of 0, while the newly inserted malicious emails identified and were flagged with the maximum score of 100.
Key takeaways for defenders
Phishing remains big business, and as the landscape evolves, today’s campaigns often look very different from earlier versions. As with network-based attacks, threat actors are increasingly leveraging legitimate tools and exploiting trusted relationships to carry out their malicious goals, often staying under the radar of security teams and traditional email defenses.
As attackers continue to exploit trusted relationships between organizations and their third-party associates, security teams must remain vigilant to unexpected or suspicious email activity. Protecting the digital estate requires an email solution capable of identifying malicious characteristics, even when they originate from otherwise trusted senders.
Credit to Jennifer Beckett (Cyber Analyst), Patrick Anjos (Senior Cyber Analyst), Ryan Traill (Analyst Content Lead), Kiri Addison (Director of Product)
Appendices
IoC - Type - Description + Confidence
- http://pub-ac94c05b39aa4f75ad1df88d384932b8.r2[.]dev/offline[.]html#p – fake Microsoft login page
- https://s3.us-east-1.amazonaws[.]com/s3cure0line-0365cql0.19db86c3-b2b9-44cc-b339-36da233a3be2ml0qin/s3cccql0.19db86c3-b2b9-44cc-b339-36da233a3be2%26l0qn[.]html# - link to domain used in homoglyph attack
The content provided in this blog is published by Darktrace for general informational purposes only and reflects our understanding of cybersecurity topics, trends, incidents, and developments at the time of publication. While we strive to ensure accuracy and relevance, the information is provided “as is” without any representations or warranties, express or implied. Darktrace makes no guarantees regarding the completeness, accuracy, reliability, or timeliness of any information presented and expressly disclaims all warranties.
Nothing in this blog constitutes legal, technical, or professional advice, and readers should consult qualified professionals before acting on any information contained herein. Any references to third-party organizations, technologies, threat actors, or incidents are for informational purposes only and do not imply affiliation, endorsement, or recommendation.
Darktrace, its affiliates, employees, or agents shall not be held liable for any loss, damage, or harm arising from the use of or reliance on the information in this blog.
The cybersecurity landscape evolves rapidly, and blog content may become outdated or superseded. We reserve the right to update, modify, or remove any content
Announcing Unified OT Security with Dedicated OT Workflows, Segmentation-Aware Risk Insights, and Next-Gen Endpoint Visibility for Industrial Teams
The challenge of convergence without clarity
Convergence is no longer a roadmap idea, it is the daily reality for industrial security teams. As Information Technology (IT) and Operational Technology (OT) environments merge, the line between a cyber incident and an operational disruption grows increasingly hard to define. A misconfigured firewall rule can lead to downtime. A protocol misuse might look like a glitch. And when a pump stalls but nothing appears in the Security Operations Center (SOC) dashboard, teams are left asking: is this operational or is this a threat?
The lack of shared context slows down response, creates friction between SOC analysts and plant engineers, and leaves organizations vulnerable at exactly the points where IT and OT converge. Defenders need more than alerts, they need clarity that both sides can trust.
The breakthrough with Darktrace / OT
This latest Darktrace / OT release was built to deliver exactly that. It introduces shared context between Security, IT, and OT operations, helping reduce friction and close the security gaps at the intersection of these domains.
With a dedicated dashboard built for operations teams, extended visibility into endpoints for new forms of detection and CVE collection, expanded protocol coverage, and smarter risk modeling aligned to segmentation policies, teams can now operate from a shared source of truth. These enhancements are not just incremental upgrades, they are foundational improvements designed to bring clarity, efficiency, and trust to converged environments.
A dashboard built for OT engineers
The new Operational Overview provides OT engineers with a workspace designed for them, not for SOC analysts. It brings asset management, risk insights and operational alerts into one place. Engineers can now see activity like firmware changes, controller reprograms or the sudden appearance of a new workstation on the network, providing a tailored view for critical insights and productivity gains without navigating IT-centric workflows. Each device view is now enriched with cross-linked intelligence, make, model, firmware version and the roles inferred by Self-Learning AI, making it easier to understand how each asset behaves, what function it serves, and where it fits within the broader industrial process. By suppressing IT-centric noise, the dashboard highlights only the anomalies that matter to operations, accelerating triage, enabling smoother IT/OT collaboration, and reducing time to root cause without jumping between tools.
This is usability with purpose, a view that matches OT workflows and accelerates response.
Figure 1: The Operational Overview provides an intuitive dashboard summarizing all OT Assets, Alerts, and Risk.
Full-spectrum coverage across endpoints, sensors and protocols
The release also extends visibility into areas that have traditionally been blind spots. Engineering workstations, Human-Machine Interfaces (HMIs), contractor laptops and field devices are often the entry points for attackers, yet the hardest to monitor.
Darktrace introduces Network Endpoint eXtended Telemetry (NEXT) for OT, a lightweight collector built for segmented and resource-constrained environments. NEXT for OT uses Endpoint sensors to capture localized network, and now process-level telemetry, placing it in context alongside other network and asset data to:
Identify vulnerabilities and OS data, which is leveraged by OT Risk Management for risk scoring and patching prioritization, removing the need for third-party CVE collection.
Surface novel threats using Self-Learning AI that standalone Endpoint Detection and Response (EDR) would miss.
Extend Cyber AI Analyst investigations through to the endpoint root cause.
NEXT is part of our existing cSensor endpoint agent, can be deployed standalone or alongside existing EDR tools, and allows capabilities to be enabled or disabled depending on factors such as security or OT team objectives and resource utilization.
Figure 2: Darktrace / OT delivers CVE patch priority insights by combining threat intelligence with extended network and endpoint telemetry
The family of Darktrace Endpoint sensors also receive a boost in deployment flexibility, with on-prem server-based setups, as well as a Windows driver tailored for zero-trust and high-security environments.
Protocol coverage has been extended where it matters most. Darktrace now performs protocol analysis of a wider range of GE and Mitsubishi protocols, giving operators real-time visibility into commands and state changes on Programmable Logic Controllers (PLCs), robots and controllers. Backed by Self-Learning AI, this inspection does more than parse traffic, it understands what normal looks like and flags deviations that signal risk.
Integrated risk and governance workflows
Security data is only valuable when it drives action. Darktrace / OT delivers risk insights that go beyond patching, helping teams take meaningful steps even when remediation isn't possible. Risk is assessed not just by CVE presence, but by how network segmentation, firewall policies, and attack path logic neutralize or contain real-world exposure. This approach empowers defenders to deprioritize low-impact vulnerabilities and focus effort where risk truly exists. Building on the foundation introduced in release 6.3, such as KEV enrichment, endpoint OS data, and exploit mapping, this release introduces new integrations that bring Darktrace / OT intelligence directly into governance workflows.
Fortinet FortiGate firewall ingestion feeds segmentation rules into attack path modeling, revealing real exposure when policies fail and closing feeds into patching prioritization based on a policy to CVE exposure assessment.
ServiceNow Configuration Management Database (CMDB) sync ensures asset intelligence stays current across governance platforms, eliminating manual inventory work.
Risk modeling has also been made more operationally relevant. Scores are now contextualized by exploitability, asset criticality, firewall policy, and segmentation posture. Patch recommendations are modeled in terms of safety, uptime and compliance rather than just Common Vulnerability Scoring System (CVSS) numbers. And importantly, risk is prioritized across the Purdue Model, giving defenders visibility into whether vulnerabilities remain isolated to IT or extend into OT-critical layers.
Figure 3: Attack Path Modeling based on NetFlow and network topology reveals high risk points of IT/OT convergence.
The real-world impact for defenders
In today’s environments, attackers move fluidly between IT and OT. Without unified visibility and shared context, incidents cascade faster than teams can respond.
With this release, Darktrace / OT changes that reality. The Operational Overview gives Engineers a dashboard they can use daily, tailored to their workflows. SOC analysts can seamlessly investigate telemetry across endpoints, sensors and protocols that were once blind spots. Operators gain transparency into PLCs and controllers. Governance teams benefit from automated integrations with platforms like Fortinet and ServiceNow. And all stakeholders work from risk models that reflect what truly matters: safety, uptime and compliance.
This release is not about creating more alerts. It is about providing more clarity. By unifying context across IT and OT, Darktrace / OT enables defenders to see more, understand more and act faster.
Because in environments where safety and uptime are non-negotiable, clarity is what matters most.
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