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March 14, 2023

Defending Against Crypto Thieves with DETECT + RESPOND

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14
Mar 2023
Cyber criminals steal from crypto-currency platforms. Learn how Darktrace uncovered Lapalas Clipper activity & defended against cryptocurrency thieves.

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.
Author
Anna Gilbertson
Cyber Security Analyst
Hanah Darley
Director of Threat Research
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February 19, 2025

Darktrace Releases Annual 2024 Threat Insights

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Introduction: Darktrace’s threat research

Defenders must understand the threat landscape in order to protect against it. They can do that with threat intelligence.

Darktrace approaches threat intelligence with a unique perspective. Unlike traditional security vendors that rely on established patterns from past incidents, it uses a strategy that is rooted in the belief that identifying behavioral anomalies is crucial for identifying both known and novel threats.

For Darktrace analysts and researchers, the incidents detected by the AI solution mark the beginning of a deeper investigation, aiming to connect mitigated threats to wider trends from across the threat landscape. Through hindsight analysis, the Darktrace Threat Research team has highlighted numerous threats, including zero-day, n-day, and other novel attacks, showcasing their evolving nature and Darktrace’s ability to identify them.

In 2024, the Threat Research team observed major trends around vulnerabilities in internet-facing systems, new and re-emerging ransomware strains, and sophisticated email attacks. Read on to discover some of our key insights into the current cybersecurity threat landscape.

Multiple campaigns target vulnerabilities in internet-facing systems

It is increasingly common for threat actors to identify and exploit newly discovered vulnerabilities in widely used services and applications, and in some cases, these vulnerability exploitations occur within hours of disclosure.

In 2024, the most significant campaigns observed involved the ongoing exploitation of zero-day and n-day vulnerabilities in edge and perimeter network technologies. In fact, in the first half of the year, 40% of all identified campaign activity came from the exploitation of internet-facing devices. Some of the most common exploitations involved Ivanti Connect Secure (CS) and Ivanti Policy Secure (PS) appliances, Palo Alto Network (PAN-OS) firewall devices, and Fortinet appliances.

Darktrace helps security teams identify suspicious behavior quickly, as demonstrated with the critical vulnerability in PAN-OS firewall devices. The vulnerability was publicly disclosed on April 11, 2024, yet with anomaly-based detection, Darktrace’s Threat Research team was able to identify a range of suspicious behavior related to exploitation of this vulnerability, including command-and-control (C2) connectivity, data exfiltration, and brute-forcing activity, as early as March 26.

That means that Darktrace and our Threat Research team detected this Common Vulnerabilities and Exposure (CVE) exploitation 16 days before the vulnerability was disclosed. Addressing critical vulnerabilities quickly massively benefits security, as teams can reduce their effectiveness by slowing malicious operations and forcing attackers to pursue more costly and time-consuming methods.

Persistent ransomware threats continue to evolve

The continued adoption of the Ransomware-as-a-Service (RaaS) model provides even less experienced threat actors with the tools needed to carry out disruptive attacks, significantly lowering the barrier to entry.

The Threat Research team tracked both novel and re-emerging strains of ransomware across the customer fleet, including Akira, LockBit, and Lynx. Within these ransomware attempts and incidents, there were notable trends in attackers’ techniques: using phishing emails as an attack vector, exploiting legitimate tools to mask C2 communication, and exfiltrating data to cloud storage services.

Read the Annual 2024 Threat Report for the complete list of prominent ransomware actors and their commonly used techniques.

Onslaught of email threats continues

With a majority of attacks originating from email, it is crucial that organizations secure the inboxes and beyond.

Between December 21, 2023, and December 18, 2024, Darktrace / EMAIL detected over 30.4 million phishing emails across the fleet. Of these, 70% successfully bypassed Domain-based Message Authentication, Reporting, and Conformance (DMARC) verification checks and 55% passed through all other existing layers of customer email security.

The abuse of legitimate services and senders continued to be a significant method for threat actors throughout 2024. By leveraging trusted platforms and domains, malicious actors can bypass traditional security measures and increase the likelihood of their phishing attempts being successful.

This past year, there was a substantial use of legitimately authenticated senders and previously established domains, with 96% of phishing emails detected by Darktrace / EMAIL utilizing existing domains rather than registering new ones.

These are not the only types of email attacks we observed. Darktrace detected over 2.7 million emails with multistage payloads.

While most traditional cybersecurity solutions struggle to cover multiple vectors and recognize each stage of complex attacks as part of wider malicious activity, Darktrace can detect and respond across email, identities, network, and cloud.

Conclusion

The Darktrace Threat Research team continues to monitor the ever-evolving threat landscape. Major patterns over the last year have revealed the importance of fast-acting, anomaly-based detection like Darktrace provides.

For example, response speed is essential when campaigns target vulnerabilities in internet-facing systems, and these vulnerabilities can be exploited by attackers within hours of their disclosure if not even before that.

Similarly, anomaly-based detection can identify hard to find threats like ransomware attacks that increasingly use living-off-the-land techniques and legitimate tools to hide malicious activity. A similar pattern can be found in the realm of email security, where attacks are also getting harder to spot, especially as they frequently exploit trusted senders, use redirects via legitimate services, and craft attacks that bypass DMARC and other layers of email security.

As attacks appear with greater complexity, speed, and camouflage, defenders must have timely detection and containment capabilities to handle all emerging threats. These hard-to-spot attacks can be identified and stopped by Darktrace.

Download the full report

Discover the latest threat landscape trends and recommendations from the Darktrace Threat Research team.

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February 18, 2025

Unifying IT & OT With AI-Led Investigations for Industrial Security

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As industrial environments modernize, IT and OT networks are converging to improve efficiency, but this connectivity also creates new attack paths. Previously isolated OT systems are now linked to IT and cloud assets, making them more accessible to attackers.

While organizations have traditionally relied on air gaps, firewalls, data diodes, and access controls to separate IT and OT, these measures alone aren’t enough. Threat actors often infiltrate IT/Enterprise networks first then exploit segmentation, compromising credentials, or shared IT/OT systems to move laterally, escalate privileges, and ultimately enter the OT network.

To defend against these threats, organizations must first ensure they have complete visibility across IT and OT environments.

Visibility: The first piece of the puzzle

Visibility is the foundation of effective industrial cybersecurity, but it’s only the first step. Without visibility across both IT and OT, security teams risk missing key alerts that indicate a threat targeting OT at their earliest stages.

For Attacks targeting OT, early stage exploits often originate in IT environments, adversaries perform internal reconnaissance among other tactics and procedures but then laterally move into OT first affecting IT devices, servers and workstations within the OT network. If visibility is limited, these threats go undetected. To stay ahead of attackers, organizations need full-spectrum visibility that connects IT and OT security, ensuring no early warning signs are missed.

However, visibility alone isn’t enough. More visibility also means more alerts, this doesn’t just make it harder to separate real threats from routine activity, but bogs down analysts who have to investigate all these alerts to determine their criticality.

Investigations: The real bottleneck

While visibility is essential, it also introduces a new challenge: Alert fatigue. Without the right tools, analysts are often occupied investigating alerts with little to no context, forcing them to manually piece together information and determine if an attack is unfolding. This slows response times and increases the risk of missing critical threats.

Figure 1: Example ICS attack scenario

With siloed visibility across IT and OT each of these events shown above would be individually alerted by a detection engine with little to no context nor correlation. Thus, an analyst would have to try to piece together these events manually. Traditional security tools struggle to keep pace with the sophistication of these threats, resulting in an alarming statistic: less than 10% of alerts are thoroughly vetted, leaving organizations vulnerable to undetected breaches. As a result, incidents inevitably follow.

Darktrace’s Cyber AI Analyst uses AI-led investigations to improve workflows for analysts by automatically correlating alerts wherever they occur across both IT and OT. The multi-layered AI engine identifies high-priority incidents, and provides analysts with clear, actionable insights, reducing noise and highlighting meaningful threats. The AI significantly alleviates workloads, enabling teams to respond faster and more effectively before an attack escalates.

Overcoming organizational challenges across IT and OT

Beyond technical challenges like visibility and alert management, organizational dynamics further complicate IT-OT security efforts. Fundamental differences in priorities, workflows, and risk perspectives create challenges that can lead to misalignment between teams:

Non-transferable practices: IT professionals might assume that cybersecurity practices from IT environments can be directly applied to OT environments. This can lead to issues, as OT systems and workflows may not handle IT security processes as expected. It's crucial to recognize and respect the unique requirements and constraints of OT environments.

Segmented responsibilities: IT and OT teams often operate under separate organizational structures, each with distinct priorities, goals, and workflows. While IT focuses on data security, network integrity, and enterprise applications, OT prioritizes uptime, reliability, and physical processes.

Different risk perspectives: While IT teams focus on preventing cyber threats and regulatory violations, OT teams prioritize uptime and operational reliability making them drawn towards asset inventory tools that provide no threat detection capability.

Result: A combination of disparate and ineffective tools and misaligned teams can make any progress toward risk reduction at an organization seem impossible. The right tools should be able to both free up time for collaboration and prompt better communication between IT and OT teams where it is needed. However, different size operations structure their IT and OT teams differently which impacts the priorities for each team.

In real-world scenarios, small IT teams struggle to manage security across both IT and OT, while larger organizations with OT security teams face alert fatigue and numerous false positives slowing down investigations and hindering effective communication with the IT security teams.

By unifying visibility and investigations, Darktrace / OT helps organizations of all sizes detect threats earlier, streamline workflows, and enhance security across both IT and OT environments. The following examples illustrate how AI-driven investigations can transform security operations, improving detection, investigation, and response.

Before and after AI-led investigation

Before: Small manufacturing company

At a small manufacturing company, a 1-3 person IT team juggles everything from email security to network troubleshooting. An analyst might see unusual traffic through the firewall:

  • Unusual repeated outbound traffic from an IP within their OT network destined to an unidentifiable external IP.

With no dedicated OT security tools and limited visibility into the industrial network, they don’t know what the internal device in question is, if it is beaconing to a malicious external IP, and what it may be doing to other devices within the OT network. Without a centralized dashboard, they must manually check logs, ask operators about changes, and hunt for anomalies across different systems.

After a day of investigation, they concluded the traffic was not to be expected activity. They stop production within their smaller OT network, update their firewall rules and factory reset all OT devices and systems within the blast radius of the IP device in question.

After: Faster, automated response with Cyber AI Analyst

With Darktrace / OT and Cyber AI Analyst, the IT team moves from reactive, manual investigations to proactive, automated threat detection:

  • Cyber AI Analyst connects alerts across their IT and OT infrastructure temporally mapping them to attack frameworks and provides contextual analysis of how alerts are linked, revealing in real time attackers attempting lateral movement from IT to OT.
  • A human-readable incident report explains the full scope of the incident, eliminating hours of manual investigation.
  • The team is faster to triage as they are led directly to prioritized high criticality alerts, now capable of responding immediately instead of wasting valuable time hunting for answers.

By reducing noise, providing context, and automating investigations, Cyber AI Analyst transforms OT security, enabling small IT teams to detect, understand, and respond to threats—without deep OT cybersecurity expertise.

Before: Large critical infrastructure organization

In large critical infrastructure operations, OT and IT teams work in separate silos. The OT security team needs to quickly assess and prioritize alerts, but their system floods them with notifications:

  • Multiple new device connected to the ICS network alerts
  • Multiple failed logins to HMI detected
  • Multiple Unusual Modbus/TCP commands detected
  • Repeated outbound OT traffic to IT destinations

At first glance, these alerts seem important, but without context, it’s unclear whether they indicate a routine error, a misconfiguration, or an active cyber-attack. They might ask:

  • Are the failed logins just a mistake, or a brute-force attempt?
  • Is the outbound traffic part of a scheduled update, or data exfiltration?

Without correlation across events, the engineer must manually investigate each one—checking logs, cross-referencing network activity, and contacting operators—wasting valuable time. Meanwhile, if it’s a coordinated attack, the adversary may already be disrupting operations.

After: A new workflow with Cyber AI Analyst

With Cyber AI Analyst, the OT security team gets clear, automated correlation of security events, making investigations faster and more efficient:

  • Automated correlation of OT threats: Instead of isolated alerts, Cyber AI Analyst stitches together related events, providing a single, high-confidence incident report that highlights key details.
  • Faster time to meaning: The system connects anomalous behaviors (e.g., failed logins, unusual traffic from an HMI, and unauthorized PLC modifications) into a cohesive narrative, eliminating hours of manual log analysis.
  • Prioritized and actionable alerts: OT security receives clear, ranked incidents, immediately highlighting what matters most.
  • Rapid threat understanding: Security teams know within minutes whether an event is a misconfiguration or a cyber-attack, allowing for faster containment.

With Cyber AI Analyst, large organizations cut through alert noise, accelerate investigations, and detect threats faster—without disrupting OT operations.

An AI-led approach to industrial cybersecurity

Security vendors with a primary focus on IT may lack insight into OT threats. Even OT-focused vendors have limited visibility into IT device exploitation within OT networks, leading to failed ability to detect early indicators of compromise. A comprehensive solution must account for the unique characteristics of various OT environments.

In a world where industrial security is no longer just about protecting OT but securing the entire digital-physical ecosystem as it interacts with the OT network, Darktrace / OT is an AI-driven solution that unifies visibility across IT, IoT and OT, Cloud into one cohesive defense strategy.

Whether an attack originates from an external breach, an insider threat, a supply chain compromise, in the Cloud, OT, or IT domains Cyber AI Analyst ensures that security teams see the full picture - before disruption occurs.

Learn more about Darktrace / OT 

  • Unify IT and OT security under a single platform, ensuring seamless communication and protection for all interconnected devices.
  • Maintain uptime with AI-driven threat containment, stopping attacks without disrupting production.
  • Mitigate risks with or without patches, leveraging MITRE mitigations to reduce attack opportunities.

Download the solution brief to see how Darktrace secures critical infrastructure.

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Daniel Simonds
Director of Operational Technology
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