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July 22, 2020

Resurgence of Ursnif Banking Trojan "May's Most Wanted Malware"

The Ursnif banking trojan tries to blend into the network as legitimate Zoom and Webex activity, trying to capture credentials. See how Darktrace stops it!
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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22
Jul 2020

Earlier this month, Darktrace’s Cyber AI detected the Ursnif banking trojan, described as May’s most wanted malware, making a resurgence across its customers’ networks. This blog follows the malicious activity in one financial services company in the US, detailing how and why Darktrace Antigena stepped in and autonomously stopped the attack in real time.

Banking trojans continue to present a credible and persistent threat to organizations of all sizes across the globe. This attack was delivered via phishing email, which initiated a download of an executable file masquerading as a .cab extension.

This specific banking trojan is particularly sophisticated, with multiple new command and control (C2) domains registered – identifiable because several distinct Domain Generation Algorithms (DGA) were observed across different networks – the majority of which were only registered the day prior to the campaign.

Figure 1: A timeline of the attack

Phishing email catches organizations unaware

The malware itself was delivered via phishing email. The attack was not recognized by antivirus solutions at the time of delivery, slipping through the organization’s perimeter solutions and landing in employees’ inboxes. Unknowingly, an employee opened a disguised attachment containing macros, downloading an executable file masquerading as a .cab extension.

Interestingly, the malware also used new User Agents imitating Zoom and Webex, a clear attempt to blend in with assumed network traffic. After the malware was downloaded, several devices were observed making connections using these Zoom or Webex User Agents to non-Zoom and non-Webex domains, another attempt to blend in.

Figure 2: Darktrace’s Breach Event Log shows a number of models were triggered

Figure 3: Darktrace’s Device Event Log showing the device was connected to Outlook at the time of the executable file download

After the downloads, Darktrace’s AI observed beaconing to rare DGA domains. The majority of these domains were Russian and registered within the previous 24 hours.

Figure 4: A screenshot taken from one of the C2 domains observed, tobmojiol2adf[.]com, which appears to host a login page

Figure 5: The External Sites Summary of one of the C2 domains observed, tobmojiol2adf[.]com, which was identified as 100% rare for the network at the time of the model breach.

This attack managed to evade the rest of the organization’s security stack since the domains observed were recently registered and the majority of the file hashes and IoCs had not yet been flagged by OSINT tools, thus bypassing all signature-based detections. The initial file downloads also purported to be .cab files, but Darktrace’s AI identified that these were in fact executable files.

Multiple Darktrace detections, including the ‘Masqueraded File Transfer’ model and the ‘Initial Breach Chain Compromise’ model, alerted the security team to this activity. At the same time, the models triggered Darktrace’s Cyber AI Analyst to launch an automated investigation into the security incident, which surfaced additional vital information and dramatically reduced time to triage.

Figure 6: The Cyber AI Analyst output showing the subsequent C2 connections made by the device after the executable file download

Figure 7: Model breaches from the affected device, showing the malicious file download and subsequent command and control beaconing activity

Figure 8: Model Breach Event Log, showing Antigena’s response after the masqueraded file download and a new outbound connection

The case for Autonomous Response

The Ursnif banking trojan presents a particularly lethal threat: silent, stealthy, and capable of stealing vital financial information, email credentials, and other sensitive data at machine speeds. The rise of advanced malware like this demonstrates the need for security technology that can stay ahead of attackers. For this organization, the malware download and subsequent command and control activity could have represented the start of a costly attack.

Luckily the organization had Antigena Network installed in active mode. The C2 communications from infected devices were blocked seconds after the initial connection, preventing further C2 activity and the download of any additional malware. Using information surfaced by the Cyber AI Analyst, the security team could catch up and the threat was quickly contained.

This attack highlights the continuously evolving approaches used by malicious actors to evade detection. In the same week as the events explained above, Darktrace identified the Urnsnif malware in numerous other customers in the US and Italy, across multiple industries. Attackers are targeting businesses indiscriminately and are not slowing down.

Thanks to Darktrace analysts Grace Carballo and Hiromi Watanabe for their insights on the above threat find.

Technical details

IoCs:

Commenttobmojiol2adf[.]com – C2 domain, registered July 9
qumogtromb2a[.]com – Not yet registered
amehota2gfgh[.]com – C2 domain, registered July 8
gofast22gfor[.]com – C2 domain, registered July 8
xquptbabzxhxw[.]com – Not yet registered
e9bja[.]com

Masqueraded file download source9ygw2[.]com
Masqueraded file download sourcen2f79[.]com
Masqueraded file download sourceioyyf[.]com
Masqueraded file download sourcehq3ll[.]com
Masqueraded file download sourcehxxp://9ygw2[.]com/iz5/yaca.php?l=kpt1.cab
File path hxxp://e9bja[.]com/iz5/yaca.php?l=kpt4.cab
File path hxxp://n2f79[.]com/iz5/yaca.php?l=kpt1.cab
File path hxxp://ioyyf[.]com/iz5/yaca.php?l=kpt4.cab
File path hxxp://hq3ll[.]com/iz5/yaca.php?l=kpt12.cabFile path

MD5 hashes

  • fa6fc057b3c1bb1e84cc37dbd14e7c10
  • 37c28815f462115ff1439e251324ed5b
  • 40f69d093a720c338963bebb3e274593
  • 5602508f262b92f25dc36c4266f410b4
  • 619e5f5d56de5dfbe7b76bba924fd631
  • 30ea60c337c5667be79539f26b613449
  • 688380643b0d70a0191b7fbbea6fb313
  • 719f36d41379574569248e599767937f
  • 7a7ba75af1210e707c495990e678f83e
  • 7c4207591c6d07ce1c611a8bc4b61898
  • 8eec0a8518e87d7248d2882c6f05a551
  • 94915a540ce01fabec9ba1e7913837ea
  • 94e6d6c3cef950ed75b82428475681c7
  • bac0246599a070c8078a966d11f7089d
  • dc17489e558d0f07b016636bc0ab0dbe
  • dff18317acadc40e68f76d3b33ea4304
  • cee72b840f4e79ed5ffde7adc680a7cd

SHA1 hashes

  • 42dd5e8ad3f0d4de95eaa46eef606e24f3d253f0
  • 97d2158a44b0eaa2465f3062413427e33cc2ac50
  • 435c5ae175b40e5d64907bdb212290af607232eb
  • 4b9845e5e7475156efa468a4e58c3c72cf0d4e7e
  • a0494bf812cf1a5b075109fea1adc0d8d1f236f9
  • 297b1b5137249a74322330e80d478e68e70add0d
  • 46a9c4679169d46563cdebae1d38e4a14ed255c9
  • 4f4f65acf3a35da9b8da460cf7910cd883fe2e46
  • 60aee8045e0eb357b88db19775c0892f6bd388f1
  • 7d92dad4971d3c2abfc368a8f47049032ef4d8a9
  • 9631216035a58d1c3d4404607bd85bf0c80ccfe8
  • aab6a948d500de30b6b75a928f43891f5daaa2a8
  • c31dcf7bc391780ecf1403d504af5e844821e9a4
  • c41a9a7f416569a7f412d1a82a78f7977395ce2a
  • c7323a5596be025c693535fbb87b84beeacc7733
  • d64a6c135d7eac881db280c4cb04443b7d2e2a0b
  • 331ede8915e42d273722802a20e8bb9a448b39c5

Darktrace model breaches

  • Anomalous File/Masqueraded File Transfer
  • Compromise/ Sustained TCP Beaconing Activity to Rare Endpoint
  • Compromise/ HTTP Beaconing to Rare Destination
  • Compromise/ Slow Beaconing Activity to External rare
  • Compromise/ Beaconing Activity to External Rare
  • Device/ Initial Breach Chain Compromise
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
Senior Director of Product
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