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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
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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

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September 9, 2025

The benefits of bringing together network and email security

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In many organizations, network and email security operate in isolation. Each solution is tasked with defending its respective environment, even though both are facing the same advanced, multi-domain threats.  

This siloed approach overlooks a critical reality: email remains the most common vector for initiating cyber-attacks, while the network is the primary stage on which those attacks progress. Without direct integration between these two domains, organizations risk leaving blind spots that adversaries can exploit.  

A modern security strategy needs to unify email and network defenses, not just in name, but in how they share intelligence, conduct investigations, and coordinate response actions. Let’s take a look at how this joined-up approach delivers measurable technical, operational, and commercial benefits.

Technical advantages

Pre-alert intelligence: Gathering data before the threat strikes

Most security tools start working when something goes wrong – an unusual login, a flagged attachment, a confirmed compromise. But by then, attackers may already be a step ahead.

By unifying network and email security under a single AI platform (like the Darktrace Active AI Security Platform), you can analyze patterns across both environments in real time, even when there are no alerts. This ongoing monitoring builds a behavioral understanding of every user, device, and domain in your ecosystem.

That means when an email arrives from a suspicious domain, the system already knows whether that domain has appeared on your network before – and whether its behavior has been unusual. Likewise, when new network activity involves a domain first spotted in an email, it’s instantly placed in the right context.

This intelligence isn’t built on signatures or after-the-fact compromise indicators – it’s built on live behavioral baselines, giving your defenses the ability to flag threats before damage is done.

Alert-related intelligence: Connecting the dots in real time

Once an alert does fire, speed and context matter. The Darktrace Cyber AI Analyst can automatically investigate across both environments, piecing together network and email evidence into a single, cohesive incident.

Instead of leaving analysts to sift through fragmented logs, the AI links events like a phishing email to suspicious lateral movement on the recipient’s device, keeping the full attack chain intact. Investigations that might take hours – or even days – can be completed in minutes, with far fewer false positives to wade through.

This is more than a time-saver. It ensures defenders maintain visibility after the first sign of compromise, following the attacker as they pivot into network infrastructure, cloud services, or other targets. That cross-environment continuity is impossible to achieve with disconnected point solutions or siloed workflows.

Operational advantages

Streamlining SecOps across teams

In many organizations, email security is managed by IT, while network defense belongs to the SOC. The result? Critical information is scattered between tools and teams, creating blind spots just when you need clarity.

When email and network data flow into a single platform, everyone is working from the same source of truth. SOC analysts gain immediate visibility into email threats without opening another console or sending a request to another department. The IT team benefits from the SOC’s deeper investigative context.

The outcome is more than convenience: it’s faster, more informed decision-making across the board.

Reducing time-to-meaning and enabling faster response

A unified platform removes the need to manually correlate alerts between tools, reducing time-to-meaning for every incident. Built-in AI correlation instantly ties together related events, guiding analysts toward coordinated responses with higher confidence.

Instead of relying on manual SIEM rules or pre-built SOAR playbooks, the platform connects the dots in real time, and can even trigger autonomous response actions across both environments simultaneously. This ensures attacks are stopped before they can escalate, regardless of where they begin.

Commercial advantages

While purchasing “best-of-breed" for all your different tools might sound appealing, it often leads to a patchwork of solutions with overlapping costs and gaps in coverage. However good a “best-in-breed" email security solution might be in the email realm, it won't be truly effective without visibility across domains and an AI analyst piecing intelligence together. That’s why we think “best-in-suite" is the only “best-in-breed" approach that works – choosing a high-quality platform ensures that every new capability strengthens the whole system.  

On top of that, security budgets are under constant pressure. Managing separate vendors for email and network defense means juggling multiple contracts, negotiating different SLAs, and stitching together different support models.

With a single provider for both, procurement and vendor management become far simpler. You deal with one account team, one support channel, and one unified strategy for both environments. If you choose to layer on managed services, you get consistent expertise across your whole security footprint.

Even more importantly, an integrated AI platform sets the stage for growth. Once email and network are under the same roof, adding coverage for other attack surfaces – like cloud or identity – is straightforward. You’re building on the same architecture, not bolting on new point solutions that create more complexity.

Check out the white paper, The Modern Security Stack: Why Your NDR and Email Security Solutions Need to Work Together, to explore these benefits in more depth, with real-world examples and practical steps for unifying your defenses.

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Mikey Anderson
Product Marketing Manager, Network Detection & Response

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September 9, 2025

Unpacking the Salesloft Incident: Insights from Darktrace Observations

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Introduction

On August 26, 2025, Google Threat intelligence Group released a report detailing a widespread data theft campaign targeting the sales automation platform Salesloft, via compromised OAuth tokens used by the third-party Drift AI chat agent [1][2].  The attack has been attributed to the threat actor UNC6395 by Google Threat Intelligence and Mandiant [1].

The attack is believed to have begun in early August 2025 and continued through until mid-August 2025 [1], with the threat actor exporting significant volumes of data from multiple Salesforce instances [1]. Then sifting through this data for anything that could be used to compromise the victim’s environments such as access keys, tokens or passwords. This had led to Google Threat Intelligence Group assessing that the primary intent of the threat actor is credential harvesting, and later reporting that it was aware of in excess of 700 potentially impacted organizations [3].

Salesloft previously stated that, based on currently available data, customers that do not integrate with Salesforce are unaffected by this campaign [2]. However, on August 28, Google Threat Intelligence Group announced that “Based on new information identified by GTIG, the scope of this compromise is not exclusive to the Salesforce integration with Salesloft Drift and impacts other integrations” [2]. Google Threat Intelligence has since advised that any and all authentication tokens stored in or connected to the Drift platform be treated as potentially compromised [1].

This campaign demonstrates how attackers are increasingly exploiting trusted Software-as-a-Service (SaaS) integrations as a pathway into enterprise environment.

By abusing these integrations, threat actors were able to exfiltrate sensitive business data at scale, bypassing traditional security controls. Rather than relying on malware or obvious intrusion techniques, the adversaries leveraged legitimate credentials and API traffic that resembled legitimate Salesforce activity to achieve their goals. This type of activity is far harder to detect with conventional security tools, since it blends in with the daily noise of business operations.

The incident underscores the escalating significance of autonomous coverage within SaaS and third-party ecosystems. As businesses increasingly depend on interconnected platforms, visibility gaps become evident that cannot be managed by conventional perimeter and endpoint defenses.

By developing a behavioral comprehension of each organization's distinct use of cloud services, anomalies can be detected, such as logins from unexpected locations, unusually high volumes of API requests, or unusual document activity. These indications serve as an early alert system, even when intruders use legitimate tokens or accounts, enabling security teams to step in before extensive data exfiltration takes place

What happened?

The campaign is believed to have started on August 8, 2025, with malicious activity continuing until at least August 18. The threat actor, tracked as UNC6395, gained access via compromised OAuth tokens associated with Salesloft Drift integrations into Salesforce [1]. Once tokens were obtained, the attackers were able to issue large volumes of Salesforce API requests, exfiltrating sensitive customer and business data.

Initial Intrusion

The attackers first established access by abusing OAuth and refresh tokens from the Drift integration. These tokens gave them persistent access into Salesforce environments without requiring further authentication [1]. To expand their foothold, the threat actor also made use of TruffleHog [4], an open-source secrets scanner, to hunt for additional exposed credentials. Logs later revealed anomalous IAM updates, including unusual UpdateAccessKey activity, which suggested attempts to ensure long-term persistence and control within compromised accounts.

Internal Reconnaissance & Data Exfiltration

Once inside, the adversaries began exploring the Salesforce environments. They ran queries designed to pull sensitive data fields, focusing on objects such as Cases, Accounts, Users, and Opportunities [1]. At the same time, the attackers sifted through this information to identify secrets that could enable access to other systems, including AWS keys and Snowflake credentials [4]. This phase demonstrated the opportunistic nature of the campaign, with the actors looking for any data that could be repurposed for further compromise.

Lateral Movement

Salesloft and Mandiant investigations revealed that the threat actor also created at least one new user account in early September. Although follow-up activity linked to this account was limited, the creation itself suggested a persistence mechanism designed to survive remediation efforts. By maintaining a separate identity, the attackers ensured they could regain access even if their stolen OAuth tokens were revoked.

Accomplishing the mission

The data taken from Salesforce environments included valuable business records, which attackers used to harvest credentials and identify high-value targets. According to Mandiant, once the data was exfiltrated, the actors actively sifted through it to locate sensitive information that could be leveraged in future intrusions [1]. In response, Salesforce and Salesloft revoked OAuth tokens associated with Drift integrations on August 20 [1], a containment measure aimed at cutting off the attackers’ primary access channel and preventing further abuse.

How did the attack bypass the rest of the security stack?

The campaign effectively bypassed security measures by using legitimate credentials and OAuth tokens through the Salesloft Drift integration. This rendered traditional security defenses like endpoint protection and firewalls ineffective, as the activity appeared non-malicious [1]. The attackers blended into normal operations by using common user agents and making queries through the Salesforce API, which made their activity resemble legitimate integrations and scripts. This allowed them to operate undetected in the SaaS environment, exploiting the trust in third-party connections and highlighting the limitations of traditional detection controls.

Darktrace Coverage

Anomalous activities have been identified across multiple Darktrace deployments that appear associated with this campaign. This included two cases on customers based within the United States who had a Salesforce integration, where the pattern of activities was notably similar.

On August 17, Darktrace observed an account belonging to one of these customers logging in from the rare endpoint 208.68.36[.]90, while the user was seen active from another location. This IP is a known indicator of compromise (IoC) reported by open-source intelligence (OSINT) for the campaign [2].

Cyber AI Analyst Incident summarizing the suspicious login seen for the account.
Figure 1: Cyber AI Analyst Incident summarizing the suspicious login seen for the account.

The login event was associated with the application Drift, further connecting the events to this campaign.

Advanced Search logs showing the Application used to login.
Figure 2: Advanced Search logs showing the Application used to login.

Following the login, the actor initiated a high volume of Salesforce API requests using methods such as GET, POST, and DELETE. The GET requests targeted endpoints like /services/data/v57.0/query and /services/data/v57.0/sobjects/Case/describe, where the former is used to retrieve records based on a specific criterion, while the latter provides metadata for the Case object, including field names and data types [5,6].

Subsequently, a POST request to /services/data/v57.0/jobs/query was observed, likely to initiate a Bulk API query job for extracting large volumes of data from the Ingest Job endpoint [7,8].

Finally, a DELETE request to remove an ingestion job batch, possibly an attempt to obscure traces of prior data access or manipulation.

A case on another US-based customer took place a day later, on August 18. This again began with an account logging in from the rare IP 208.68.36[.]90 involving the application Drift. This was followed by Salesforce GET requests targeting the same endpoints as seen in the previous case, and then a POST to the Ingest Job endpoint and finally a DELETE request, all occurring within one minute of the initial suspicious login.

The chain of anomalous behaviors, including a suspicious login and delete request, resulted in Darktrace’s Autonomous Response capability suggesting a ‘Disable user’ action. However, the customer’s deployment configuration required manual confirmation for the action to take effect.

An example model alert for the user, triggered due to an anomalous API DELETE request.
Figure 3: An example model alert for the user, triggered due to an anomalous API DELETE request.
Figure 4: Model Alert Event Log showing various model alerts for the account that ultimately led to an Autonomous Response model being triggered.

Conclusion

In conclusion, this incident underscores the escalating risks of SaaS supply chain attacks, where third-party integrations can become avenues for attacks. It demonstrates how adversaries can exploit legitimate OAuth tokens and API traffic to circumvent traditional defenses. This emphasizes the necessity for constant monitoring of SaaS and cloud activity, beyond just endpoints and networks, while also reinforcing the significance of applying least privilege access and routinely reviewing OAuth permissions in cloud environments. Furthermore, it provides a wider perspective into the evolution of the threat landscape, shifting towards credential and token abuse as opposed to malware-driven compromise.

Credit to Emma Foulger (Global Threat Research Operations Lead), Calum Hall (Technical Content Researcher), Signe Zaharka (Principal Cyber Analyst), Min Kim (Senior Cyber Analyst), Nahisha Nobregas (Senior Cyber Analyst), Priya Thapa (Cyber Analyst)

Appendices

Darktrace Model Detections

·      SaaS / Access / Unusual External Source for SaaS Credential Use

·      SaaS / Compromise / Login From Rare Endpoint While User Is Active

·      SaaS / Compliance / Anomalous Salesforce API Event

·      SaaS / Unusual Activity / Multiple Unusual SaaS Activities

·      Antigena / SaaS / Antigena Unusual Activity Block

·      Antigena / SaaS / Antigena Suspicious Source Activity Block

Customers should consider integrating Salesforce with Darktrace where possible. These integrations allow better visibility and correlation to spot unusual behavior and possible threats.

IoC List

(IoC – Type)

·      208.68.36[.]90 – IP Address

References

1.     https://cloud.google.com/blog/topics/threat-intelligence/data-theft-salesforce-instances-via-salesloft-drift

2.     https://trust.salesloft.com/?uid=Drift+Security+Update%3ASalesforce+Integrations+%283%3A30PM+ET%29

3.     https://thehackernews.com/2025/08/salesloft-oauth-breach-via-drift-ai.html

4.     https://unit42.paloaltonetworks.com/threat-brief-compromised-salesforce-instances/

5.     https://developer.salesforce.com/docs/atlas.en-us.api_rest.meta/api_rest/resources_query.htm

6.     https://developer.salesforce.com/docs/atlas.en-us.api_rest.meta/api_rest/resources_sobject_describe.htm

7.     https://developer.salesforce.com/docs/atlas.en-us.api_asynch.meta/api_asynch/get_job_info.htm

8.     https://developer.salesforce.com/docs/atlas.en-us.api_asynch.meta/api_asynch/query_create_job.htm

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About the author
Emma Foulger
Global Threat Research Operations Lead
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