Blog
/
Network
/
March 14, 2023

Protecting Yourself from Laplas Clipper Crypto Theives

Explore strategies to combat Laplas Clipper attacks and enhance your defenses against cryptocurrency theft in the digital landscape.
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
Anna Gilbertson
Cyber Security Analyst
Written by
Hanah Darley
Director of Threat Research
Default blog image
14
Mar 2023

Between June 2021 and June 2022, crypto-currency platforms around the world lost an estimated 44 billion USD to cyber criminals, whose modus operandi range from stealing passwords and account recovery phrases, to cryptojacking and directly targeting crypto-currency transactions. 

There has been a recent rise in cases of cyber criminals’ using information stealer malware to gather and exfiltrate sensitive crypto-currency wallet details, ultimately leading to the theft of significant sums of digital currency. Having an autonomous decision maker able to detect and respond to potential compromises is crucial to safeguard crypto wallets and transactions against would-be attackers.

In late 2022, Darktrace observed several threat actors employing a novel attack method to target crypto-currency users across its customer base, specifically the latest version of the Laplas Clipper malware. Using Self-Learning AI, Darktrace DETECT/Network™ and Darktrace RESPOND/Network™ were able to uncover and mitigate Laplas Clipper activity and intervene to prevent the theft of large sums of digital currency.

Laplas Clipper Background

Laplas Clipper is a variant of information stealing malware which operates by diverting crypto-currency transactions from victims’ crypto wallets into the wallets of threat actors [1]. Laplas Clipper is a Malware-as-a-Service (MaaS) offering available for purchase and use by a variety of threat actors. It has been observed in the wild since October 2022, when 180 samples were identified and linked with another malware strain, namely SmokeLoader [2]. This loader has itself been observed since at least 2011 and acts as a delivery mechanism for popular malware strains [3]. 

SmokeLoader is typically distributed via malicious attachments sent in spam emails or targeted phishing campaigns but can also be downloaded directly by users from file hosting pages or spoofed websites. SmokeLoader is known to specifically deliver Laplas Clipper onto compromised devices via a BatLoader script downloaded as a Microsoft Word document or a PDF file attached to a phishing email. These examples of social engineering are relatively low effort methods intended to convince users to download the malware, which subsequently injects malicious code into the explorer.exe process and downloads Laplas Clipper.

Laplas Clipper activity observed across Darktrace’s customer base generally began with SmokeLoader making HTTP GET requests to Laplas Clipper command and control (C2) infrastructure. Once downloaded, the clipper loads a ‘build[.]exe’ module and begins monitoring the victim’s clipboard for crypto-currency wallet addresses. If a wallet address is identified, the infected device connects to a server associated with Laplas Clipper and downloads wallet addresses belonging to the threat actor. The actor’s addresses are typically spoofed to appear similar to those they replace in order to evade detection. The malware continues to update clipboard activity and replaces the user’s wallet addresses with a spoofed address each time one is copied for a for crypto-currency transactions.

Darktrace Coverage of Laplas Clipper and its Delivery Methods 

In October and November 2022, Darktrace observed a significant increase in suspicious activity associated with Laplas Clipper across several customer networks. The activity consisted largely of:  

  1. User devices connecting to a suspicious endpoint.  
  2. User devices making HTTP GET requests to an endpoint associated with the SmokeLoader loader malware, which was installed on the user’s device.
  3. User devices making HTTP connections to the Laplas Clipper download server “clipper[.]guru”, from which it downloads spoofed wallet addresses to divert crypto-currency payments. 

In one particular instance, a compromised device was observed connecting to endpoints associated with SmokeLoader shortly before connecting to a Laplas Clipper download server. In other instances, devices were detected connecting to other anomalous endpoints including the domains shonalanital[.]com, transfer[.]sh, and pc-world[.]uk, which appears to be mimicking the legitimate endpoint thepcworld[.]com. 

Additionally, some compromised devices were observed attempting to connect malicious IP addresses including 193.169.255[.]78 and 185.215.113[.]23, which are associated with the RedLine stealer malware. Additionally, Darktrace observed connections to the IP addresses 195.178.120[.]154 and 195.178.120[.]154, which are associated with SmokeLoader, and 5.61.62[.]241, which open-source intelligence has associated with Cobalt Strike. 

Figure 1: Beacon to Young Endpoint model breach demonstrating Darktrace’s ability to detect external connections that are considered extremely rare for the network.
Figure 2: The event log of an infected device attempting to connect to IP addresses associated with the RedLine stealer malware, and the actions RESPOND took to block these attempts.

The following DETECT/Network models breached in response to these connections:

  • Compromise / Beacon to Young Endpoint 
  • Compromise / Slow Beaconing Activity to External Rare 
  • Compromise / Beacon for 4 Days
  • Compromise / Beaconing Activity to External Rare
  • Compromise / Sustained TCP Beaconing Activity to Rare Endpoint 
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoints 
  • Compromise / Large Number of Suspicious Failed Connections 
  • Compromise / HTTP Beaconing to Rare Destination 
  • Compromise / Post and Beacon to Rare External 
  • Anomalous Connection / Callback on Web Facing Device 

DETECT/Network is able to identify such activity as its models operate based on a device’s usual pattern of behavior, rather than a static list of indicators of compromise (IOCs). As such, Darktrace can quickly identify compromised devices that deviate for their expected pattern of behavior by connecting to newly created malicious endpoints or C2 infrastructure, thereby triggering an alert.

In one example, RESPOND/Network autonomously intercepted a compromised device attempting to connect to the Laplas Clipper C2 server, preventing it from downloading SmokeLoader and subsequently, Laplas Clipper itself.

Figure 3: The event log of an infected device attempting to connect to the Laplas Clipper download server, and the actions RESPOND/Network took to block these attempts.

In another example, DETECT/Network observed an infected device attempting to perform numerous DNS Requests to a crypto-currency mining pool associated with the Monero digital currency.  

This activity caused the following DETECT/Network models to breach:

  • Compromise / Monero Mining
  • Compromise / High Priority Crypto Currency Mining 

RESPOND/Network quickly intervened, enforcing a previously established pattern of life on the device, ensuring it could not perform any unexpected activity, and blocking the connections to the endpoint in question for an hour. These actions carried out by Darktrace’s autonomous response technology prevented the infected device from carrying out crypto-mining activity, and ensured the threat actor could not perform any additional malicious activity.

Figure 4. The event log of an infected devices showing DNS requests to the Monero crypto-mining pool, and the actions taken to block them by RESPOND/Network.

Finally, in instances when RESPOND/Network was not activated, external connections to the Laplas Clipper C2 server were nevertheless monitored by DETECT/Network, and the customer’s security team were notified of the incident.

Conclusion 

The rise of information stealing malware variants such as Laplas Clipper highlights the importance of crypto-currency and crypto-mining in the malware ecosystem and more broadly as a significant cyber security concern. Crypto-mining is often discounted as background noise for security teams or compliance issues that can be left untriaged; however, malware strains like Laplas Clipper demonstrate the real security risks posed to digital estates from threat actors focused on crypto-currency. 

Leveraging its Self-Learning AI, DETECT/Network and RESPOND/Network are able to work in tandem to quickly identify connections to suspicious endpoints and block them before any malicious software can be downloaded, safeguarding customers.

Appendices

List of IOCs 

a720efe2b3ef7735efd77de698a5576b36068d07 - SHA1 Filehash - Laplas Malware Download

conhost.exe - URI - Laplas Malware Download

185.223.93.133 - IP Address - Laplas C2 Endpoint

185.223.93.251 - IP Address - Laplas C2 Endpoint

45.159.189.115 - IP Address - Laplas C2 Endpoint

79.137.204.208 - IP Address - Laplas C2 Endpoint

5.61.62.241 - IP Address - Laplas C2 Endpoint

clipper.guru - URI - Laplas C2 URI

/bot/online?guid= - URI - Laplas C2 URI

/bot/regex?key= - URI - Laplas C2 URI

/bot/get?address - URI - Laplas C2 URI

Mitre Attack and Mapping 

Initial Access:

T1189 – Drive By Compromise 

T1566/002 - Spearphishing

Resource Development:

T1588 / 001 - Malware

Ingress Tool Transfer:

T1105 – Ingress Tool Transfer

Command and Control:

T1071/001 – Web Protocols 

T1071 – Application Layer Protocol

T1008 – Fallback Channels

T1104 – Multi-Stage Channels

T1571 – Non-Standard Port

T1102/003 – One-Way Communication

T1573 – Encrypted Channel

Persistence:

T1176 – Browser Extensions

Collection:

T1185 – Man in the Browser

Exfiltration:

T1041 – Exfiltration over C2 Channel

References

[1] https://blog.cyble.com/2022/11/02/new-laplas-clipper-distributed-by-smokeloader/ 

[2] https://thehackernews.com/2022/11/new-laplas-clipper-malware-targeting.html

[3] https://attack.mitre.org/software/S0226/

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
Anna Gilbertson
Cyber Security Analyst
Written by
Hanah Darley
Director of Threat Research

More in this series

No items found.

Blog

/

Proactive Security

/

June 2, 2026

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

Default blog imageDefault blog image

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.”

Continue reading
About the author

Blog

/

Proactive Security

/

June 1, 2026

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

Default blog imageDefault blog image

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.

Continue reading
About the author
Your data. Our AI.
Elevate your network security with Darktrace AI