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September 6, 2021

What Are the Early Signs of a Ransomware Attack?

Discover the early signs of ransomware and how to defend against it. Often attack is the best form of defense with cybersecurity. Learn more here!
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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager
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06
Sep 2021

The deployment of ransomware is the endgame of a cyber-attack. A threat actor must have accomplished several previous steps – including lateral movement and privilege escalation – to reach this final position. The ability to detect and counter the early moves is therefore just as important as detecting the encryption itself.

Attackers are using diverse strategies – such as ‘Living off the Land’ and carefully crafting their command and control (C2) – to blend in with normal network traffic and evade traditional security defenses. The analysis below examines the Tactics, Techniques and Procedures (TTPs) used by many ransomware actors by unpacking a compromise which occurred at a defense contractor in Canada.

Phases of a ransomware attack

Figure 1: Timeline of the attack.

The opening: Initial access to privileged account

The first indicator of compromise was a login on a server with an unusual credential, followed by unusual admin activity. The attacker may have gained access to the username and password in a number of ways, from credential stuffing to buying them on the Dark Web. As the attacker had privileged access from the get-go, there was no need for privilege escalation.

Lateral movement

Two days later, the attacker began to spread from the initial server. The compromised server began to send out unusual Windows Management Instrumentation (WMI) commands.

It began remotely controlling four other devices – authenticating on them with a single admin credential. One of the destinations was a domain controller (DC), another was a backup server.

By using WMI – a common admin tool – for lateral movement, the attacker opted to ‘live off the land’ rather than introduce a new lateral movement tool, aiming to remain unnoticed by the company’s security stack. The unusual use of WMI was picked up by Darktrace and the timings of the unusual WMI connections were pieced together by Cyber AI Analyst.

Models:

  • New or Uncommon WMI Activity
  • AI Analyst / Extensive Chain of Administrative Connections

Establish C2

The four devices then connected to the IP 185.250.151[.]172. Three of them, including the DC and backup server, established SSL beacons to the IP using the dynamic DNS domain goog1e.ezua[.]com.

The C2 endpoints had very little open-source intelligence (OSINT) available, but it seems that a Cobalt Strike-style script had used the endpoint in the past. This suggests complex tooling, as the attacker used dynamic SSL and spoofed Google to mask their beaconing.

Interestingly, through the entirety of the attack, only these three devices used SSL connections for beaconing, while later C2 occurred over unencrypted protocols. It appears these three critical devices were treated differently to the other infected devices on the network.

Models:

  • Immediate breach of Anomalous External Activity from Critical Network Device, then several model breaches involving beaconing and SSL to dynamic DNS. (Domain Controller DynDNS SSL or HTTP was particularly specific to this activity.)

The middle game: Internal reconnaissance and further lateral movement

The attack chain took the form of two cycles of lateral movement, followed by establishing C2 at the newly controlled destinations.

Figure 2: Observed chain of lateral movement and C2.

So, after establishing C2, the DC made WMI requests to 20 further IPs over an extended period. It also scanned 234 IPs via ICMP pings, presumably in an attempt to find more hosts.

Many of these were eventually found with ransom notes, in particular when the targeted devices were hypervisors. The ransomware was likely deployed with remote commands via WMI.

Models:

  • AI Analyst / Suspicious Chain of Administrative Connections (from the initial server to the DC to the hypervisor)
  • AI Analyst / Extensive Suspicious WMI Activity (from the DC)
  • Device / ICMP Address Scan, Scanning of Multiple Devices AI Analyst incident (from the DC)

Further C2

As the second stage of lateral movement stopped, a second stage of unencrypted C2 was seen from five new devices. Each started with GET requests to the IP seen in the SSL C2 (185.250.151[.]172), which used the spoofed hostname google[.]com.

Activity started on each device with HTTP requests for a URI ending in .png, before a more consistent beaconing to the URI /books/. Eventually, the devices made POST requests to the URI /ebooks/?k= (a unique identifier for each device). All this appears to be a way of concealing a C2 beacon in what looks like plausible traffic to Google.

In this way, by encrypting some C2 connections with SSL to a Dynamic DNS domain, while crafting other unencrypted HTTP to look like traffic to google[.]com, the attacker managed to operate undetected by the company’s antivirus tools.

Darktrace identified this anomalous activity and generated a large number of external connectivity model breaches.

Models:

  • Eight breaches of Compromise / HTTP Beaconing to New Endpoint from the affected devices

Accomplish mission: Checkmate

Finally, the attacker deployed ransomware. In the ransom note, they stated that sensitive information had been exfiltrated and would be leaked if the company did not pay.

However, this was a lie. Darktrace confirmed that no data had been exfiltrated, as the C2 communications had sent far too little data. Lying about data exfiltration in order to extort a ransom is a common tactic for attackers, and visibility is crucial to determine whether a threat actor is bluffing.

In addition, Antigena – Darktrace’s Autonomous Response technology – blocked an internal download from one of the servers compromised in the first round of lateral movement, because it was an unusual incoming data volume for the client device. This was most likely the attacker attempting to transfer data in preparation for the end goal, so the block may have prevented this data from being moved for exfiltration.

Figure 3: Antigena model breach.

Figure 4: Device is blocked from SMB communication with the compromised server three seconds later.

Models:

  • Unusual Incoming Data Volume
  • High Volume Server Data Transfer

Unfortunately, Antigena was not active on the majority of the devices involved in the incident. If in active mode, Antigena would have stopped the early stages of this activity, including the unusual administrative logins and beaconing. The customer is now working to fully configure Antigena, so they benefit from 24/7 Autonomous Response.

Cyber AI Analyst investigates

Darktrace’s AI spotted and reported on beaconing from several devices including the DC, which was the highest scoring device for unusual behavior at the time of the activity. It condensed this information into three incidents – ‘Possible SSL Command and Control’, ‘Extensive Suspicious Remote WMI Activity’, and ‘Scanning of Remote Devices’.

Crucially, Cyber AI Analyst not only summarized the admin activity from the DC but also linked it back to the first device through an unusual chain of administrative connections.

Figure 5: Cyber AI Analyst incident showing a suspicious chain of administrative connections linking the first device in the chain of connections to a hypervisor where a ransom note was found via the compromised DC, saving valuable time in the investigation. It also highlights the credential common to all of the lateral movement connections.

Finding lateral movement chains manually is a laborious process well suited to AI. In this case, it enabled the security team to quickly trace back to the device which was the likely source of the attack and find the common credential in the connections.

Play the game like a machine

To get the full picture of a ransomware attack, it is important to look beyond the final encryption to previous phases of the kill chain. In the attack above, the encryption itself did not generate network traffic, so detecting the intrusion at its early stages was vital.

Despite the attacker ‘Living off the Land’ and using WMI with a compromised admin credential, as well as spoofing the common hostname google[.]com for C2 and applying dynamic DNS for SSL connections, Darktrace was able to identify all the stages of the attack and immediately piece them together into a meaningful security narrative. This would have been almost impossible for a human analyst to achieve without labor-intensive checking of the timings of individual connections.

With ransomware infections becoming faster and more frequent, with the threat of offensive AI looming closer and the Dark Web marketplace thriving, with security teams drowning under false positives and no time left on the clock, AI is now an essential part of any security solution. The board is set, the time is ticking, the stakes are higher than ever. Your move.

Thanks to Darktrace analyst Daniel Gentle for his insights on the above threat find.

IoCs:

IoCComment185.250.151[.]172IP address used for both HTTP and SSL C2goog1e.ezua[.]comDynamic DNS Hostname used for SSL C2

Darktrace model detections:

  • AI Analyst models:
  • Extensive Suspicious WMI Activity
  • Suspicious Chain of Administrative Connections
  • Scanning of Multiple Devices
  • Possible SSL Command and Control
  • Meta model:
  • Device / Large Number of model breaches
  • External connectivity models:
  • Anonymous Server Activity / Domain Controller DynDNS SSL or HTTP
  • Compromise / Suspicious TLS Beaconing to Rare External
  • Compromise / Beaconing Activity To External Rare
  • Compromise / SSL to DynDNS
  • Anomalous Server Activity / External Activity from Critical Network Device
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Suspicious Beaconing Behaviour
  • Compromise / HTTP Beaconing to New Endpoint
  • Internal activity models:
  • Device / New or Uncommon WMI Activity
  • User / New Admin Credentials on Client
  • Device / ICMP Address Scan
  • Anomalous Connection / Unusual Incoming Data Volume
  • Unusual Activity / High Volume Server Data Transfer

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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager

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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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