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February 8, 2024

How CoinLoader Hijacks Networks

Discover how Darktrace decrypted the CoinLoader malware hijacking networks for cryptomining. Learn about the tactics and protection 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
Signe Zaharka
Principal Cyber Analyst
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08
Feb 2024

About Loader Malware

Loader malware was a frequent topic of conversation and investigation within the Darktrace Threat Research team throughout 2023, with a wide range of existing and novel variants affecting a significant number of Darktrace customers, as detailed in Darktrace’s inaugural End of Year Threat Report. The multi-phase nature of such compromises poses a significant threat to organizations due to the need to defend against multiple threats at the same time.

CoinLoader, a variant of loader malware first observed in the wild in 2018 [1], is an example of one of the more prominent variant of loaders observed by Darktrace in 2023, with over 65 customers affected by the malware. Darktrace’s Threat Research team conducted a deep dive investigation into the patterns of behavior exhibited by devices infected with CoinLoader in the latter part of 2023, with compromises observed in Europe, the Middle East and Africa (EMEA), Asia-Pacific (APAC) and the Americas.

The autonomous threat detection capabilities of Darktrace DETECT™ allowed for the effective identification of these CoinLoader infections whilst Darktrace RESPOND™, if active, was able to quickly curtail attacker’s efforts and prevent more disruptive, and potentially costly, secondary compromises from occurring.

What is CoinLoader?

Much like other strains of loader, CoinLoader typically serves as a first stage malware that allows threat actors to gain initial access to a network and establish a foothold in the environment before delivering subsequent malicious payloads, including adware, botnets, trojans or pay-per-install campaigns.

CoinLoader is generally propagated through trojanized popular software or game installation archive files, usually in the rar or zip formats. These files tend can be easily obtained via top results displayed in search engines when searching for such keywords as "crack" or "keygen" in conjunction with the name of the software the user wishes to pirate [1,2,3,4]. By disguising the payload as a legitimate programme, CoinLoader is more likely to be unknowingly downloaded by endpoint users, whilst also bypassing traditional security measures that trust the download.

It also has several additional counter-detection methods including using junk code, variable obfuscation, and encryption for shellcode and URL schemes. It relies on dynamic-link library (DLL) search order hijacking to load malicious DLLs to legitimate executable files. The malware is also capable of performing a variety of checks for anti-virus processes and disabling endpoint protection solutions.

In addition to these counter-detection tactics, CoinLoader is also able to prevent the execution of its malicious DLL files in sandboxed environments without the presence of specific DNS cache records, making it extremely difficult for security teams and researchers to analyze.

In 2020 it was reported that CoinLoader compromises were regularly seen alongside cryptomining activity and even used the alias “CoinMiner” in some cases [2]. Darktrace’s investigations into CoinLoader in 2023 largely confirmed this theory, with around 15% of observed CoinLoader connections being related to cryptomining activity.

Cryptomining malware consumes large amounts of a hijacked (or cryptojacked) device's resources to perform complex mathematical calculations and generate income for the attacker all while quietly working in the background. Cryptojacking can lead to high electricity costs, device slow down, loss of functionality, and in the worst case scenario can be a potential fire hazard.

Darktrace Coverage of CoinLoader

In September 2023, Darktrace observed several cases of CoinLoader that served to exemplify the command-and-control (C2) communication and subsequent cryptocurrency mining activities typically observed during CoinLoader compromises. While the initial infection method in these cases was outside of Darktrace’s purview, it likely occurred via socially engineered phishing emails or, as discussed earlier, trojanized software downloads.

Command-and-Control Activity

CoinLoader compromises observed across the Darktrace customer base were typically identified by encrypted C2 connections over port 433 to rare external endpoints using self-signed certificates containing "OU=IT,O=MyCompany LLC,L=San Francisco,ST=California,C=US" in their issue fields.

All observed CoinLoader C2 servers were associated with the ASN of MivoCloud, a Virtual Private Server (VPS) hosting service (AS39798 MivoCloud SRL). It had been reported that Russian-state sponsored threat actors had previously abused MivoCloud’s infrastructure in order to bypass geo-blocking measures during phishing attacks against western nations [5].

Darktrace observed that the majority of CoinLoader infrastructure utilized IP addresses in the 185.225.0.0/19 range and were associated with servers hosted in Romania, with just one instance of an IP address based in Moldova. The domain names of these servers typically followed the naming pattern ‘*[a-d]{1}[.]info’, with 'ams-updatea[.]info’, ‘ams-updateb[.]info’, ‘ams-updatec[.]info’, and ‘ams-updated[.]info’ routinely identified on affected networks.

Researchers found that CoinLoader typically uses DNS tunnelling in order to covertly exchange information with attacker-controlled infrastructure, including the domains ‘candatamsnsdn[.]info’, ‘mapdatamsnsdn[.]info’, ‘rqmetrixsdn[.]info’ [4].

While Darktrace did not observe these particular domains, it did observer similar DNS lookups to a similar suspicous domain, namely ‘ucmetrixsdn[.]info’, in addition to the aforementioned HTTPS C2 connections.

Cryptomining Activity and Possible Additional Tooling

After establishing communication channels with CoinLoader servers, affected devices were observed carrying out a range of cryptocurrency mining activities. Darktrace detected devices connecting to multiple MivoCloud associated IP addresses using the MinerGate protocol alongside the credential “x”, a MinerGate credential observed by Darktrace in previous cryptojacking compromises, including the Sysrv-hello botnet.

Figure 1: Darktrace DETECT breach log showing an alerted mining activity model breach on an infected device.
Figure 2: Darktrace's Cyber AI Analyst providing details about unusual repeated connections to multiple endpoints related to CoinLoader cryptomining.

In a number of customer environments, Darktrace observed affected devices connected to endpoints associated with other malware such as the Andromeda botnet and the ViperSoftX information stealer. It was, however, not possible to confirm whether CoinLoader had dropped these additional malware variants onto infected devices.

On customer networks where Darktrace RESPOND was enabled in autonomous response mode, Darktrace was able to take swift targeted steps to shut down suspicious connections and contain CoinLoader compromises. In one example, following DETECT’s initial identification of an affected device connecting to multiple MivoCloud endpoints, RESPOND autonomously blocked the device from carrying out such connections, effectively shutting down C2 communication and preventing threat actors carrying out any cryptomining activity, or downloading subsequent malicious payloads. The autonomous response capability of RESPOND provides customer security teams with precious time to remove infected devices from their network and action their remediation strategies.

Figure 3: Darktrace RESPOND autonomously blocking CoinLoader connections on an affected device.

Additionally, customers subscribed to Darktrace’s Proactive Threat Notification (PTN) service would be alerted about potential CoinLoader activity observed on their network, prompting Darktrace’s Security Operations Center (SOC) to triage and investigate the activity, allowing customers to prioritize incidents that require immediate attention.

Conclusion

By masquerading as free or ‘cracked’ versions of legitimate popular software, loader malware like CoinLoader is able to indiscriminately target a large number of endpoint users without arousing suspicion. What’s more, once a network has been compromised by the loader, it is then left open to a secondary compromise in the form of potentially costly information stealers, ransomware or, in this case, cryptocurrency miners.

While urging employees to think twice before installing seemingly legitimate software unknown or untrusted locations is an essential first step in protecting an organization against threats like CoinLoader, its stealthy tactics mean this may not be enough.

In order to fully safeguard against such increasingly widespread yet evasive threats, organizations must adopt security solutions that are able to identify anomalies and subtle deviations in device behavior that could indicate an emerging compromise. The Darktrace suite of products, including DETECT and RESPOND, are well-placed to identify and contain these threats in the first instance and ensure they cannot escalate to more damaging network compromises.

Credit to: Signe Zaharka, Senior Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant

Appendix

Darktrace DETECT Model Detections

  • Anomalous Connection/Multiple Connections to New External TCP Port
  • Anomalous Connection/Multiple Failed Connections to Rare Endpoint
  • Anomalous Connection/Rare External SSL Self-Signed
  • Anomalous Connection/Repeated Rare External SSL Self-Signed
  • Anomalous Connection/Suspicious Self-Signed SSL
  • Anomalous Connection/Young or Invalid Certificate SSL Connections to Rare
  • Anomalous Server Activity/Rare External from Server
  • Compromise/Agent Beacon (Long Period)
  • Compromise/Beacon for 4 Days
  • Compromise/Beacon to Young Endpoint
  • Compromise/Beaconing Activity To External Rare
  • Compromise/High Priority Crypto Currency Mining
  • Compromise/High Volume of Connections with Beacon Score
  • Compromise/Large Number of Suspicious Failed Connections
  • Compromise/New or Repeated to Unusual SSL Port
  • Compromise/Rare Domain Pointing to Internal IP
  • Compromise/Repeating Connections Over 4 Days
  • Compromise/Slow Beaconing Activity To External Rare
  • Compromise/SSL Beaconing to Rare Destination
  • Compromise/Suspicious File and C2
  • Compromise/Suspicious TLS Beaconing To Rare External
  • Device/ Anomalous Github Download
  • Device/ Suspicious Domain
  • Device/Internet Facing Device with High Priority Alert
  • Device/New Failed External Connections

Indicators of Compromise (IoCs)

IoC - Hostname C2 Server

ams-updatea[.]info

ams-updateb[.]info

ams-updatec[.]info

ams-updated[.]info

candatamsna[.]info

candatamsnb[.]info

candatamsnc[.]info

candatamsnd[.]info

mapdatamsna[.]info

mapdatamsnb[.]info

mapdatamsnc[.]info

mapdatamsnd[.]info

res-smarta[.]info

res-smartb[.]info

res-smartc[.]info

res-smartd[.]info

rqmetrixa[.]info

rqmetrixb[.]info

rqmetrixc[.]info

rqmetrixd[.]info

ucmetrixa[.]info

ucmetrixb[.]info

ucmetrixc[.]info

ucmetrixd[.]info

any-updatea[.]icu

IoC - IP Address - C2 Server

185.225[.]16.192

185.225[.]16.61

185.225[.]16.62

185.225[.]16.63

185.225[.]16.88

185.225[.]17.108

185.225[.]17.109

185.225[.]17.12

185.225[.]17.13

185.225[.]17.135

185.225[.]17.14

185.225[.]17.145

185.225[.]17.157

185.225[.]17.159

185.225[.]18.141

185.225[.]18.142

185.225[.]18.143

185.225[.]19.218

185.225[.]19.51

194.180[.]157.179

194.180[.]157.185

194.180[.]158.55

194.180[.]158.56

194.180[.]158.62

194.180[.]158.63

5.252.178[.]74

94.158.246[.]124

IoC - IP Address - Cryptocurrency mining related endpoint

185.225.17[.]114

185.225.17[.]118

185.225.17[.]130

185.225.17[.]131

185.225.17[.]132

185.225.17[.]142

IoC - SSL/TLS certificate issuer information - C2 server certificate example

emailAddress=admin@example[.]ltd,CN=example[.]ltd,OU=IT,O=MyCompany LLC,L=San Francisco,ST=California,C=US

emailAddress=admin@'res-smartd[.]info,CN=res-smartd[.]info,OU=IT,O=MyCompany LLC,L=San Francisco,ST=California,C=US

CN=ucmetrixd[.]info,OU=IT,O=MyCompany LLC,L=San Francisco,ST=California,C=US

MITRE ATT&CK Mapping

INITIAL ACCESS

Exploit Public-Facing Application - T1190

Spearphishing Link - T1566.002

Drive-by Compromise - T1189

COMMAND AND CONTROL

Non-Application Layer Protocol - T1095

Non-Standard Port - T1571

External Proxy - T1090.002

Encrypted Channel - T1573

Web Protocols - T1071.001

Application Layer Protocol - T1071

DNS - T1071.004

Fallback Channels - T1008

Multi-Stage Channels - T1104

PERSISTENCE

Browser Extensions

T1176

RESOURCE DEVELOPMENT

Web Services - T1583.006

Malware - T1588.001

COLLECTION

Man in the Browser - T1185

IMPACT

Resource Hijacking - T1496

References

1. https://www.avira.com/en/blog/coinloader-a-sophisticated-malware-loader-campaign

2. https://asec.ahnlab.com/en/17909/

3. https://www.cybereason.co.jp/blog/cyberattack/5687/

4. https://research.checkpoint.com/2023/tunnel-warfare-exposing-dns-tunneling-campaigns-using-generative-models-coinloader-case-study/

5. https://securityboulevard.com/2023/02/three-cases-of-cyber-attacks-on-the-security-service-of-ukraine-and-nato-allies-likely-by-russian-state-sponsored-gamaredon/

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
Signe Zaharka
Principal Cyber Analyst

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July 31, 2026

Building Operational Resilience Across Mission-Critical Marine Services

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Mission-Critical Marine Services

This marine organization supports offshore energy production, export infrastructure, and regional logistics, delivering critical services through its diverse fleet and a regional shorebase footprint. To power rapid mobilization and 24/7 operational readiness, the organization has embraced cloud adoption and digital transformation, reshaping how crews, contractors, and shore-based teams access services.

While technology modernization has enhanced operations, it has also introduced new security complexities.

  • From perimeter to identity: As access becomes more distributed, identity has become the primary security control, elevating the risk of credential compromise and privilege misuse.
  • From confidentiality to availability and resilience: As cloud platforms increasingly underpin fleet and operational systems, cyber incidents can disrupt services and safety.
  • From isolated tools to unified visibility:  Because Information Technology (IT) and Operational Technology (OT) often intersect, and legacy systems coexist with modern cloud platforms, fragmented monitoring makes it harder to understand risk and respond decisively across domains.
“Our cybersecurity priorities expanded along with our business goals, placing availability and resilience at the forefront. The impact of a potential threat became an operational risk, which elevated cybersecurity from an IT issue to an operational safety and resilience enabler.” - Information and Communications Technology (ICT) Manager.

A Unified, AI-Driven Platform for IT and OT

To strengthen visibility, detection, and response across its highly distributed environment, the customer adopted the Darktrace ActiveAI Security Platform™ in 2022.

Darktrace’s contextual detection capability was a key driver. Unlike traditional tools that rely on known threat signatures, Darktrace’s Self-Learning AI learns “normal” behavior to identify emerging threats and correlate visibility across the customer's siloed on-premises and cloud domains.

Today, the customer relies on:

  • Darktrace / EMAIL™ to reduce phishing risk and minimize disruption from legacy mail controls and false positives
  • Darktrace / IDENTITY™ to support identity-centric security as cloud access expands across vessels and shore-based operations
  • Darktrace / NETWORK™ to strengthen oversight across the broader environment, including operational contexts where IT and OT intersect
  • Darktrace / CLOUD™ (Azure), added in 2024, to extend detection and response into Azure and support cloud transformation without treating cloud as a separate security silo
  • Darktrace / Incident Readiness & Recovery to strengthen incident readiness and recovery planning
  • Darktrace Managed Detection and Response Services to provide 24/7/365 monitoring and support

This combination supports a single operating model for the customer: security that can adapt as the environment changes while remaining practical for a lean team responsible for safeguarding both business operations and safety-critical services.

Extending cloud protection without complexity

As the customer accelerated cloud adoption, it expanded coverage in 2024 with Darktrace / CLOUD for Azure to bring cloud workloads under the same AI-driven visibility and response model – without adding operational burden. “This matters in hybrid environments because attacks rarely stay in one place,” explains the ICT Manager. “A compromised identity can trigger activity in the cloud, which can open pathways back into on-premises systems.”

In parallel, Darktrace / CLOUD’s posture management capabilities support governance and audit readiness by surfacing misconfigurations and exposure risks earlier, before they become incidents.

A Stronger, Faster, More Resilient Business

Since adopting Darktrace, the customer has strengthened cyber resilience while reducing operational burden on its small ICT team.

Darktrace continuously analyzes millions of individual events that can contribute to a wider incident. Within a single month, the solution autonomously investigated 88% of all potential threats, taking appropriate action within just 39.4 seconds on average.

Autonomous capabilities ensure threats are stopped and contained until the ICT team can investigate. In one standout instance, Darktrace autonomously blocked malicious links during a mass phishing/spam event before other controls flagged the threat. the ICT Manager later confirmed Microsoft reported the link as malicious, but Darktrace had already acted to prevent delivery and reduce exposure.

“Whether something happens during off hours, while we’re on vacation, or when our attention is focused elsewhere, we’re confident Darktrace will take control and stop a threat before it spreads,” says the ICT Manager.

Darktrace’s Self-Learning AI combines multiple AI methods and advanced techniques to improve threat detection, investigation, and response dramatically reducing alert overload and manual triage. Within a single month, the solution saved the customer's IT group 411 equivalent human investigation hours.

“For a lean team supporting a 24/7 operational footprint, this autonomous action eliminates the constant firefighting and stress, giving us the space to focus on higher-value priorities.”- Information and Communications Technology (ICT) Manager.

Protecting communications without disruption

the customer experienced friction from legacy email and network controls prior to Darktrace, which generated high false positive rates, disrupted legitimate communications, created operational drag, and added workload for ICT. With Darktrace / EMAIL learning normal email behavior and applying context-aware actions, the team reduced unnecessary interruptions while maintaining protection.

“That shift matters in marine services, where business communications directly support coordination across vessels, shore bases, clients, ports, and regulators,” says the ICT Manager. “Darktrace doesn’t just block more threats, it autonomously makes decisions that preserve operational continuity and enable my team to focus on credible threats instead of chasing volume.”

Delivering clarity and confidence

Darktrace has reduced manual triage by correlating activity across email, identity, network, and cloud, providing the context needed to prioritize what matters without requiring the ICT team to stitch together evidence across multiple tools.

“With unified visibility we can identify patterns across domains, make informed decisions about where risk actually exists, and align security actions with operational impact rather than theoretical threats,” explains the ICT Manager. “I can now prioritize effort and investment across our ICT landscape with far greater confidence.”

Regular Executive Threat Reports reinforce operational confidence by giving leadership clear visibility into threats Darktrace has handled autonomously, supporting decisive action when needed and confidence to avoid unnecessary disruption when it isn’t.

Scaling Securely in a Hybrid World

As the customer advances its cloud transformation, the ICT Manager sees the Darktrace partnership evolving into a foundational layer of resilience and assurance, supporting scale, governance, and operational confidence in an increasingly cloud-centric environment.

Key priorities include:

  • Shifting from hybrid visibility to cloud-first resilience, using continuous monitoring and posture insights to reduce exposure earlier
  • Strengthening governance and audit readiness, especially as critical workloads and sensitive data expand in Azure and expectations rise under regulatory and client assurance requirements
  • Increasing reliance on autonomous response and AI investigation as the number of identities, workloads, and access paths grows faster than headcount
  • Deepening cross-domain correlation so cloud signals further enrich decision-making, supporting faster containment and more confident prioritization

“As we accelerate our cloud strategy, Darktrace will play an even more strategic role,” says the ICT Manager, “providing the guidance, technology, and expertise that allow us to grow with confidence and innovate securely.”

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July 28, 2026

Hiding in Plain Sight: Uncovering a Multi-Stage Ransomware Attack Through Behavioral Detection

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Why ransomware has changed

Ransomware attacks have continued to increase globally, with 698 incidents reported in May 2026, representing a 48% rise compared to 472 incidents in May 2025 [1]. At the same time, the ransomware landscape is evolving. Several major ransomware groups, including LockBit [2], have been disrupted by successful joint law enforcement operations, resulting in a shift away from a small number of dominant actors towards a more fragmented and distributed ecosystem. This is increasingly composed of smaller groups who play a specialized role in the attack, such as initial access brokers, affiliates or developers.

As a result, ransomware tactics, techniques, and procedures (TTPs) are becoming more diverse and less predictable. On top of this, adversaries are leveraging native tools and legitimate penetration testing frameworks to evade detection. Anomaly-based detection is therefore critical to identify pre-ransomware activity, rather than relying on signatures associated with a handful of well-known ransomware groups.

As these attacks often unfold over several days, there is a critical window for defenders to act. In this context, behavioral-based detection plays a vital role in identifying suspicious pre-ransomware activity, and enabling early intervention before encryption or exfiltration occurs.

Inside a modern ransomware intrusion

In early 2026, Darktrace detected activity within a customer’s environment related to a multi-stage ransomware intrusion from the initial compromise. This activity does not appear to be attributable to a specific ransomware group, and no known ransomware payload was observed until the final stage.

The attack aligns with a broader industry trend in which compromised virtual private network (VPN) credentials are used as an entry point, followed by rapid internal reconnaissance and lateral movement using legitimate administrative tools. This growing preference for native tools and legitimate frameworks in cyber-attacks illustrates that it is increasingly unreliable to depend solely on traditional indicators of compromise such as known malware signatures or exploit detection.

The intrusion also involved the use of Sliver, an open-source adversary emulation framework, which is increasingly observed in real-world attacks. Originally designed for penetration testing and red teaming, Sliver has gained traction among threat actors as a stealthier alternative to more heavily signatured frameworks such as Cobalt Strike. As a legitimate framework, its use further complicates detection for security tools that rely on known malicious signatures.

Darktrace’s detection of a ransomware event in a customer’s environment

The initial compromise appears to have occurred via compromised credentials used over the VPN shortly before, or at the onset of the first indicators of suspicious activity. While it remains unclear as to how or when the threat actors gained access to these credentials, the use of initial access brokers (IABs) is a common feature of modern ransomware operations. This suggests that access to the environment may have been established several days or weeks beforehand.

The intrusion unfolded over three days, presenting multiple opportunities for early detection and intervention before ransomware deployment. The attack progressed through a compressed but structured sequence: initial access and reconnaissance were completed within hours, followed by privilege escalation and lateral movement the next day, and culminating in data exfiltration and encryption shortly thereafter. Throughout each stage, distinct behavioral anomalies emerged across the network providing clear indicators of malicious activity well before the ransomware was deployed.

While Darktrace’s Autonomous Response capability was enabled within the customer’s environment, it was not fully configured across the impacted devices, allowing the attack to progress to ransomware deployment. Had Autonomous Response been fully deployed across the affected systems, it could have taken targeted action against the earliest stages of malicious activity, potentially disrupting the intrusion before it escalated.

Figure 1: Timeline of the attack progression.

Day 1: Reconnaissance and privilege escalation

The threat actor gained access via compromised VPN credentials and initiated internal reconnaissance. Darktrace detected anomalous scanning behavior, including unusual port scanning activity and widespread network enumeration.

Specifically, Darktrace detected a high volume of east-west scanning activity across a broad range of ports, with TCP connections targeting ports 21, 80, 445, 4899 and 8080. Associated URIs suggested the use of Nmap, a widely used penetration testing tool. This highlights how attackers often leverage legitimate penetration testing tools for malicious reconnaissance, enabling them to blend into normal network activity and evade traditional signature-based detection methods.

Figure 2: Darktrace's detection of a sharp increase in anomalous internal connections, triggering multiple high-severity model alerts associated with reconnaissance activity.

Several devices were observed using administrative credentials to carry out privileged actions in a manner that was highly anomalous for the environment. This activity was accompanied by behavior consistent with SMB authentication scanning, suggesting efforts to identify and access additional systems. As the activity intensified, an increasing number of devices became involved, signalling lateral movement and further spread across the network.

Darktrace also identified privilege escalation through active directory (AD) replication abuse, specifically via the drsuapi::DRSGetNCChanges function. This technique allows an attacker with sufficient privileges to request directory replication data from a domain controller (DC), enabling them to extract credentials, including password hashes, without directly interacting with user accounts. Commonly associated with ‘DCSync’ attacks, this technique is frequently used to obtain highly privileged credentials and enable further escalation within an environment.

Figure 3: Darktrace’s detection of anomalous AD replication activity indicative of privilege escalation.

This activity was seen alongside the use of the now obsolete SMBv1, repeated NTLM authentication attempts using multiple variations of ‘Administrator’ credentials, reverse DNS scanning, and large-scale network scanning. Darktrace observed widespread use of SMBv1 across the customer’s environment, exposing a significant security weakness. As a legacy protocol with well-documented weaknesses, SMBv1 can be exploited to facilitate lateral movement, allowing the attackers to expand their access following initial compromise.

Day 3: Lateral Movement, Command & Control, and Exfiltration

Two days later, the attacker escalated privileges and expanded their foothold using living-off-the-land (LOTL) techniques such as PSExec, WMI, and RDP. Concurrently, Darktrace identified command-and-control (C2)-style communications consistent with the Sliver framework, alongside rare outbound connections to cloud infrastructure indicating potential data exfiltration. The volume and severity of observed activity increased as attack behavior intensified.

The device was observed conducting extensive lateral movement, leveraging LOTL techniques to evade detection. Activity included WMI execution (e.g. ExecQuery), DCE-RPC activity, SMB sessions and file writes, most of which were successful, as well as the deployment of PSEXESVC.exe via ADMIN$ shares and prolonged RDP sessions. Darktrace identified this behavior as highly anomalous for the environment. Such activity is commonly associated with the transfer of attacker tooling, remote command execution, and the establishment of persistent access across compromised systems.  

Figure 4: Darktrace’s detection of a spike in RPC binding events indicative of potential lateral movement.

On the same day, Darktrace detected C2-style SSL communications originating from multiple internal devices to rare external endpoints. These connections exhibited anomalous characteristics, including invalid SSL certificates and repeated connection patterns resembling beaconing. Analysis of the observed JA3 fingerprint further linked the activity to Sliver, the adversary simulation framework referenced earlier, as the hash has previously been associated with Sliver-related infrastructure [3]. The use of this framework reflects a broader trend of attackers repurposing legitimate offensive security tools for stealthy C2 communications. Connections to 137[.]220[.]59[.]55 (ASN AS20473 AS-VULTR) indicated that the communications were likely routed via a virtual private server (VPS) hosted by Vultr. Attackers often utilize VPS infrastructure from legitimate cloud providers like Vultr to obscure their true origin, blend into benign traffic, and evade IP-based detection mechanisms [4].

Figure 5: Darktrace’s Cyber AI Analyst detection of two linked unusual connections to Vultr infrastructure.

Darktrace also observed a device initiating SSL connections to safedata.s3[.]wasabisys[.]com, an endpoint associated with Wasabi cloud storage. Darktrace recognized that neither the destination nor the associated IP address had previously been observed within the environment.  More than 200 MB of data was subsequently uploaded externally to endpoints sharing the same JA3 client hash, indicating a sustained transfer session and potential data exfiltration to third-party storage. The apparent exfiltration prior to encryption is consistent with a double-extortion ransomware strategy.

Figure 6: Darktrace’s Cyber AI Analyst detection of more than 30 rare outbound connections to a Wasabi cloud storage endpoint, indicative of potential data exfiltration

Day 4: Encryption

The attack culminated in ransomware deployment, marking the transition from suspicious network activity to a business-impacting incident. Using SMB-based propagation, the threat actor encrypted thousands of files across the network, affecting multiple systems and disrupting normal operations. Throughout the encryption event, the legacy SMBv1 protocol was used extensively across multiple internal systems, resulting in a significant increase in newly encrypted files.

Figure 7: Darktrace’s detection of abnormal spikes in SMB activity and associated model alerts, indicative of ransomware encryption and propagation.

Darktrace’s Cyber AI Analyst automatically investigated and correlated the encryption activity and related events into a single incident narrative, providing the customer with real-time visibility into the attack while significantly reducing investigation time.

Figure 8: Darktrace’s Cyber AI Analyst’s investigation into the encryption activity. AI Analyst incident detailing example encryption activity in real time. Related events are automatically correlated and summarized into a clear narrative, reducing investigation time.

Defender action recommendations

What Could Have Stopped the Attack Earlier?

Although the attack ultimately resulted in ransomware deployment, there were multiple opportunities to detect, contain, and disrupt the intrusion before encryption occurred. The following actions could have significantly reduced the overall impact:

Detect and investigate indicators of reconnaissance and lateral movement

  • Unusual scanning
  • Active Directory replication anomalies consistent with DCSync activity
  • Anomalous use of native tools and processes indicative of LOTL attacks
  • Unusual use of common reconnaissance tools such as Nmap and NetScan

Contain compromised credentials and affected devices

  • Disable and reset compromised VPN credentials
  • Isolate devices performing anomalous scanning and lateral movement activity

Block suspicious external communications and data exfiltration

  • Use anomaly-based detection to detect and block repeated outbound connections to rare external infrastructure
  • Prevent data exfiltration to unauthorized cloud storage services such as Wasabi

Conclusion

The incident highlights the importance of anomaly-based detection, particularly against attacks that primarily use native or legitimate tools to evade traditional security measures. Darktrace identified suspicious activity from the first day of the compromise, providing multiple opportunities to disrupt the intrusion before it progressed to lateral movement and data exfiltration.

In this instance, detection was not the limiting factor; response time was. Prompt investigation and containment of devices exhibiting anomalous behavior could have prevented lateral movement, data exfiltration, and ultimately ransomware deployment.

As adversaries increasingly prioritize stealth over custom malware, relying instead on legitimate tools, valid credentials, and trusted infrastructure, traditional signature-based detection becomes less effective. Identifying subtle behavioral deviations early remains critical to disrupting attacks before they escalate into full-scale ransomware incidents.

Credit to Alexandra Evzona (Cyber Analyst), Priya Thapa (Senior Cyber Analyst)
Edited by Ryan Traill (Content Manager)

Appendices

References

[1] https://industrialcyber.co/ransomware/check-point-reports-ransomware-attacks-jump-48-year-over-year-despite-decline-in-overall-cyberattack-activity/

[2] https://www.europol.europa.eu/media-press/newsroom/news/law-enforcement-disrupt-worlds-biggest-ransomware-operation

[3] https://fieldeffect.com/blog/field-effect-mitigates-not-so-simplehelp-exploits-enabling-deployment-of-backdoors

[4] https://www.darktrace.com/blog/from-vps-to-phishing-how-darktrace-uncovered-saas-hijacks-through-virtual-infrastructure-abuse

Indicators of Compromise (IoCs)

IP Addresses

  • 137[.]220[.]59[.]55 – Potential C2 infrastructure (Vultr AS20473)
  • 38[.]27[.]106[.]123 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]128 – Wasabi cloud storage endpoint associated with potential data exfiltration
  • 38[.]27[.]106[.]117 – Wasabi cloud storage endpoint associated with potential data exfiltration

Domains

  • safedata[.]s3[.]wasabisys[.]com – Potential data exfiltration endpoint
  • *.wasabisys[.]com – Associated Wasabi cloud storage infrastructure

JA3 Fingerprint

  • d6828e30ab66774a91a96ae93be4ae4c – Associated with the Sliver adversary emulation framework

Files

  • Delete[.]me – File observed during reconnaissance activity, commonly associated with NetScan

Darktrace Model Coverage

·       Anomalous Connection / Active Remote Desktop Tunnel

·       Anomalous Connection / Anomalous Remote Registry Service Control

·       Anomalous Connection / Multiple Failed Windows UDP

·       Anomalous Connection / New or Uncommon Service Control

·       Anomalous Connection / New or Uncommon Service Enumeration

·       Anomalous Connection / New User Agent to IP Without Hostname

·       Anomalous Connection / SMB Enumeration

·       Anomalous Connection / Suspicious Activity On High Risk Device

·       Anomalous Connection / Suspicious Read Write Ratio

·       Anomalous Connection / Sustained MIME Type Conversion

·       Anomalous Connection / Uncommon 1 GiB Outbound

·       Anomalous Connection / Unusual Admin RDP Session

·       Anomalous Connection / Unusual Admin SMB Session

·       Anomalous Connection / Unusual SMB Version 1 Connectivity

·       Anomalous File / EXE from Rare External Location

·       Anomalous File / Internal / Additional Extension Appended to SMB File

·       Anomalous Server Activity / Outgoing from Server

·       Compromise / Beaconing Activity To External Rare

·       Compromise / Ransomware / Possible Ransom Note Read

·       Compromise / Ransomware / Ransom or Offensive Words Written to SMB

·       Compromise / Ransomware / Suspicious SMB Activity

·       Device / Anonymous NTLM Logins

·       Device / Attack and Recon Tools

·       Device / Initial Attack Chain Activity

·       Device / Large Number of Model Alerts

·       Device / Long Agent Connection to New Endpoint

·       Device / Multiple Lateral Movement Model Alerts

·       Device / Network Scan

·       Device / New or Uncommon SMB Named Pipe

·       Device / New or Unusual Remote Command Execution

·       Device / New User Agent

·       Device / Possible RPC Lateral Movement

·       Device / Possible SMB/NTLM Brute Force

·       Device / RDP Scan

·       Device / SMB Lateral Movement

·       Device / SMB Session Brute Force (Non-Admin)

·       Device / SMB Version 1 Access Failures

·       Device / Suspicious File Delete Activity

·       Device / Suspicious Network Scan Activity

·       Device / Unusual SMB Error Detected

·       Device / Unusual SMB To Critical Resource

·       Device / Unusual Winreg Operation

·       Unusual Activity / Multiple Failed Internal Connections

·       Unusual Activity / Possible RPC Recon Activity

·       Unusual Activity / Sustained Anomalous SMB Activity

·       Unusual Activity / Unusual External Data to New Endpoint

·       Unusual Activity / Unusual External Data Transfer

·       Unusual Activity / Unusual File Storage Data Transfer

·       Unusual Activity / Unusual Large Internal Transfer

·       User / New Admin Credentials on Client

·       User / NTLM Login from Unauthenticated Device

Autonomous Response Model Alerts

·       Antigena / Network / External Threat / Antigena Ransomware Block

·       Antigena / Network / External Threat / Antigena Suspicious File Block

·       Antigena / Network / Insider Threat / Antigena Active Threat SMB Write Block

·       Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity

·       Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block

·       Antigena / Network / Insider Threat / Antigena Network Scan Block

·       Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block

·       Antigena / Network / Manual / Quarantine Device

·       Antigena / Network / Significant Anomaly / Antigena Alerts Over Time Block

·       Antigena / Network / Significant Anomaly / Antigena Controlled and Model Alert

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block

·       Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block 100

·       Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block

MITRE ATT&CK MAPPING

Command and control - Protocol Tunneling - T1572

Command and control – Web Protocols – T1071.001

Credential Access- Exploitation for Credential Access- T1212

Credential Access- Password Guessing- T1110

Discovery- File and Directory Discovery- T1083

Discovery- Network Service Discovery- T1046

Discovery- Network Share Discovery- T1135

Discovery- Remote System Discovery- T1018

Exfiltration- Exfiltration Over C2 Channel- T1041

Exfiltration- Exfiltration to Cloud Storage- T1567

Impact- Data Encrypted for Impact- T1486

Impact- Data Encrypted for Impact- T1486

Impact- Service Stop - T1489

Initial Access- Public-Facing Application- T1190

Lateral Movement- Exploitation of Remote Services- T1210

Lateral Movement- Remote Desktop Protocol- T1021

Lateral Movement- SMB/Windows Admin Shares- T1021

Lateral Movement- Taint Shared Content- T1080

Persistence- Modify Registry- T1112

Privilege Escalation- Exploitation for Privilege Escalation- T0890

Privilege Escalation- Valid Accounts- T1078

Reconnaissance- Scanning IP Blocks- T1595

Reconnaissance- Vulnerability Scanning- T1595

Resource Development- Malware- T1588

Stealth- File Deletion- T1070

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About the author
Alexandra Evzona
Cyber Analyst
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