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November 7, 2022

[Part 1] Analysis of a Raccoon Stealer v1 Infection

Darktrace’s SOC team observed a fast-paced compromise involving Raccoon Stealer v1. See which steps the Raccoon Stealer v1 took to extract company data!
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
Mark Turner
SOC Shift Supervisor
Written by
Sam Lister
Specialist Security Researcher
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07
Nov 2022

Introduction

Towards the end of March 2022, the operators of Raccoon Stealer announced the closure of the Raccoon Stealer project [1]. In May 2022, Raccoon Stealer v2 was unleashed onto the world, with huge numbers of cases being detected across Darktrace’s client base. In this series of blog posts, we will follow the development of Raccoon Stealer between March and September 2022. We will first shed light on how Raccoon Stealer functioned before its demise, by providing details of a Raccoon Stealer v1 infection which Darktrace’s SOC saw within a client network on the 18th March 2022. In the follow-up post, we will provide details about the surge in Raccoon Stealer v2 cases that Darktrace’s SOC has observed since May 2022.  

What is Raccoon Stealer?

The misuse of stolen account credentials is a primary method used by threat actors to gain initial access to target environments [2]. Threat actors have several means available to them for obtaining account credentials. They may, for example, distribute phishing emails which trick their recipients into divulging account credentials. Alternatively, however, they may install information-stealing malware (i.e, info-stealers) onto users’ devices. The results of credential theft can be devastating. Threat actors may use the credentials to gain access to an organization’s SaaS environment, or they may use them to drain users’ online bank accounts or cryptocurrency wallets. 

Raccoon Stealer is a Malware-as-a-Service (MaaS) info-stealer first publicized in April 2019 on Russian-speaking hacking forums. 

Figure 1: One of the first known mentions of Raccoon Stealer on a Russian-speaking hacking forum named ‘Hack Forums’ on the 13th April 2019

The team of individuals behind Raccoon Stealer provide a variety of services to their customers (known as ‘affiliates’), including access to the info-stealer, an easy-to-use automated backend panel, hosting infrastructure, and 24/7 customer support [3]. 

Once Raccoon Stealer affiliates gain access to the info-stealer, it is up to them to decide how to distribute it. Since 2019, affiliates have been observed distributing the info-stealer via a variety of methods, such as exploit kits, phishing emails, and fake cracked software websites [3]/[4]. Once affiliates succeed in installing Raccoon Stealer onto target systems, the info-stealer will typically seek to obtain sensitive information saved in browsers and cryptocurrency wallets. The info-stealer will then exfiltrate the stolen data to a Command and Control (C2) server. The affiliate can then use the stolen data to conduct harmful follow-up activities. 

Towards the end of March 2022, the team behind Raccoon Stealer publicly announced that they would be suspending their operations after one of their core developers was killed during the Russia-Ukraine conflict [5]. 

Figure 2: Raccoon Stealer resignation post on March 25th 2022

Recent details shared by the US Department of Justice [6]/[7] indicate that it was in fact the arrest, rather than the death, of a key Raccoon Stealer operator which led the Raccoon Stealer team to suspend their operations [8].  

The closure of the Raccoon Stealer project, which ultimately resulted from the FBI-backed dismantling of Raccoon Stealer’s infrastructure in March 2022, did not last long, with the completion of Raccoon Stealer v2 being announced on the Raccoon Stealer Telegram channel on the 17th May 2022 [9]. 

 

Figure 3: Telegram post about new version of Raccoon Stealer

In the second part of this blog series, we will provide details of the recent surge in Raccoon Stealer v2 activity. In this post, however, we will provide insight into how the old version of Raccoon Stealer functioned just before its demise, by providing details of a Raccoon Stealer v1 infection which occurred on the 18th March 2022. 

Attack Details

On the 18th March, at around 13:00 (UTC), a user’s device within a customer’s network was seen contacting several websites providing fake cracked software. 

Figure 4: The above figure — obtained from the Darktrace Event Log for the infected device — highlights its connections to cracked software websites such as ‘licensekeysfree[.]com’ and ‘hdlicense[.]com’ before contacting ‘lion-files[.]xyz’ and ‘www.mediafire[.]com’

The user’s attempt to download cracked software from one of these websites resulted in their device making an HTTP GET request with a URI string containing ‘autodesk-revit-crack-v2022-serial-number-2022’ to an external host named ‘lion-filez[.]xyz’

Figure 5: Screenshot from hdlicense[.]com around the time of the infection shows a “Download” button linking to the ‘lion-filez[.]xyz’ endpoint

The device’s HTTP GET request to lion-filez[.]xyz was immediately followed by an HTTPS connection to the file hosting service, www.mediafire[.]com. Given that threat actors are known to abuse platforms such as MediaFire and Discord CDN to host their malicious payloads, it is likely that the user’s device downloaded the Raccoon Stealer v1 sample over its HTTPS connection to www.mediafire[.]com.  

After installing the info-stealer sample, the user’s device was seen making an HTTP GET request with the URI string ‘/g_shock_casio_easy’ to 194.180.191[.]185. The endpoint responded to the request with data related to a Telegram channel named ‘G-Shock’.

Figure 6: Telegram channel ‘@g_shock_casio_easy’

The returned data included the Telegram channel’s description, which in this case, was a base64 encoded and RC4 encrypted string of characters [10]/[11]. The Raccoon Stealer sample decoded and decrypted this string of characters to obtain its C2 IP address, 188.166.49[.]196. This technique used by Raccoon Stealer v1 closely mirrors the espionage method known as ‘dead drop’ — a method in which an individual leaves a physical object such as papers, cash, or weapons in an agreed hiding spot so that the intended recipient can retrieve the object later on without having to come in to contact with the source. In this case, the operators of Raccoon Stealer ‘left’ the malware’s C2 IP address within the description of a Telegram channel. Usage of this method allowed the operators of Raccoon Stealer to easily change the malware’s C2 infrastructure.  

After obtaining the C2 IP address from the ‘G-Shock’ Telegram channel, the Raccoon Stealer sample made an HTTP POST request with the URI string ‘/’ to the C2 IP address, 188.166.49[.]196. This POST request contained a Windows GUID,  a username, and a configuration ID. These details were RC4 encrypted and base64 encoded [12]. The C2 server responded to this HTTP POST request with JSON-formatted configuration information [13], including an identifier string, URL paths for additional files, along with several other fields. This configuration information was also concealed using RC4 encryption and base64 encoding.  

Figure 7- Fields within the JSON-formatted configuration data [13]

In this case, the server’s response included the identifier string ‘hv4inX8BFBZhxYvKFq3x’, along with the following URL paths:

  • /l/f/hv4inX8BFBZhxYvKFq3x/77d765d8831b4a7d8b5e56950ceb96b7c7b0ed70
  • /l/f/hv4inX8BFBZhxYvKFq3x/0cb4ab70083cf5985b2bac837ca4eacb22e9b711
  • /l/f/hv4inX8BFBZhxYvKFq3x/5e2a950c07979c670b1553b59b3a25c9c2bb899b
  • /l/f/hv4inX8BFBZhxYvKFq3x/2524214eeea6452eaad6ea1135ed69e98bf72979

After retrieving configuration data, the user’s device was seen making HTTP GET requests with the above URI strings to the C2 server. The C2 server responded to these requests with legitimate library files such as sqlite3.dll. Raccoon Stealer uses these libraries to extract data from targeted applications. 

Once the Raccoon Stealer sample had collected relevant data, it made an HTTP POST request with the URI string ‘/’ to the C2 server. This posted data likely included a ZIP file (named with the identifier string) containing stolen credentials [13]. 

The observed infection chain, which lasted around 20 minutes, consisted of the following steps:

1. User’s device installs Raccoon Stealer v1 samples from the user attempting to download cracked software

2. User’s device obtains the info-stealer’s C2 IP address from the description text of a Telegram channel

3. User’s device makes an HTTP POST request with the URI string ‘/’ to the C2 server. The request contains a Windows GUID,  a username, and a configuration ID. The response to the request contains configuration details, including an identifier string and URL paths for additional files

4. User’s device downloads library files from the C2 server

5. User’s device makes an HTTP POST request with the URI string ‘/’ to the C2 server. The request contains stolen data

Darktrace Coverage 

Although RESPOND/Network was not enabled on the customer’s deployment, DETECT picked up on several of the info-stealer’s activities. In particular, the device’s downloads of library files from the C2 server caused the following DETECT/Network models to breach:

  • Anomalous File / Masqueraded File Transfer
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Zip or Gzip from Rare External Location
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Multiple EXE from Rare External Locations
Figure 8: Event Log for the infected device shows 'Anomalous File / Masqueraded File Transfer' model breach after the device's download of a library file from the C2 server

Since the customer was subscribed to the Darktrace Proactive Threat Notification (PTN) service, they were proactively notified of the info-stealer’s activities. The quick response by Darktrace’s 24/7 SOC team helped the customer to contain the infection and to prevent further damage from being caused. Having been alerted to the info-stealer activity by the SOC team, the customer would also have been able to change the passwords for the accounts whose credentials were exfiltrated.

If RESPOND/Network had been enabled on the customer’s deployment, then it would have blocked the device’s connections to the C2 server, which would have likely prevented any stolen data from being exfiltrated.

Conclusion

Towards the end of March 2022, the team behind Raccoon Stealer announced that they would be suspending their operations. Recent developments suggest that the arrest of a core Raccoon Stealer developer was responsible for this suspension. Just before the Raccoon Stealer team were forced to shut down, Darktrace’s SOC team observed a Raccoon Stealer infection within a client’s network. In this post, we have provided details of the network-based behaviors displayed by the observed Raccoon Stealer sample. Since these v1 samples are no longer active, the details provided here are only intended to provide historical insight into the development of Raccoon Stealer’s operations and the activities carried out by Raccoon Stealer v1 just before its demise. In the next post of this series, we will discuss and provide details of Raccoon Stealer v2 — the new and highly prolific version of Raccoon Stealer. 

Thanks to Stefan Rowe and the Threat Research Team for their contributions to this blog.

References

[1] https://twitter.com/3xp0rtblog/status/1507312171914461188

[2] https://www.gartner.com/doc/reprints?id=1-29OTFFPI&ct=220411&st=sb

[3] https://www.cybereason.com/blog/research/hunting-raccoon-stealer-the-new-masked-bandit-on-the-block

[4] https://www.cyberark.com/resources/threat-research-blog/raccoon-the-story-of-a-typical-infostealer

[5] https://www.bleepingcomputer.com/news/security/raccoon-stealer-malware-suspends-operations-due-to-war-in-ukraine/

[6] https://www.justice.gov/usao-wdtx/pr/newly-unsealed-indictment-charges-ukrainian-national-international-cybercrime-operation

[7] https://www.youtube.com/watch?v=Fsz6acw-ZJY

[8] https://riskybiznews.substack.com/p/raccoon-stealer-dev-didnt-die-in

[9] https://medium.com/s2wblog/raccoon-stealer-is-back-with-a-new-version-5f436e04b20d

[10] https://blog.cyble.com/2021/10/21/raccoon-stealer-under-the-lens-a-deep-dive-analysis/

[11] https://decoded.avast.io/vladimirmartyanov/raccoon-stealer-trash-panda-abuses-telegram/

[12] https://blogs.blackberry.com/en/2021/09/threat-thursday-raccoon-infostealer

[13] https://cyberint.com/blog/research/raccoon-stealer/

Appendices

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
Mark Turner
SOC Shift Supervisor
Written by
Sam Lister
Specialist Security Researcher

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Proactive Security

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January 7, 2026

How a leading bank is prioritizing risk management to power a resilient future

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As one of the region’s most established financial institutions, this bank sits at the heart of its community’s economic life – powering everything from daily transactions to business growth and long-term wealth planning. Its blend of physical branches and advanced digital services gives customers the convenience they expect and the personal trust they rely on. But as the financial world becomes more interconnected and adversaries more sophisticated, safeguarding that trust requires more than traditional cybersecurity. It demands a resilient, forward-leaning approach that keeps pace with rising threats and tightening regulatory standards.

A complex risk landscape demands a new approach

The bank faced a challenge familiar across the financial sector: too many tools, not enough clarity. Vulnerability scans, pen tests, and risk reports all produced data, yet none worked together to show how exposures connected across systems or what they meant for day-to-day operations. Without a central platform to link and contextualize this data, teams struggled to see how individual findings translated into real exposure across the business.

  • Fragmented risk assessments: Cyber and operational risks were evaluated in silos, often duplicated across teams, and lacked the context needed to prioritize what truly mattered.
  • Limited executive visibility: Leadership struggled to gain a complete, real-time view of trends or progress, making risk ownership difficult to enforce.
  • Emerging compliance pressure: This gap also posed compliance challenges under the EU’s Digital Operational Resilience Act (DORA), which requires financial institutions to demonstrate continuous oversight, effective reporting, and the ability to withstand and recover from cyber and IT disruptions.
“The issue wasn’t the lack of data,” recalls the bank’s Chief Technology Officer. “The challenge was transforming that data into a unified, contextualized picture we could act on quickly and decisively.”

As the bank advanced its digital capabilities and embraced cloud services, its risk environment became more intricate. New pathways for exploitation emerged, human factors grew harder to quantify, and manual processes hindered timely decision-making. To maintain resilience, the security team sought a proactive, AI-powered platform that could consolidate exposures, deliver continuous insight, and ensure high-value risks were addressed before they escalated.

Choosing Darktrace to unlock proactive cyber resilience

To reclaim control over its fragmented risk landscape, the bank selected Darktrace / Proactive Exposure Management™ for cyber risk insight. The solution’s ability to consolidate scanner outputs, pen test results, CVE data, and operational context into one AI-powered view made it the clear choice. Darktrace delivered comprehensive visibility the team had long been missing.

By shifting from a reactive model to proactive security, the bank aimed to:

  • Improve resilience and compliance with DORA
  • Prioritize remediation efforts with greater accuracy
  • Eliminate duplicated work across teams
  • Provide leadership with a complete view of risk, updated continuously
  • Reduce the overall likelihood of attack or disruption

The CTO explains: “We needed a solution that didn’t just list vulnerabilities but showed us what mattered most for our business – how risks connected, how they could be exploited, and what actions would create the biggest reduction in exposure. Darktrace gave us that clarity.”

Targeting the risks that matter most

Darktrace / Proactive Exposure Management offered the bank a new level of visibility and control by continuously analyzing misconfigurations, critical attack paths, human communication patterns, and high-value assets. Its AI-driven risk scoring allowed the team to understand which vulnerabilities had meaningful business impact, not just which were technically severe.

Unifying exposure across architectures

Darktrace aggregates and contextualizes data from across the bank’s security stack, eliminating the need to manually compile or correlate findings. What once required hours of cross-team coordination now appears in a single, continuously updated dashboard.

Revealing an adversarial view of risk

The solution maps multi-stage, complex attack paths across network, cloud, identity systems, email environments, and endpoints – highlighting risks that traditional CVE lists overlook.

Identifying misconfigurations and controlling gaps

Using Self-Learning AI, Darktrace / Proactive Exposure Management spots misconfigurations and prioritizes them based on MITRE adversary techniques, business context, and the bank’s unique digital environment.

Enhancing red-team and pen test effectiveness

By directing testers to the highest-value targets, Darktrace removes guesswork and validates whether defenses hold up against realistic adversarial behavior.

Supporting DORA compliance

From continuous monitoring to executive-ready reporting, the solution provides the transparency and accountability the bank needs to demonstrate operational resilience frameworks.

Proactive security delivers tangible outcomes

Since deploying Darktrace / Proactive Exposure Management, the bank has significantly strengthened its cybersecurity posture while improving operational efficiency.

Greater insight, smarter prioritization, stronger defensee

Security teams are now saving more than four hours per week previously spent aggregating and analyzing risk data. With a unified view of their exposure, they can focus directly on remediation instead of manually correlating multiple reports.

Because risks are now prioritized based on business impact and real-time operational context, they no longer waste time on low-value tasks. Instead, critical issues are identified and resolved sooner, reducing potential windows for exploitation and strengthening the bank’s ongoing resilience against both known and emerging threats.

“Our goal was to move from reactive to proactive security,” the CTO says. “Darktrace didn’t just help us achieve that, it accelerated our roadmap. We now understand our environment with a level of clarity we simply didn’t have before.”

Leadership clarity and stronger governance

Executives and board stakeholders now receive clear, organization-wide visibility into the bank’s risk posture, supported by consistent reporting that highlights trends, progress, and areas requiring attention. This transparency has strengthened confidence in the bank’s cyber resilience and enabled leadership to take true ownership of risk across the institution.

Beyond improved visibility, the bank has also deepened its overall governance maturity. Continuous monitoring and structured oversight allow leaders to make faster, more informed decisions that strategically align security efforts with business priorities. With a more predictable understanding of exposure and risk movement over time, the organization can maintain operational continuity, demonstrate accountability, and adapt more effectively as regulatory expectations evolve.

Trading stress for control

With Darktrace, leaders now have the clarity and confidence they need to report to executives and regulators with accuracy. The ability to see organization-wide risk in context provides assurance that the right issues are being addressed at the right time. That clarity is also empowering security analysts who no longer shoulder the anxiety of wondering which risks matter most or whether something critical has slipped through the cracks. Instead, they’re working with focus and intention, redirecting hours of manual effort into strategic initiatives that strengthen the bank’s overall resilience.

Prioritizing risk to power a resilient future

For this leading financial institution, Darktrace / Proactive Exposure Management has become the foundation for a more unified, data-driven, and resilient cybersecurity program. With clearer, business-relevant priorities, stronger oversight, and measurable efficiency gains, the bank has strengthened its resilience and met demanding regulatory expectations without adding operational strain.

Most importantly, it shifted the bank’s security posture from a reactive stance to a proactive, continuous program. Giving teams the confidence and intelligence to anticipate threats and safeguard the people and services that depend on them.

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Kelland Goodin
Product Marketing Specialist

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AI

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December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

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Introduction: 2026 cyber trends

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk

In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy

Prompt Injection moves from theory to front-page breach

We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken

When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact

One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target

Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy

Increased commercialization of generative AI and AI assistants in cyber attacks

One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

-- Toby Lewis, Global Head of Threat Analysis

Conclusion

Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

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