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September 21, 2020

The Rise of Stealthy Malware in Public Organizations

Gain insights into how malware attempts to infiltrate public organizations to steal data and the defenses needed to combat these threats.
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
Max Heinemeyer
Global Field CISO
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21
Sep 2020

Cyber AI was recently deployed at a government organization in the EMEA region, where it was protecting over 10,000 devices by learning a sense of ‘self’ for each unique device in order to detect anomalous behavior. Just a week into the Darktrace trial, the AI detected a device which had been infected with malware beaconing to C2 endpoints via HTTP and SSL before downloading a suspicious file.

The attackers were using a strain of Glupteba malware in an attempt to steal sensitive information from browsers such as passwords and credit card information, as well as email account credentials. Given that this was a government agency, the consequences had the attackers been able to gain access to an employees’ account credentials could have been severe.

Darktrace’s Autonomous Response technology, Antigena, would have taken action to contain the threatening behavior, enforcing the device’s ‘pattern of life’ for five minutes and escalating its response as the severity of the threat escalated.

The attack occurred over the course of an hour on a Sunday, meaning the security team’s response time was likely slower than it would have been during a weekday.

Figure 1: A timeline of events

Details of the attack

Darktrace detected a device initiating encrypted connections to an external domain never seen before across the organization. The device had likely been infected before Darktrace was deployed, most likely through a malicious email attachment or link.

Newer strains of Glupteba also use malvertising which directs the user to a rare endpoint and forces an anomalous file download.

Darktrace’s AI detected the device downloading an executable file, atx777.exe, which appears to be associated with the stealer Taurus, accredited to the cyber-criminal group ‘Predator the Thief’.

Following this file download, the device initiated further encrypted connections to suspicious endpoints over unusual communication channels. At the same time, the device downloaded another executable file from a domain with an unusual user agent, ‘CertUtil URL Agent’.

A stealthy stealer

Malicious actors are using more sophisticated techniques to avoid traditional security tools. The Glupteba malware framework, which has seen a resurgence over the past few months, utilizes several evasion techniques, including sandbox detection.

Shortly after the payload is dropped, the malware examines the environment where it has been installed and will not execute any further processes if it detects the host machine is a sandbox. The malware is able to further conceal itself by excluding Glupteba files from Windows Defender, altering Firewall rules to allow command and control traffic, and by ‘Living off the Land,’ using tools preinstalled on the device such as CertUtil.

Despite these attempts at evasion, Darktrace’s Cyber AI easily detected the suspicious activity, which fell outside the ‘pattern of life’ for the device and the wider organization. Darktrace identified the activity as suspicious at the first stages of the attack, and the Cyber AI Analyst investigated the incident in full, revealing some crucial metrics, including the endpoints contacted.

Figure 2: AI Analyst’s detection and summary of the command and control traffic

Antigena responds

In this case, the malware had been installed on the device before Darktrace started monitoring the environment, however had Antigena been active it would have taken a precise response at every stage of the attack. At the beginning of the attack, Antigena would have blocked connections to the suspicious domain, zvwxstarserver17km[.]xyz for two hours, preventing any additional malicious downloads.

As the activity escalated, Antigena would have enforced a ‘pattern of life’ on the infected device and stopped any malicious command and control communications by blocking all outgoing traffic for one hour.

Concluding thoughts

As the race between cyber-criminals and security analysts continues, malware authors are employing increasingly sophisticated techniques to avoid detection. Although the Taurus stealer utilizes a number of these evasion techniques, Darktrace’s AI technology was able to not only alert and act on the malicious activity without disrupting business continuity, but did so despite the malware already being present on a device before the customer began leveraging Darktrace for cyber defense.

Had Antigena been deployed in active mode during this incident, it would have stopped the malware in its tracks at the initial stages, preventing any sensitive data from being removed from the government network. Critically, Antigena updated and escalated its actions in light of the evolving activity, and yet was still precise enough to ensure normal business operations were allowed to continue.

Despite Antigena being in passive mode, this case study demonstrates the power of Autonomous Response in intelligently acting to stop cyber-threats when human security resources are limited, or when the team is out of office. As both public and private organizations continue to be targeted with ransomware and other fast and stealthy threats, the need for Autonomous Response is greater than ever.

Thanks to Darktrace analyst Tom Priest for his insights on the above threat find.

Learn more about Darktrace Antigena

Darktrace model detections

  • Device / New Failed External Connections
  • Device / New User Agent and New IP
  • Antigena / Network::External Threat::Antigena Suspicious File Block
  • Anomalous File / EXE from Rare External Location
  • Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach
  • Antigena / Network::External Threat::Antigena File then New Outbound Block
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Device / Long Agent Connection to New Endpoint
  • Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block
  • Anomalous Connection / Lots of New Connections
  • Device / Large Number of Model Breaches
  • Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block
  • Device / Initial Breach Chain Compromise
  • Antigena / Network::External Threat::Antigena Suspicious Activity Block
  • Compliance / CertUtil External Connection

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
Max Heinemeyer
Global Field CISO

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June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider.  “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”  

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls.  While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader  at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

  • Credential-based, not malware-based
  • Behavioral, not signature-based
  • Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

  • Trusted sessions
  • Legitimate services
  • Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

  • Establish a baseline of normal behavior
  • Detect subtle anomalies in real time
  • Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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May 28, 2026

From Efficiency to Exposure: How AI Adoption Is Creating Unseen Vulnerabilities on the Factory Floor

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How AI agents impact the manufacturing industry

Security teams and IT personnel across the manufacturing industry are under constant pressure to protect production, maintain uptime, and safeguard critical assets but the rise of AI is bringing huge new opportunities alongside new cyber risks. Across manufacturing, AI is embedded into workflows, decision-making, and increasingly, autonomous AI agents are acting on behalf of employees and systems.  

Agentic systems are powerful because they can act independently, but that same autonomy also creates cyber and operational risk. Agents have extensive permissions and are capable of carrying out complex tasks, making decisions, and interacting with tools or external systems with little to no human intervention.

Unlike traditional AI models that perform predefined tasks, AI agents use advanced techniques to mimic human decision-making processes, dynamically adapting to new challenges, making decision and taking action based on their own judgement. They look like employees operationally but lack judgment, ethics, or fear of consequences like humans do. This means they can be easily manipulated by cybercriminals, and an AI agent embedded across an OT network creates threats that extend well beyond data exposure. For example, at BMW, AI identifies faults in welding processes as they occur. At its Spartanburg plant, AI monitors the weld of 300-400 metal studs onto every SUV frame to detect misplaced or faulty studs and correct them instantly. Corruption of BMW’s AI system could lead to catastrophic quality control errors.

Adopting agentic AI systems across manufacturing raises some concerns across security teams. New data from our State of AI Cybersecurity survey shows that 78% of manufacturing security professionals are worried about employee use of AI agents – their top concern. That’s followed by employee use of generative AI tools like CoPilot and ChatGPT, a worry for 76% of security professionals at manufacturing organizations. As these tools gain more access to business data and processes, and more autonomy within organizations, security teams, who today have minimal visibility of agent activity in their environments, increasingly have sensitive data exposure (a worry for 60%) and accidental policy and regulatory violations (59%) on their minds.

External AI-powered threats are evolving just as quickly

The same capabilities transforming manufacturing are also reshaping cyberattacks.

AI is enabling attackers to automate reconnaissance, refine targeting, and adapt in real time. What once required time and manual effort can now be executed continuously and at scale. Manufacturers are already seeing the impact. According to manufacturing security professionals we surveyed, 76% are already being impacted by AI-powered threats and 90% see AI increasing the success of social engineering attacks.

And the techniques themselves are evolving. Concerns across the manufacturing sector show growing anxiety about the range of AI-powered attack routes, most pressingly of adaptive malware that evolves in real-time – a prospect half (49%) of manufacturing security professionals we surveyed are worried by, a full 9% more than the average across industries. AI adaptive malware is followed by:

  • Automated vulnerability scanning and exploit chaining (48%) which has become even more pressing as Anthropic’s new Mythos AI Model supercharges vulnerability discovery
  • Hyper-personalized phishing campaigns (46%), which remain a mainstay in hackers’ arsenals, and AI has amplified their effectiveness by making phishing emails more convincing and harder to detect.

This is not just an increase in volume, it is a shift toward threats that evolve as they unfold - often faster than static defenses can respond.

Despite rising awareness, many manufacturers are not yet equipped to manage this shift. More than half (51%) say they are not adequately prepared for AI-driven threats, and only 37% have formal policies governing AI deployment.  

Securing AI through visibility, context, and guardrails

Addressing this challenge does not require manufacturers to slow innovation. It requires a different approach to security, one that can operate at the same speed and scale as AI. Three specific priorities are emerging for manufacturers looking to take advantage of the power of AI.

Visibility is foundational.  

Organizations need to understand where AI is being used, what it can access, and how it behaves across both IT and OT environments. Without that, risk cannot be measured or managed. It is no surprise that Darktrace’s research found that 91% of manufacturing security professionals said that they need to understand how AI makes decisions before trusting it. This is even more critical in operational settings where disruption has safety, environmental, financial, and reputational impacts.

Context is what turns visibility into action.  

In environments shaped by AI, normal behavior is constantly shifting. Detecting threats requires a behavioral approach; understanding patterns of life across the organization and identifying subtle deviations in real time – a step change in organizations’ traditional approach to security and risk management.

Guardrails ensure that agency does not become exposure  

As AI systems take on greater responsibility, organizations need clear boundaries around what they can do and when they can act independently. These controls must be embedded into systems themselves, not applied after the fact.  

Securing AI Agents Across Manufacturing IT and OT

The rise of agentic AI is transforming manufacturing - powering next-generation operations while reshaping the security landscape. This is not just an increase in threats, but a shift to autonomous systems, continuously evolving behaviors, and risks moving at machine speed. For organizations trying to grapple with the challenge of enabling AI while managing the risk, visibility, context and guardrails should be foundational.

Darktrace helps manufacturers build secure AI approaches by making those foundations possible. It provides visibility and real-time detection and response to unusual activity across IT and OT environments and allows organizations to understand AI activity from the prompts employees use and the agents they build to how those agents are behaving across the environment. For manufacturers scaling AI, this delivers a foundation for innovation without sacrificing control.

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About the author
Oakley Cox
Director of Product
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