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.
Advancing OT Security with Architecture Visibility, Operational Reporting, and Industrial Context
This Darktrace / OT release introduces new capabilities designed to help industrial organizations better understand, document, and operationalize their operational environments. With native OT architecture visualization, structured asset and compliance reporting, and expanded industrial protocol coverage, this release focuses on improving how teams manage real operational security workflows.
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
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Darktrace is proud to announce that Darktrace / OT has been recognized as the only Visionary in the 2026 Gartner® Magic Quadrant™ for CPS Protection Platforms, marking the second consecutive year Darktrace has held this position.
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
Managing OT Remote Access with Zero Trust Control & AI Driven Detection
A forward-looking breakdown of why modern OT environments can’t rely on visibility alone, and how combining Zero Trust access control with AI-driven behavioral detection gives industrial organizations real-time oversight, accountability, and secure remote access without disrupting operations.
Pallavi Singh
Product Marketing Manager, OT Security & Compliance
In today's threat landscape, blending in to normal activity is the key to success for attackers and the growing reliance on residential proxies shows a significant shift in how threat actors are attempting to bypass IP detection tools.
The increasing dependency on residential proxies has exposed how prevalent proxy services are and how reliant a diverse range of threat actors are on them. From cybercriminal groups to state‑sponsored actors, the need to bypass IP detection tools is fundamental to the success of these groups. One malware that has quietly become notorious for its ability to avoid anomaly detection is GhostSocks, a malware that turns compromised devices into residential proxies.
What is GhostSocks?
Originally marketed on the Russian underground forum xss[.]is as a Malware‑as‑a‑Service (MaaS), GhostSocks enables threat actors to turn compromised devices into residential proxies, leveraging the victim's internet bandwidth to route malicious traffic through it.
How does Ghostsocks malware work?
The malware offers the threat actor a “clean” IP address, making it look like it is coming from a household user. This enables the bypassing of geographic restrictions and IP detection tools, a perfect tool for avoiding anomaly detection. It wasn’t until 2024, when a partnership was announced with the infamous information stealer Lumma Stealer, that GhostSocks surged into widespread adoption and alluded to who may be the author of the proxy malware.
Written in GoLang, GhostSocks utilizes the SOCKS5 proxy protocol, creating a SOCKS5 connection on infected devices. It uses a relay‑based C2 implementation, where an intermediary server sits in between the real command-and-control (C2) server and the infected device.
How does Ghostsocks malware evade detection?
To further increase evasion, the Ghostsocks malware wraps its SOCKS5 tunnels in TLS encryption, allowing its malicious traffic to blend into normal network traffic.
Early variants of GhostSocks do not implement a persistence mechanism; however, later versions achieve persistence via registry run keys, ensuring sustained proxy operational time [1].
While proxying is its primary purpose, GhostSocks also incorporates backdoor functionality, enabling malicious actors to run arbitrary commands and download and deploy additional malicious payloads. This was evident with the well‑known ransomware group Black Basta, which reportedly used GhostSocks as a way of maintaining long‑term access to victims’ networks [1].
Darktrace’s detection of GhostSocks Malware
Darktrace observed a steady increase in GhostSocks activity across its customer base from late 2025, with its Threat Research team identifying multiple incidents involving the malware. In one notable case from December 2025, Darktrace detected GhostSocks operating alongside Lumma Stealer, reinforcing that the partnership between Lumma and GhostSocks remains active despite recent attempts to disrupt Lumma’s infrastructure.
Darktrace’s first detection of GhostSocks‑related activity came when a device on the network of a customer in the education sector began making connections to an endpoint with a suspicious self‑signed certificate that had never been seen on the network before.
The endpoint in question, 159.89.46[.]92 with the hostname retreaw[.]click, has been flagged by multiple open‑source intelligence (OSINT) sources as being associated with Lumma Stealer’s C2 infrastructure [2], indicating its likely role in the delivery of malicious payloads.
Figure 1: Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.
Less than two minutes later, Darktrace observed the same device downloading the executable (.exe) file “Renewable.exe” from the IP 86.54.24[.]29, which Darktrace recognized as 100% rare for this network.
Figure 2: Darktrace’s detection of a device downloading the unusual executable file “Renewable.exe”.
Both the file MD5 hash and the executable itself have been identified by multiple OSINT vendors as being associated with the GhostSocks malware [3], with the executable likely the backdoor component of the GhostSocks malware, facilitating the distribution of additional malicious payloads [4].
Following this detection, Darktrace’s Autonomous Response capability recommended a blocking action for the device in an early attempt to stop the malicious file download. In this instance, Darktrace was configured in Human Confirmation Mode, meaning the customer’s security team was required to manually apply any mitigative response actions. Had Autonomous Response been fully enabled at the time of the attack, the connections to 86.54.24[.]29 would have been blocked, rendering the malware ineffective at reaching its C2 infrastructure and halting any further malicious communication.
Figure 3: Darktrace’s Autonomous Response capability suggesting blocking the suspicious connections to the unusual endpoint from which the malicious executable was downloaded.
As the attack was able to progress, two days later the device was detected downloading additional payloads from the endpoint www.lbfs[.]site (23.106.58[.]48), including “Setup.exe”, “,.exe”, and “/vp6c63yoz.exe”.
Figure 4: Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.
Once again, Darktrace recognized the anomalous nature of these downloads and suggested that a “group pattern of life” be enforced on the offending device in an attempt to contain the activity. By enforcing a pattern of life on a device, Darktrace restricts its activity to connections and behaviors similar to those performed by peer devices within the same group, while still allowing it to carry out its expected activity, effectively preventing deviations indicative of compromise while minimizing disruption. As mentioned earlier, these mitigative actions required manual implementation, so the activity was able to continue. Darktrace proceeded to suggest further actions to contain subsequent malicious downloads, including an attempt to block all outbound traffic to stop the attack from progressing.
Figure 5: An overview of download activity and the Autonomous Response actions recommended by Darktrace to block the downloads.
Around the same time, a third executable download was detected, this time from the hostname hxxp[://]d2ihv8ymzp14lr.cloudfront.net/2021-08-19/udppump[.]exe, along with the file “udppump.exe”.While GhostSocks may have been present only to facilitate the delivery of additional payloads, there is no indication that these CloudFront endpoints or files are functionally linked to GhostSocks. Rather, the evidence points to broader malicious file‑download activity.
Shortly after the multiple executable files had been downloaded, Darktrace observed the device initiating a series of repeated successful connections to several rare external endpoints, behavior consistent with early-stage C2 beaconing activity.
Cyber AI Analyst’s investigation
Figure 7: Darktrace’s detection of additional malicious file downloads from malicious CloudFront endpoints.
Throughout the course of this attack, Darktrace’s Cyber AI Analyst carried out its own autonomous investigation, piecing together seemingly separate events into one wider incident encompassing the first suspicious downloads beginning on December 4, the unusual connectivity to many suspicious IPs that followed, and the successful beaconing activity observed two days later. By analyzing these events in real-time and viewing them as part of the bigger picture, Cyber AI Analyst was able to construct an in‑depth breakdown of the attack to aid the customer’s investigation and remediation efforts.
Figure 8: Cyber AI Analyst investigation detailing the sequence of events on the compromised device, highlighting its extensive connectivity to rare endpoints, the related malicious file‑download activity, and finally the emergence of C2 beaconing behavior.
Conclusion
The versatility offered by GhostSocks is far from new, but its ability to convert compromised devices into residential proxy nodes, while enabling long‑term, covert network access—illustrates how threat actors continue to maximise the value of their victims’ infrastructure. Its growing popularity, coupled with its ongoing partnership with Lumma, demonstrates that infrastructure takedowns alone are insufficient; as long as threat actors remain committed to maintaining anonymity and can rapidly rebuild their ecosystems, related malware activity is likely to persist in some form.
Credit to Isabel Evans (Cyber Analyst), Gernice Lee (Associate Principal Analyst & Regional Consultancy Lead – APJ) Edited by Ryan Traill (Content Manager)
Darktrace Unites Human Behavior and Threat Detection Across Email, Slack, Teams, and Zoom
The communication attack surface is expanding
Modern attackers no longer focus solely on inboxes, they target people and the productivity systems where work actually happens. Meanwhile, the boundary between internal and external usage of tools is becoming blurrier everyday – turning the entire workplace into the attack surface. In 2025, identity compromise emerged as the single most consistent threat across the global threat landscape, as observed by Darktrace research across our entire customer base. Over 70% of incidents in the US involved SaaS/M365 account compromise and phishing or email-based social engineering, making credential abuse the single most effective initial access vector.
Despite this upward trend, investment in existing security awareness training (SAT) isn’t moving the needle on reducing risk. 84% of organizations still measure success through completion rates1, even though completion of standard training correlates with less than 2% real improvement in risky behavior.2 By prioritizing completion, organizations reward time spent rather than meaningful engagement, yet time in training doesn’t translate to retention or real-world decision-making. This compliance-first approach has left the workforce unprepared for the threats they actually face.
At the same time, attacks have evolved. Highly personalized, AI-generated campaigns now move fluidly across email, Slack, Teams, Zoom, and beyond, blending channels and even targeting systems directly through techniques like prompt injection. This new reality demands a different approach: one that treats people and the tools they use as a single ecosystem, where behavior and detection continuously inform and strengthen each other.
Only an adaptive communication security system can keep pace with the speed, creativity, and cross channel nature of today’s threats.
Ushering in the adaptive era of workplace security
With this release, Darktrace brings together our new behavior-driven training solution with email detection, cross-channel visibility, and platform-level insights. Powered by Self-Learning AI, it delivers protection across both people and the communication tools they rely on every day, including email, Slack, Teams, and Zoom.
Each component learns from the others – training adapts to real user behavior, detection evolves across channels, and response is continuously refined – creating a powerful feedback loop that strengthens resilience and improves accuracy against today’s AI-driven threats.
Introducing: Unified training and email security for a self-improving email defense
Our brand new product, Darktrace / Adaptive Human Defense, closes the gap between human behavior and email security to continuously strengthen both people and defenses. Each user receives personalized training that adapts to their own inbox activity and skill level, with learning delivered directly within the flow of their day-to-day email interactions.
By learning from each user’s interactions with security training, it adapts security responses, creating a closed-loop system where training reinforces detection and detection informs training. Let’s look at some of the benefits.
Reduce successful phishing at the source with contextual Just in Time coaching: Contextual coaching appears directly in real email threads the moment risky behavior is detected, so habits change where mistakes actually happen. Configurable triggers and group policies target the right users, reducing repeated errors and administrative overhead.
Adaptive phishing simulations that progress automatically with each user: Embedded simulations vary in their degree of realism, from generic phishing to generative AI-enabled spear phishing. Users progress through the difficulty levels based on their performance to give an accurate picture of their phishing preparedness.
Native email security integration turns human behavior into quantified risk: The native email security integration allows engagement, links clicked, and question success signals to flow back into / EMAIL recipes and models, so detection and response adapt automatically as users learn.
Actionable risk and trend analytics beyond completion rates: Analytics that surface repeat offenders, high-value targets, and measurable exposure, moving beyond completion metrics to give leaders actionable insights tied to real behavior.
Industry-first cross-channel full-message analysis for email, Slack, Teams, and Zoom
Darktrace now brings full-message analysis to Email, Slack, Teams, Zoom, and even generative AI prompts. The same leading behavioral analysis from EMAIL extends to every message, tracing intent, tone, relationships, and conversation flow across all communication activity for a complete understanding of every user interaction.
By correlating messaging and collaboration activity with email and account environments, cross-channel analysis reveals multi-domain attack paths and follows both users and threats as a single, continuous narrative – delivering better context to improve detection across the entire organization.
Eliminate cross-channel blind spots: Detect phishing, malware, account takeovers, and conversational manipulation across email and collaboration platforms, so attackers can’t exploit Slack, Teams, or Zoom as a new entry point. Unified behavioral analysis gives security teams a coherent, single view, for no more fragmented, channel-specific gaps.
Spot generative AI prompt injection attacks before they manipulate assistants: Dedicated models surface threats targeting corporate AI assistants – like ShadowLeak and Hashjack – before they can silently manipulate workflows, reducing risk before static filters catch up.
Industry-first DMARC with bi-directional ASM and email security integration
Darktrace transforms domain protection by linking DMARC, attack surface intelligence, and email security into a single, continuously evolving workflow. Instead of treating domain authentication and exposure as separate tasks, this unified approach shows not just where domains are vulnerable, but how attackers are actively exploiting them.
Fix authentication weaknesses faster: SPF, DKIM, DMARC configurations, and external exposure data are analyzed together, giving teams clear guidance to correct weaknesses before they can be abused. Deep bidirectional integration with attack surface intelligence reduces impersonation risk at the source.
Accelerate email investigations: DMARC context is embedded directly into email workflows, enriching triage with authentication posture, internal/external sender lists, and seamless pivots between email and domain intelligence for faster, more accurate investigations.
Committed to innovation
These updates are part of a broader Darktrace release, which also includes:
Innovations in cloud security with continuous Kubernetes posture management, as well as native integrations with Proactive Exposure Management (PEM) and Attack Surface Management (ASM).
Innovations to Darktrace / Forensic Acquisition & Investigation, including faster cloud incident investigations, automated and on-demand forensic data capture across hybrid environments, and open forensic coverage for third-party endpoint and XDR ecosystems.
Innovations in OT security, including Operational Overview Architecture diagrams, Operational Overview reporting, expanded ICS & IoMT device classification, and expanded OT & IIoT Protocol Coverage.
Join us for an exclusive announcement event where Darktrace, the leader in AI-native cybersecurity, will be announcing our latest innovations, including a demo of our new product / Adaptive Human Defense, an exclusive conversation with a Darktrace customer, and a deep dive into the Darktrace ActiveAI Security Portal.
[1] 84% of organizations still measure security awareness training success through completion rates, a vanity metric with no correlation to behavior change. (Source: NIST Awareness Effectiveness Study, Forrester 2025)
[2] 'Limited benefit from embedded phishing training. Using randomized controlled trials and statistical modeling, embedded training provides a statistically-significant reduction in average failure rate, but of only 2%.' Ho, G., Mirian, A., Luo, E., Tong, K., Lee, E., Liu, L., Longhurst, C. A., Dameff, C., Savage, S., & Voelker, G. M. (2025). Understanding the Efficacy of Phishing Training in Practice. Proceedings of the 2025 IEEE Symposium on Security and Privacy.
![Darktrace’s detection of suspicious SSL connections to retreaw[.]click, indicating an attempted link to Lumma C2 infrastructure.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69c5739b43fdfed6f1b02053_Screenshot%202026-03-26%20at%2010.57.44%E2%80%AFAM.png)
![Darktrace’s detection of a malicious payload being downloaded from the endpoint www.lbfs[.]site.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/69c57465977a5ae3f07c6d69_Screenshot%202026-03-26%20at%2011.01.05%E2%80%AFAM.png)
