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June 23, 2023

How Darktrace Quickly Foiled An Information Stealer

Discover how Darktrace thwarted the CryptBot malware in just 2 seconds. Learn about this fast-moving threat and the defense strategies employed.
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
Alexandra Sentenac
Cyber Analyst
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23
Jun 2023

The recent trend of threat actors using information stealer malware, designed to gather and exfiltrate confidential data, shows no sign of slowing. With new or updated info-stealer strains appearing in the wild on a regular basis, it came as no surprise to see a surge in yet another prolific variant in late 2022, CryptBot.

What is CryptBot?

CryptBot is a Windows-based trojan malware that was first discovered in the wild in December 2019. It belongs to the prolific category of information stealers whose primary objective, as the name suggests, is to gather information from infected devices and send it to the threat actor.

ZeuS was reportedly the first info-stealer to be discovered, back in 2006. After its code was leaked, many other variants came to light and have been gaining popularity amongst cyber criminals [1] [2] [3]. Indeed, Inside the SOC has discussed multiple infections across its customer base associated with several types of stealers in the past months [4] [5] [6] [7]. 

The Darktrace Threat Research team investigated CryptBot infections on the digital environments of more than 40 different Darktrace customers between October 2022 and January 2023. Darktrace DETECT™ and its anomaly-based approach to threat detection allowed it to successfully identify the unusual activity surrounding these info-stealer infections on customer networks. Meanwhile, Darktrace RESPOND™, when enabled in autonomous response mode, was able to quickly intervene and prevent the exfiltration of sensitive company data.

Why is info-stealer malware popular?

It comes as no surprise that info-stealers have “become one of the most discussed malware types on the cybercriminal underground in 2022”, according to Accenture’s Cyber Threat Intelligence team [10]. This is likely in part due to the fact that:

More sensitive data on devices

Due to the digitization of many aspects of our lives, such as banking and social interactions, a trend accelerated by the COVID-19 pandemic.

Cost effective

Info-stealers provide a great return on investment (ROI) for threat actors looking to exfiltrate data without having to do the traditional internal reconnaissance and data transfer associated with data theft. Info-stealers are usually cheap to purchase and are available through Malware-as-a-Service (MaaS) offerings, allowing less technical and resourceful threat actors in on the stealing action. This makes them a prevalent threat in the malware landscape. 

How does CryptBot work?

The techniques employed by info-stealers to gather and exfiltrate data as well as the type of data targeted vary from malware to malware, but the data targeted typically includes login credentials for a variety of applications, financial information, cookies and global information about the infected computer [8]. Given its variety and sensitivity, threat actors can leverage the stolen data in several ways to make a profit. In the case of CryptBot, the data obtained is sold on forums or underground data marketplaces and can be later employed in higher profile attacks [9]. For example, stolen login information has previously been leveraged in credential-based attacks, which can successfully bypass authentication-based security measures, including multi-factor authentication (MFA). 

CryptBot functionalities

Like many information stealers, CryptBot is designed to steal a variety of sensitive personal and financial information such as browser credentials, cookies and history information and social media accounts login information, as well as cryptocurrency wallets and stored credit card information [11]. General information (e.g., OS, installed applications) about the infected computer is also retrieved. Browsers targeted by CryptBot include Chrome, Firefox, and Edge. In early 2022, CryptBot’s code was revamped in order to streamline its data extraction capabilities and improve its overall efficiency, an update that coincided with a rise in the number of infections [11] [12].

Some of CryptBot's functionalities were removed and its exfiltration process was streamlined, which resulted in a leaner payload, around half its original size and a quicker infection process [11]. Some of the features removed included sandbox detection and evasion functionalities, the collection of desktop text files and screen captures, which were deemed unnecessary. At the same time, the code was improved in order to include new Chrome versions released after CryptBot’s first appearance in 2019. Finally, its exfiltration process was simplified: prior to its 2022 update, the malware saved stolen data in two separate folders before sending it to two separate command and control (C2) domains. Post update, the data is only saved in one location and sent to one C2 domain, which is hardcoded in the C2 transmission function of the code. This makes the infection process much more streamlined, taking only a few minutes from start to finish. 

Aside from the update to its malware code, CryptBot regularly updates and refreshes its C2 domains and dropper websites, making it a highly fluctuating malware with constantly new indicators of compromise and distribution sites. 

Even though CryptBot is less known than other info-stealers, it was reportedly infecting thousands of devices daily in the first months of 2020 [13] and its continued prevalence resulted in Google taking legal action against its distribution infrastructure at the end of April 2023 [14].  

How is CryptBot obtained?

CryptBot is primarily distributed through malicious websites offering free and illegally modified software (i.e., cracked software) for common commercial programs (e.g., Microsoft Windows and Office, Adobe Photoshop, Google Chrome, Nitro PDF Pro) and video games. From these ‘malvertising’ pages, the user is redirected through multiple sites to the actual payload dropper page [15]. This distribution method has seen a gain in popularity amongst info-stealers in recent months and is also used by other malware families such as Raccoon Stealer and Vidar [16] [17].

A same network of cracked software websites can be used to download different malware strains, which can result in multiple simultaneous infections. Additionally, these networks often use search engine optimization (SEO) in order to make adverts for their malware distributing sites appear at the top of the Google search results page, thus increasing the chances of the malicious payloads being downloaded.

Furthermore, CryptBot leverages Pay-Per-Install (PPI) services such as 360Installer and PrivateLoader, a downloader malware family used to deliver payloads of multiple malware families operated by different threat actors [18] [19] [20]. The use of this distribution method for CryptBot payloads appears to have stemmed from its 2022 update. According to Google, 161 active domains were associated with 360Installer, of which 90 were associated with malware delivery activities and 29 with the delivery of CryptBot malware specifically. Google further identified hundreds of domains used by CryptBot as C2 sites, all of which appear to be hosted on the .top top-level domain [21].

This simple yet effective distribution tactic, combined with the MaaS model and the lucrative prospects of selling the stolen data resulted in numerous infections. Indeed, CryptBot was estimated to have infected over 670,000 computers in 2022 [14]. Even though the distribution method chosen means that most of the infected devices are likely to be personal computers, bring your own device (BYOD) policies and users’ tendency to reuse passwords means that corporate environments are also at risk. 

CryptBot Attack Overview

In some cases observed by Darktrace, after connecting to malvertising websites, devices were seen making encrypted SSL connections to file hosting services such as MediaFire or Mega, while in others devices were observed connecting to an endpoint associated with a content delivery network. This is likely the location from where the malware payload was downloaded alongside cracked software, which is executed by the unsuspecting user. As the user expects to run an executable file to install their desired software, the malware installation often happens without the user noticing.

Some of the malvertising sites observed by Darktrace on customer deployments were crackful[.]com, modcrack[.]net, windows-7-activator[.]com and office-activator[.]com. However, in many cases detected by Darktrace, CryptBot was propagated via websites offering trojanized KMSPico software (e.g., official-kmspico[.]com, kmspicoofficial[.]com). KMSPico is a popular Microsoft Windows and Office product activator that emulates a Windows Key Management Services (KMS) server to activate licenses fraudulently. 

Once it has been downloaded and executed, CryptBot will search the system for confidential information and create a folder with a seemingly randomly generated name, matching the regex [a-zA-Z]{10}, to store the gathered sensitive data, ready for exfiltration. 

Figure 1: Packet capture (PCAP) of an HTTP POST request showing the file with the stolen data being sent over the connection.
Figure 1: Packet capture (PCAP) of an HTTP POST request showing the file with the stolen data being sent over the connection.

This data is then sent to the C2 domain via HTTP POST requests on port 80 to the URI /gate.php. As previously stated, CryptBot C2 infrastructure is changed frequently and many of the domains seen by Darktrace had been registered within the previous 30 days. The domain names detected appeared to have been generated by an algorithm, following the regex patterns [a-z]{6}[0-9]{2,3}.top or [a-z]{6}[0-9]{2,3}.cfd. In several cases, the C2 domain had not been flagged as malicious by other security vendors or had just one detection. This is likely because of the frequent changes in the C2 infrastructure operated by the threat actors behind CryptBot, with new malicious domains being created periodically to avoid detection. This makes signature-based security solutions much less efficient to detect and block connections to malicious domains. Additionally, the fact that the stolen data is sent over regular HTTP POST requests, which are used daily as part of a multitude of legitimate processes such as file uploads or web form submissions, allows the exfiltration connections to blend in with normal and legitimate traffic making it difficult to isolate and detect as malicious activity. 

In this context, anomaly-based security detections such as Darktrace DETECT are the best way to pick out these anomalous connections amidst legitimate Internet traffic. In the case of CryptBot, two DETECT models were seen consistently breaching for CryptBot-related activity: ‘Device / Suspicious Domain’, breaching for connections to 100% rare C2 .top domains, and ‘Anomalous Connection / POST to PHP on New External Host’, breaching on the data exfiltration HTTP POST request. 

In deployments where Darktrace RESPOND was deployed, a RESPOND model breached within two seconds of the first HTTP POST request. If enabled in autonomous mode, RESPOND would block the data exfiltration connections, thus preventing the data safe from being sold in underground forums to other threat actors. In one of the cases investigated by Darktrace’s Threat Research team, DETECT was able to successfully identify and alert the customer about CryptBot-related malicious activity on a device that Darktrace had only begun to monitor one day before, showcasing how fast Darktrace’s Self-Learning AI learns every nuance of customer networks and the devices within it.

In most cases investigated by Darktrace, fewer than 5 minutes elapsed between the first connection to the endpoint offering free cracked software and the data being exfiltrated to the C2 domain. For example, in one of the attack chains observed in a university’s network, a device was seen connecting to the 100% rare endpoint official-kmspico[.]com at 16:53:47 (UTC).

Device Event Log showing SSL connections to the official-kmspico[.]com malvertising website.
Figure 2: Device Event Log showing SSL connections to the official-kmspico[.]com malvertising website.

One minute later, at 16:54:19 (UTC), the same device was seen connecting to two mega[.]co[.]nz subdomains and downloading around 13 MB of data from them. As mentioned previously, these connections likely represent the CryptBot payload and cracked software download.

Device Event Log showing SSL connections to mega[.]com endpoints following the connection to the malvertising site.
Figure 3: Device Event Log showing SSL connections to mega[.]com endpoints following the connection to the malvertising site.

At 16:56:01 (UTC), Darktrace detected the device making a first HTTP POST request to the 100% rare endpoint, avomyj24[.]top, which has been associated with CryptBot’s C2 infrastructure [22]. This initial HTTP POST connection likely represents the transfer of confidential data to the attacker’s infrastructure.

Device Event Log showing HTTP connections made by the infected device to the C2 domain. 
Figure 4: Device Event Log showing HTTP connections made by the infected device to the C2 domain. 

The full attack chain, from visiting the malvertising website to the malicious data egress, took less than three minutes to complete. In this circumstance, the machine-speed detection and response capabilities offered by Darktrace DETECT and RESPOND are paramount in order to stop CryptBot before it can successfully exfiltrates sensitive data. This is an incredibly quick infection timeline, with no lateral movement nor privilege escalation required to carry out the malware’s objective. 

Device Event Log showing the DETECT and RESPOND models breached during the attack. 
Figure 5: Device Event Log showing the DETECT and RESPOND models breached during the attack. 

Darktrace Cyber AI Analyst incidents were also generated as a result of this activity, displaying all relevant information in one panel for easy review by customer security teams.

Cyber AI Analyst event log showing the HTTP connections made by the breach device to the C2 endpoint.
Figure 6: Cyber AI Analyst event log showing the HTTP connections made by the breach device to the C2 endpoint.

Conclusion 

CryptBot info-stealer is fast, efficient, and apt at evading detection given its small size and swift process of data gathering and exfiltration via legitimate channels. Its constantly changing C2 infrastructure further makes it difficult for traditional security tools that really on rules and signatures or known indicators of compromise (IoCs) to detect these infections. 

In the face of such a threat, Darktrace’s anomaly-based detection allows it to recognize subtle deviations in a device’s pattern of behavior that may signal an evolving threat and instantly bring it to the attention of security teams. Darktrace DETECT is able to distinguish between benign activity and malicious behavior, even from newly monitored devices, while Darktrace RESPOND can move at machine-speed to prevent even the fastest moving threat actors from stealing confidential company data, as it demonstrated here by stopping CryptBot infections in as little as 2 seconds.

Credit to Alexandra Sentenac, Cyber Analyst, Roberto Romeu, Senior SOC Analyst

Darktrace Model Detections  

AI Analyst Coverage 

  • Possible HTTP Command and Control  

DETECT Model Breaches  

  • Device / Suspicious Domain 
  • Anomalous Connection / POST to PHP on New External Host 
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname 
  • Compromise / Multiple SSL to Rare DGA Domains

List of IOCs

Indicator Type Description
luaigz34[.]top Hostname CryptBot C2 endpoint
watibt04[.]top Hostname CryptBot C2 endpoint
avolsq14[.]top Hostname CryptBot C2 endpoint

MITRE ATT&CK Mapping

Category Technique Tactic
INITIAL ACCESS Drive-by Compromise - T1189 N/A
COMMAND AND CONTROL Web Protocols - T1071.001 N/A
COMMAND AND CONTROL Domain Generation Algorithm - T1568.002 N/A

References

[1] https://www.malwarebytes.com/blog/threats/info-stealers

[2] https://cybelangel.com/what-are-infostealers/

[3] https://ke-la.com/information-stealers-a-new-landscape/

[4] https://darktrace.com/blog/vidar-info-stealer-malware-distributed-via-malvertising-on-google

[5] https://darktrace.com/blog/a-surge-of-vidar-network-based-details-of-a-prolific-info-stealer 

[6] https://darktrace.com/blog/laplas-clipper-defending-against-crypto-currency-thieves-with-detect-respond

[7] https://darktrace.com/blog/amadey-info-stealer-exploiting-n-day-vulnerabilities 

[8] https://cybelangel.com/what-are-infostealers/

[9] https://webz.io/dwp/the-top-10-dark-web-marketplaces-in-2022/

[10] https://www.accenture.com/us-en/blogs/security/information-stealer-malware-on-dark-web

[11] https://www.bleepingcomputer.com/news/security/revamped-cryptbot-malware-spread-by-pirated-software-sites/

[12] https://blogs.blackberry.com/en/2022/03/threat-thursday-cryptbot-infostealer

[13] https://www.deepinstinct.com/blog/cryptbot-how-free-becomes-a-high-price-to-pay

[14] https://blog.google/technology/safety-security/continuing-our-work-to-hold-cybercriminal-ecosystems-accountable/

[15] https://asec.ahnlab.com/en/31802/

[16] https://darktrace.com/blog/the-last-of-its-kind-analysis-of-a-raccoon-stealer-v1-infection-part-1

[17] https://www.trendmicro.com/pt_br/research/21/c/websites-hosting-cracks-spread-malware-adware.html

[18] https://intel471.com/blog/privateloader-malware

[19] https://cyware.com/news/watch-out-pay-per-install-privateloader-malware-distribution-service-is-flourishing-888273be 

[20] https://regmedia.co.uk/2023/04/28/handout_google_cryptbot_complaint.pdf

[21] https://www.bankinfosecurity.com/google-wins-court-order-to-block-cryptbot-infrastructure-a-21905

[22] https://github.com/stamparm/maltrail/blob/master/trails/static/malware/cryptbot.txt

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
Alexandra Sentenac
Cyber Analyst

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June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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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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