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May 25, 2022

Understanding Grief Ransomware Attacks

Discover the latest insights on Grief ransomware and how to protect your organization. Stay informed on evolving cybersecurity threats with the cyber experts.
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
Oakley Cox
Director of Product
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25
May 2022

The Grief ransomware strain, also referred to as PayOrGrief, quickly gained a reputation for disruption in mid-to-late 2021. The gang behind the malware used quadruple-extortion ransomware tactics and targeted a range of victims including municipalities and school districts.

In July 2021, just weeks after the strain was first reported to cyber security teams, Grief successfully targeted Thessaloniki, the second largest city in Greece. Faced with a $20 million ransom demand, the municipality’s security team was forced to shut down all of its websites and public-facing services and launch a full investigation into the breach.

Double act: Grief and DoppelPaymer

From its emergence in May 2021, Grief used novel malware which confounded security tools trained on historical attacks. By July, however, the sophistication and efficiency of the group’s attacks led many to suspect that Grief’s operators had experience beyond their supposed two months of operation.

Grief is now widely reported to be a rebrand of the DoppelPaymer ransomware gang, which ended its operations in May 2021 and was believed to be affiliated with the Russian ransomware gang Evil Corp. After adopting the new moniker, however, Grief regularly blew past traditional security tools, amassing well over $10 million in ransom payments in just four months.

Adaptations and rebrands are common techniques adopted by criminal gangs using the Ransomware-as-a-Service business model. The success of Grief’s rebrand illustrates how rapidly a ransomware group can update its attacks and render them unrecognizable to signature-based tools.

Revealing Grief’s tricks with Cyber AI Analyst

In July 2021, PayOrGrief targeted a European manufacturing company which had Darktrace deployed across its network. Darktrace’s early detection of the attack, along with the real-time visibility into its lifecycle offered by Darktrace’s Cyber AI Analyst, meant that each stage of the attack was clear to see.

Figure 1: Timeline of the PayOrGrief attack

The initial intrusion compromised four devices, which Darktrace detected when these devices connected to rare external IPs and downloaded encoded text files. It is likely that the devices were compromised as the result of a targeted phishing campaign, which are often used in Grief attacks as a way of injecting malware such as Dridex onto devices. If deployed within the targeted organization, Antigena Email would have identified the phishing campaign and halted it, before it reached employee inboxes. In this case, however, the attack continued.

Following the initial compromise, C2 (Command and Control) connections were made over an encrypted channel using invalid SSL certificates. An upload of 50MB of data was made from one of the infected devices to the company’s corporate server, which gave the attackers access to the company’s crown jewels: its most sensitive data. From this privileged position, and with keep-alive beacons in place, the attack was ready for detonation.

Several devices were detected attempting to upload data totaling more than 100 GB to the external file storage platform, Mega, using encrypted HTTPS on port 443. However, the attackers did not receive the total package of data they had expected. The organization had deployed Darktrace’s Autonomous Response to protect its key assets and most sensitive data. The AI recognized the anomalous behavior as a significant deviation from the business’s normal ‘pattern of life’ and autonomously blocked uploads from protected devices, preventing exfiltration wherever it was able to do so.

Figure 2: Data exfiltration from a single device, investigated by Cyber AI Analyst

The attackers then continued to spread through the digital environment. Using ‘Living off the Land’ techniques including RDP and SMB, they performed internal reconnaissance, escalated their privileges and moved laterally to additional digital assets. With access to new admin credentials, just ten hours after the initial C2 communications, the attackers commenced ransomware encryption.

It’s highly possible, therefore, that Grief has targeted Darktrace customers previously and been neutralized too early for the attack to be identified and attributed. In this instance, the organization had deployed Autonomous Response only on certain areas of the network, and we are therefore able to see how the attack progressed on unprotected devices.

Unusual suspects

The Indicators of Compromise (IoCs) for Grief ransomware have now been incorporated by many traditional security tools, but this is a short-term solution, and won’t account for further changes in both threat actor tactics and the digital environments they target. Once the Grief moniker has been exhausted, it is more than likely that another will be adopted in its place.

The AI-driven approach to cyber security tackles threats regardless of when and where they arrive, or what name they arrive under. By focusing on developing its sophisticated understanding of the entire digital estate, Darktrace’s Autonomous Response targets specific anomalies with specific, proportionate responses, even when they are part of entirely novel attacks. And when given the freedom to take action against these threats the moment they’re detected, Autonomous Response can ensure that organizations stay protected even when human teams are unavailable.

Thanks to Darktrace analyst Beverly McCann for her insights on the above threat find.

Technical details

Darktrace model detections

  • Device / Suspicious SMB Scanning Activity
  • Device / New User Agents
  • Anomalous Server Activity / Rare External from Server
  • Compliance / External Windows Communications
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Connection / Anomalous SSL without SNI to New External
  • Anomalous Connection / Rare External SSL Self-Signed
  • Anomalous Connection / Multiple Connections to New External TCP Port
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Compliance / Remote Management Tool on Server
  • Anomalous Server Activity / Outgoing from Server
  • Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
  • Anomalous Connection / Data Sent to Rare Domain
  • Anomalous Connection / Lots of New Connections
  • Unusual Activity / Unusual File Storage Data Transfer
  • Unusual Activity / Enhanced Unusual External Data Transfer [Enhanced Monitoring]
  • Anomalous Connection / Uncommon 1GiB Outbound
  • Unusual Activity / Unusual External Data to New Ips
  • Anomalous Connection / SMB Enumeration
  • Multiple Device Correlations / Behavioral Change Across Multiple Devices
  • Device / New or Uncommon WMI Activity
  • Unusual Activity / Unusual External Connections
  • Device / ICMP Address Scan
  • Anomalous Connection / Unusual Admin RDP Session
  • Compliance / SMB Version 1 Usage
  • Anomalous Connection / Unusual SMB Version 1
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Unusual Activity / Anomalous SMB Move and Write
  • Compromise / Ransomware / Suspicious SMB Activity [Enhanced Monitoring]
  • Anomalous Connection / Suspicious Read Write Ratio and Unusual SMB
  • Anomalous Connection / New or Uncommon Service Control
  • Device / New or Unusual Remote Command Execution
  • User / New Admin Credentials On Client
  • Device / New or Uncommon SMB Named Pipe
  • Device / Multiple Lateral Movement Model Breaches [Enhanced Monitoring]
  • Anomalous Connection / Suspicious Read Write Ratio
  • Device / SMA Lateral Movement
  • Anomalous File / Internal / Unusual Internal EXE File Transfer
  • Anomalous Server Activity / Unusual Unresponsive Server
  • Device / Internet Facing Device with High Priority Alert
  • Multiple Device Correlations / Spreading Unusual SMB Activity
  • Multiple Device Correlations / Multiple Devices Breaching the Same Model

Darktrace Autonomous Response alerts

  • Antigena / Network / Insider Threat / Antigena Network Scan Block
  • Antigena / Network / Insider Threat / Antigena Breaches Over Time Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly Block
  • Antigena / Network / Significant Anomaly / Antigena Breaches over Time Block
  • Antigena / Network / Insider Threat / Antigena Large Data Volume Outbound Block
  • Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Client Block
  • Antigena / Network / Insider Threat / Antigena SMB Enumeration Block
  • Antigena / Network / Significant Anomaly / Antigena Controlled and Model Breach
  • Antigena / Network / Insider Threat / Antigena Internal Anomalous File Activity
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network / External Threat / Antigena Ransomware Block
  • Antigena / Network / External Threat / SMB Ratio Antigena Block

MITRE ATT&CK techniques observed

Reconnaissance
T1595 — Active Scanning

Resource Development
T1608 — Stage Capabilities

Initial Access
T1190 — Exploit Public-Facing Application

Persistence
T1133 — External Remote Services

Defense Evasion
T1079 — Valid Accounts

Discovery
T1046 — Network Service Scanning
T1083 — File and Directory Discovery
T1018 — Remote System Discovery

Lateral Movement
T1210 — Exploitation of Remote Services
T1080 — Taint Shared Content
T1570 — Lateral Tool Transfer
T1021 — Remote Services

Command and Control
T1071 — Application Layer Protocol
T1095 — Non-Application Layer Protocol
T1571 — Non-Standard Port

Exfiltration
T1041 — Exfiltration over C2 Channel
T1567 — Exfiltration Over Web Service
T1029 — Scheduled Transfer


Impact
T1486 — Data Encrypted for Impact
T1489 — Service Stop
T1529 — System Shutdown/Reboot

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
Oakley Cox
Director of Product

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April 21, 2026

How a Compromised eScan Update Enabled Multi‑Stage Malware and Blockchain C2

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The rise of supply chain attacks

In recent years, the abuse of trusted software has become increasingly common, with supply chain compromises emerging as one of the fastest growing vectors for cyber intrusions. As highlighted in Darktrace’s Annual Threat Report 2026, attackers and state-actors continue to find significant value in gaining access to networks through compromised trusted links, third-party tools, or legitimate software. In January 2026, a supply chain compromise affecting MicroWorld Technologies’ eScan antivirus product was reported, with malicious updates distributed to customers through the legitimate update infrastructure. This, in turn, resulted in a multi‑stage loader malware being deployed on compromised devices [1][2].

An overview of eScan exploitation

According to eScan’s official threat advisory, unauthorized access to a regional update server resulted in an “incorrect file placed in the update distribution path” [3]. Customers associated with the affected update servers who downloaded the update during a two-hour window on January 20 were impacted, with affected Windows devices subsequently have experiencing various errors related to update functions and notifications [3].

While eScan did not specify which regional update servers were affected by the malicious update, all impacted Darktrace customer environments were located in the Europe, Middle East, and Africa (EMEA) region.

External research reported that a malicious 32-bit executable file , “Reload.exe”, was first installed on affected devices, which then dropped the 64-bit downloader, “CONSCTLX.exe”. This downloader establishes persistence by creating scheduled tasks such as “CorelDefrag”, which are responsible for executing PowerShell scripts. Subsequently, it evades detection by tampering with the Windows HOSTS file and eScan registry to prevent future remote updates intended for remediation. Additional payloads are then downloaded from its command-and-control (C2) server [1].

Darktrace’s coverage of eScan exploitation

Initial Access and Blockchain as multi-distributed C2 Infrastructure

On January 20, the same day as the aforementioned two‑hour exploit window, Darktrace observed multiple devices across affected networks downloading .dlz package files from eScan update servers, followed by connections to an anomalous endpoint, vhs.delrosal[.]net, which belongs to the attackers’ C2 infrastructure.

The endpoint contained a self‑signed SSL certificate with the string “O=Internet Widgits Pty Ltd, ST=SomeState, C=AU”, a default placeholder commonly used in SSL/TLS certificates for testing and development environments, as well as in malicious C2 infrastructure [4].

Utilizing a multi‑distributed C2 infrastructure, the attackers also leveraged domains linked with the Solana open‑source blockchain for C2 purposes, namely “.sol”. These domains were human‑readable names that act as aliases for cryptocurrency wallet addresses. As browsers do not natively resolve .sol domains, the Solana Naming System (formerly known as Bonfida, an independent contributor within the Solana ecosystem) provides a proxy service, through endpoints such as sol-domain[.]org, to enable browser access.

Darktrace observed devices connecting to blackice.sol-domain[.]org, indicating that attackers were likely using this proxy to reach a .sol domain for C2 activity. Given this behavior, it is likely that the attackers leveraged .sol domains as a dead drop resolver, a C2 technique in which threat actors host information on a public and legitimate service, such as a blockchain. Additional proxy resolver endpoints, such as sns-resolver.bonfida.workers[.]dev, were also observed.

Solana transactions are transparent, allowing all activity to be viewed publicly. When Darktrace analysts examined the transactions associated with blackice[.]sol, they observed that the earliest records dated November 7, 2025, which coincides with the creation date of the known C2 endpoint vhs[.]delrosal[.]net as shown in WHOIS Lookup information [4][5].

WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
Figure 1: WHOIS Look records of the C2 endpoint vhs[.]delrosal[.]net.
 Earliest observed transaction record for blackice[.]sol on public ledgers.
Figure 2: Earliest observed transaction record for blackice[.]sol on public ledgers.

Subsequent instructions found within the transactions contained strings such as “CNAME= vhs[.]delrosal[.]net”, indicating attempts to direct the device toward the malicious endpoint. A more recent transaction recorded on January 28 included strings such as “hxxps://96.9.125[.]243/i;code=302”, suggesting an effort to change C2 endpoints. Darktrace observed multiple alerts triggered for these endpoints across affected devices.

Similar blockchain‑related endpoints, such as “tumama.hns[.]to”, were also observed in C2 activities. The hns[.]to service allows web browsers to access websites registered on Handshake, a decentralized blockchain‑based framework designed to replace centralized authorities and domain registries for top‑level domains. This shift toward decentralized, blockchain‑based infrastructure likely reflects increased efforts by attackers to evade detection.

In outgoing connections to these malicious endpoints across affected networks, Darktrace / NETWORK recognized that the activity was 100% rare and anomalous for both the devices and the wider networks, likely indicative of malicious beaconing, regardless of the underlying trusted infrastructure. In addition to generating multiple model alerts to capture this malicious activity across affected networks, Darktrace’s Cyber AI Analyst was able to compile these separate events into broader incidents that summarized the entire attack chain, allowing customers’ security teams to investigate and remediate more efficiently. Moreover, in customer environments where Darktrace’s Autonomous Response capability was enabled, Darktrace took swift action to contain the attack by blocking beaconing connections to the malicious endpoints, even when those endpoints were associated with seemingly trustworthy services.

Conclusion

Attacks targeting trusted relationships continue to be a popular strategy among threat actors. Activities linked to trusted or widely deployed software are often unintentionally whitelisted by existing security solutions and gateways. Darktrace observed multiple devices becoming impacted within a very short period, likely because tools such as antivirus software are typically mass‑deployed across numerous endpoints. As a result, a single compromised delivery mechanism can greatly expand the attack surface.

Attackers are also becoming increasingly creative in developing resilient C2 infrastructure and exploiting legitimate services to evade detection. Defenders are therefore encouraged to closely monitor anomalous connections and file downloads. Darktrace’s ability to detect unusual activity amidst ever‑changing tactics and indicators of compromise (IoCs) helps organizations maintain a proactive and resilient defense posture against emerging threats.

Credit to Joanna Ng (Associate Principal Cybersecurity Analyst) and Min Kim (Associate Principal Cybersecurity Analyst) and Tara Gould (Malware Researcher Lead)

Edited by Ryan Traill (Content Manager)

Appendices

Darktrace Model Detections

  • Anomalous File::Zip or Gzip from Rare External Location
  • Anomalous Connection / Suspicious Self-Signed SSL
  • Anomalous Connection / Rare External SSL Self-Signed
  • Anomalous Connection / Suspicious Expired SSL
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device

List of Indicators of Compromise (IoCs)

  • vhs[.]delrosal[.]net – C2 server
  • tumama[.]hns[.]to – C2 server
  • blackice.sol-domain[.]org – C2 server
  • 96.9.125[.]243 – C2 Server

MITRE ATT&CK Mapping

  • T1071.001 - Command and Control: Web Protocols
  • T1588.001 - Resource Development
  • T1102.001 - Web Service: Dead Drop Resolver
  • T1195 – Supple Chain Compromise

References

[1] https://www.morphisec.com/blog/critical-escan-threat-bulletin/

[2] https://www.bleepingcomputer.com/news/security/escan-confirms-update-server-breached-to-push-malicious-update/

[3] hxxps://download1.mwti.net/documents/Advisory/eScan_Security_Advisory_2026[.]pdf

[4] https://www.virustotal.com/gui/domain/delrosal.net

[5] hxxps://explorer.solana[.]com/address/2wFAbYHNw4ewBHBJzmDgDhCXYoFjJnpbdmeWjZvevaVv

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About the author
Joanna Ng
Associate Principal Analyst

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April 17, 2026

Why Behavioral AI Is the Answer to Mythos

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How AI is breaking the patch-and-prevent security model

The business world was upended last week by the news that Anthropic has developed a powerful new AI model, Claude Mythos, which poses unprecedented risk because of its ability to expose flaws in IT systems.  

Whether it’s Mythos or OpenAI’s GPT-5.4-Cyber, which was just announced on Tuesday, supercharged AI models in the hands of hackers will allow them to carry out attacks at machine speed, much faster than most businesses can stop them.  

This news underscores a stark reality for all leaders: Patching holes alone is not a sufficient control against modern cyberattacks. You must assume that your software is already vulnerable right now. And while LLMs are very good at spotting vulnerabilities, they’re pretty bad at reliably patching them.

Project Glasswing members say it could take months or years for patches to be applied. While that work is done, enterprises must be protected against Zero-Day attacks, or security holes that are still undiscovered.  

Most cybersecurity strategies today are built like a daily multivitamin: broad, preventative, and designed to keep the system generally healthy over time. Patch regularly. Update software. Reduce known vulnerabilities. It’s necessary, disciplined, and foundational. But it’s also built for a world where the risks are well known and defined, cycles are predictable, and exposure unfolds at a manageable pace.

What happens when that model no longer holds?

The AI cyber advantage: Behavioral AI

The vulnerabilities exposed by AI systems like Mythos aren’t the well-understood risks your “multivitamin” was designed to address. They are transient, fast-emerging entry points that exist just long enough to be exploited.

In that environment, prevention alone isn’t enough. You don’t need more vitamins—you need a painkiller. The future of cybersecurity won’t be defined by how well you maintain baseline health. It will be defined by how quickly you respond when something breaks and every second counts.

That’s why behavioral AI gives businesses a durable cyber advantage. Rather than trying to figure out what the attacker looks like, it learns what “normal” looks like across the digital ecosystem of each individual business.  

That’s exactly how behavioral AI works. It understands the self, or what's normal for the organization, and then it can spot deviations in from normal that are actually early-stage attacks.

The Darktrace approach to cybersecurity

At Darktrace, we’ve been defending our 10,000 customers using behavioral AI cybersecurity developed in our AI Research Centre in Cambridge, U.K.

Darktrace was built on the understanding that attacks do not arrive neatly labeled, and that the most damaging threats often emerge before signatures, indicators, or public disclosures can catch up.  

Our AI algorithms learn in real time from your personalized business data to learn what’s normal for every person and every asset, and the flows of data within your organization. By continuously understanding “normal” across your entire digital ecosystem, Darktrace identifies and contains threats emerging from unknown vulnerabilities and compromised supply chain dependencies, autonomously curtailing attacks at machine speed.  

Security for novel threats

Darktrace is built for a world where AI is not just accelerating attacks, but fundamentally reshaping how they originate. What makes our AI so unique is that it's proven time and again to identify cyber threats before public vulnerability disclosures, such as critical Ivanti vulnerabilities in 2025 and SAP NetWeaver exploitations tied to nation-state threat actors.  

As AI reshapes how vulnerabilities are found and exploited, cybersecurity must be anchored in something more durable than a list of known flaws. It requires a real-time understanding of the business itself: what belongs, what does not, and what must be stopped immediately.

What leaders should do right now

The leadership priority must shift accordingly.

First, stop treating unknown vulnerabilities as an edge case. AI‑driven discovery makes them the norm. Security programs built primarily around known flaws, signatures, and threat intelligence will always lag behind an attacker that is operating in real time.

Second, insist on an understanding of what is actually normal across the business. When threats are novel, labels are useless. The earliest and most reliable signal of danger is abnormal behavior—systems, users, or data flows that suddenly depart from what is expected. If you cannot see that deviation as it happens, you are effectively blind during the most critical window.

Finally, assume that the next serious incident will occur before remediation guidance is available. Ask what happens in those first minutes and hours. The organizations that maintain resilience are not the ones waiting for disclosure cycles to catch up—they are the ones that can autonomously identify and contain emerging threats as they unfold.

This is the reality of cybersecurity in an AI‑shaped world. Patching and prevention remain important foundations, but the advantage now belongs to those who can respond instantly when the unpredictable occurs.

Behavioral AI is security designed not just for known threats, but for the ones that AI will discover next.

[related-resource]

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About the author
Ed Jennings
President and CEO
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