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March 17, 2026

When Reality Diverges from the Playbook: Darktrace Identifies Encryption in a World Leaks Ransomware Attack

World Leaks, a rebrand of Hunters International, are known for their extortion-only attack model, abandoning the tactic of file encryption. However, contrary to these claims, Darktrace detected a World Leaks compromise where a ransomware payload was deployed, and customer data was encrypted.
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
Tiana Kelly
Senior Cyber Analyst & Team Lead
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17
Mar 2026

As-a-Service Cybercrime Models

As-a-Service cybercrime models reduce the barrier to entry for cyber criminals as they no longer need expertise in every domain. Threat actors can increasingly outsource or supplement missing skills through the broader cybercrime-as-a-service ecosystem, and thus these models continue to grow in popularity within the cybercriminal underground. This has led to multiple templates in this sphere, such as Phishing-as-a-Service, Botnet-as-a-Service, DDoS-as-a-Service, and notably Ransomware-as-a-Service (RaaS) [1].

What is Extortion-as-a-Service?

Extortion-as-a-Service (EaaS) businesses function as a formalized way for cyber threat actors to offer extortion services to others for a fee or profit share and represents an evolution of extortion operations from the double-extortion ransomware model. Advancing from the RaaS model, extortion has become a distinct profit stream, separate from the encryption payload. This separation of functions, data theft, negotiation, and publicity, sets the stage for EaaS [1].

The EaaS model reflects a broader trend in cybercriminal activity, in which threat actors increasingly prioritize data theft and public exposure over traditional ransomware encryption. This shift reduces operational complexity while increasing pressure on victims through reputational damage. This approach has become increasingly popular among threat actors as, unlike encryption-based attacks, these operations are more difficult to detect and remediate [2]. It reflects a trend of ‘hack-and-leak’ operations that prioritize stealth, speed, and reputational damage over traditional encryption-based ransomware attacks [3].

World Leaks Overview

World Leaks emerged in early 2024 as a direct rebrand of the Hunters International ransomware group, which was notorious for encrypting victims’ data and demanding payment for decryption keys. In mid-2025, Hunters International shifted to an extortion-only model due to law enforcement scrutiny and reduced profitability, rebranding itself as World Leaks.

World Leaks functions as an affiliate-based EaaS operation which provides proprietary Storage Software exfiltration tooling to affiliates while maintaining a four-platform infrastructure consisting of a main data leak site hosted on the Dark Web where victim data is published, a victim negotiation portal with live chat, an affiliate management panel, and an insider journalist platform granting media outlets 24-hour advance access to stolen data before public release [4]. Since its emergence, World Leaks has published data stolen from dozens of organizations globally on its data leak site, serving both as a pressure tactic and a means for building reputation among cyber criminals.

World Leaks (known associations include Hive Ransomware, Secp0 Ransomware, and UNC6148) have been known to target the industrial (manufacturing) sector, along with healthcare organizations, technology firms and more generally, industries with valuable intellectual property [4]. Victims targeted have spanned multiple countries, with most located in the US, as well as Canada and several countries across Europe [5].

World Leaks’ Tactics, Techniques, and Procedures (TTPs) [3][4]

World Leaks’ typical attack pattern involves the exploitation of credentials with inadequate access controls, e.g. lacking multi-factor authentication (MFA), moving through reconnaissance, lateral movement and data exfiltration, notably without an encryption element.

Initial Access:

Initial access is typically gained through the exploitation of compromised virtual private network (VPN) credentials lacking MFA through valid accounts, as well as phishing campaigns. The targeting of internet-facing VPN infrastructure, RDP, and public-facing applications also represent common attack vectors in World Leaks incidents.

Lateral Movement:

SMB, RDP, and SSH are used for lateral movement via remote services. Notably, the group is also known to use PsExec and Rclone as part of their lateral movement activities.

Persistence:

Registry key modifications, scheduled tasks creation, account manipulation.

Exfiltration:

Data exfiltration is carried out through custom storage software tooling via TOR connections. Cloud storage services used for exfiltration particularly include MEGA. World Leaks also carry out direct data transfer through established command-and-control (C2) infrastructure.

Unlike Hunters International, which combined encryption with extortion, World Leaks claims to have abandoned the use of encryption. Some reports note that operations since January 2025 represent a pivot toward eliminating encryption entirely, instead relying on custom exfiltration tooling with SOCKSv5 proxy and TOR-based communications [4]. However, in early 2026, Darktrace detected an incident that directly contradicted this claim: World Leaks carried out an attack that involved both the exfiltration and encryption of customer data.

Darktrace’s Coverage of World Leaks Ransomware

Organizations today face a growing challenge: keeping pace with increasingly fast-moving threats. This incident highlights a common problem, when time-limited mitigations expire or human security teams cannot respond quickly enough, attackers are often able to regain the upper hand. A recent Darktrace detection of World Leaks ransomware provides a clear example of this challenge in practice.

In January 2026, Darktrace identified the presence of ransomware and data encryption linked to World Leaks within the network of an organization within the healthcare sector. Although Darktrace’s Autonomous Response capability was active in the customer’s environment and initially blocking suspicious connectivity, buying time for the customer to remediate, the attack continued once these mitigative actions expired. Darktrace continued to apply Autonomous Response actions as the attack progressed, working to inhibit the attackers at each stage of the intrusion.

Investigations carried out by Darktrace revealed that threat actors likely gained initial access via a Fortigate appliance in mid-October, indicating a three-month dwell time, before employing living-off-the-land (LOTL) techniques for lateral movement. C2 communications were established using Cloudflare Tunnel (formerly Argo Tunnel). As part of the Actions on Objectives attack phase, a significant volume of data was exfiltrated to the MEGA cloud storage platform, followed by the encryption of customer data.

Initial access/ Lateral movement

Darktrace analysts identified the likely patient-zero device within the network as a Fortigate appliance. In October 2025, this device was seen conducting brute-force activity using the compromised ‘administrator’ credential to gain a foothold deeper within the customer’s environment. Masquerading as a privileged user, the threat actor then went on to launch activity on remote devices via PsExec, a common administrative tool that allows users to execute processes on remote systems without manually installing client software, providing significant power to attackers when abused. Around the time, Darktrace detected an unknown device on the network attempting to authenticate via NTLM. As this device had not previously been seen on the network, it likely belonged to the attacker.

Reconnaissance

As part of the reconnaissance phase of the attack, port and network scanning was carried out in an attempt to identify open UDP and TCP ports within the network.

Lateral movement & C2

Around one month after entering the customer’s network, the World Leaks threat actors began tunnelling activity using Cloudflare Tunnel. Darktrace detected connections to several hostnames including: region2.v2.argotunnel[.]com; h2.cftunnel[.]com; region1.v2.argotunnel[.]com. This tunnelling activity continued until January of 2026, when encryption occurred. Cloudflare tunnels are known to be abused by attackers as they enable the use of temporary infrastructure to scale operations, allowing rapid deployment and teardown. Furthermore, leveraging of Cloudflare’s infrastructure to create these rate-limited tunnels (used to relay traffic from an attacker-controlled server to a local machine) makes such malicious activity harder to detect by both defenders and traditional security measures, particularly those that rely on static blocklists [6].

Further lateral movement was carried out using common remote management tools such as Windows Remote Management (WinRM) RDP, allowing the World Leaks threat actors to access local devices within the victim organization’s network.

As this attack progressed, Darktrace detected multiple files being written over SMB. These files included Windows\Temp\chromeremotedesktophost.msi, which was written from the patient-zero device to another internal device as part of lateral movement efforts. Following this transfer, and prior to subsequent data exfiltration activity, a network server was observed connecting to the hostname remotedesktop-pa[.]googleapis[.]com, an API endpoint required for Chrome Remote Desktop, indicating that Chrome RDP was used by the threat actor in this stage of the attack.

Other files written over SMB included the script programdata\syc\OpenSSHUtils.psm1 (which can be used legitimately to configure OpenSSH) and the executable programdata\syc\ssh‑sk‑helper.exe (a legitimate OpenSSH component used to support security keys). These files were written from the suspected patient‑zero device to an internal domain controller using the ‘administrator’ credential.

Thereafter, SSH connections to external IP address 51.15.109[.]222 were observed, providing another channel between the malicious actors and victim machines. Darktrace recognized that the use of SSH by the devices seen connecting to this IP address was highly anomalous, indicating that this suspicious activity formed part of the attack.

Writes of the script programdata\syc\OpenSSHUtils.psm1 were also observed into January, highlighting the continuation of the attack that had begun three months earlier.

On December 19 and 20, Darktrace detected a DNS server within the customer’s network making anomalous outgoing connections to an external IP address not previously seen in the environment: 193.161.193[.]99. This IP address has been reported by open-source-intelligence (OSINT) as being associated with C2 infrastructure, having been linked to several remote access trojans (RATs) and botnets in the past.

This activity a shift towards the infrastructure-as-a-service (IaaS) model, underscoring the growing trend around As-a-Service Cybercrime models and the increasing the industrialization of botnets. The presence of extensive digital botnets, often leased to other criminal organizations, means the group gaining initial access is not necessarily the same group conducting ransomware deployment or data theft; botnets now act as shared underlying infrastructure enabling multiple forms of cybercriminal activity [7].

Furthermore, connections to this IP address (193.161.193[.]99) were made over port 1194, which is associated with OpenVPN, suggesting that World Leaks may have leveraged it to obfuscate C2 communication with attacker-controlled infrastructure.

Darktrace’s detection of the IP address 193.161.193[.]99, noting that it was first seen within the customer’s network on December 19, 2025.
Figure 1: Darktrace’s detection of the IP address 193.161.193[.]99, noting that it was first seen within the customer’s network on December 19, 2025.

Data exfiltration

In November, Darktrace detected the threat actors carrying out one of their Attack on Objective tactics: data exfiltration. Multiple local devices within the compromised network began transferring data to Backblaze and MEGA domains, both of which provide cloud storage services; 80+GB of data was transferred to MEGA in late December 2025. Endpoints associated with this activity included: backblazeb2[.]com and gfs302n520[.]userstorage[.]mega[.]co[.]nz, as well as related user agents such as AS40401 BACKBLAZE) and MegaClient/10.3.0/64.

Notably, Darktrace researchers identified two known World Leaks TTPs in this attack: the use of MEGA, a known tool abused by the group, and Rclone, a command-line tool used to manage files on cloud storage, which was observed in the user agent of the MEGA data-transfer connections: rclone/v1.69.0 [4].

Cyber AI Analyst Incident highlighting data upload activity to backblaze[.]com endpoints.
Figure 2: Cyber AI Analyst Incident highlighting data upload activity to backblaze[.]com endpoints.\

Ransomware deployment & encryption

The encryption stage of this attack was confirmed by the presence of a ransom note found on the network in a file with a seemingly randomized nine-character string preceding README.txt, attributing the incident to World Leaks, along with an extension with the same nine characters appended to encrypted files. Darktrace also observed SMB writes of files named world.exe and task.bat, with the compromised ‘localadmin’ credential used during the SMB logins. It is likely that these files served as the vector for the ransomware payload.

 Packet Capture (PCAP) of the ransom note claiming that the attack was carried out by World Leaks.
Figure 3: Packet Capture (PCAP) of the ransom note claiming that the attack was carried out by World Leaks.

Conclusion

Though traditional ransomware relies on encryption, recent trends show that cyber threat actors no longer need to rely on noisy encryption tools and can eliminate much of the risk and technical complexity associated with encrypting systems. This is the model reportedly preferred by World Leaks after their rebrand from Hunters International.

In addition to reducing noise around these attacks, extortion‑only operations may be favored by threat actors over encryption‑focused ones for several reasons, including the fact that traditional security tools may struggle to detect data theft compared to encryption, that attackers leave less evidence behind when encryption is avoided, and that the long‑term impacts of stolen data on organizations can be greater than the loss of systems caused by encryption processes, which can be restored [8]. This is supported by analysis of data leak sites suggesting that almost 1,500 incidents in 2025 relied on data theft alone. Attackers can simply steal victim data and attempt to extort a ransom by threatening to publish it, without needing to deploy ransomware at all [9]. Furthermore, although World Leaks aims to function as an affiliate‑based EaaS operation, security teams should remain aware that their affiliates may have different criminal objectives.

Contrary to reports that World Leaks’ typical attack style has an extortion‑only objective, Darktrace detected an incident in which a World Leaks attack did end with the encryption of customer data. This highlights the need for adaptive defenses and reinforces the importance of network defenders staying proactive in the face of attacks, particularly as they may progress in ways that are unexpected compared to previous trends associated with a given threat actor.

Credit to Tiana Kelly (Senior Cyber Analyst and Analyst Manager) and Emily Megan Lim (Senior Cyber Analyst)

Edited by Ryan Traill (Content Manager)

Appendices

IoCs

  • world.exe – Executable File – Possible Ransomware Payload
  • task.bat – Script File – Possible Ransomware Payload
  • ‘^[A-Z][a-z]{3}[A-Z][a-z][A-Z]{3}[.]README[.]txt' – Ransom Note
  • [.]^[A-Z][a-z]{3}[A-Z][a-z][A-Z]{3} – Ransomware file extension

·       51.15.109[.]222 – IP Address - Possible C2 Infrastructure

·       193.161.193[.]99 – IP Address – Probable C2 Infrastructure

Darktrace Model Detections (Enhanced Monitoring models denoted with an asterisk)

·      Device / Attack and Recon Tools

·      Device / Suspicious SMB Scanning Activity

·      Device / Anomalous NTLM Brute Force

·      Compliance / Connection to Tunnelling Service

·      Device / Suspicious New User Agents

·      Device / New or Unusual Remote Command Execution

·      Compliance / SMB Drive Write

·      Anomalous Connection / Uncommon 1 GiB Outbound

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

·      Device / Multiple Lateral Movement Model Alerts*

·      Device / SMB Lateral Movement

·      Unusual Activity / Sustained Anomalous SMB Activity

·      Device / Large Number of Model Alerts

·      Compromise / Ransomware / SMB Reads then Writes with Additional Extensions

·      Compromise / Ransomware / Suspicious SMB Activity*

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

·      Unusual Activity / SMB Access Failures

·      Unusual Activity / Enhanced Unusual External Data Transfer*

·      Device / Suspicious File Writes to Multiple Hidden SMB Shares

·      Anomalous Server Activity / Rare External from Server

·      Unusual Activity / Unusual Mega Data Transfer*

·      Device / Possible SMB/NTLM Brute Force

·      Anomalous Connection / Unusual Admin RDP Session

·      Anomalous Connection / Active Remote Desktop Tunnel

·      Anomalous Connection / Data Sent to Rare Domain

·      Anomalous Connection / New or Uncommon Service Control

·      Anomalous Connection / New or Uncommon Service Enumeration

·      Anomalous Connection / Rare WinRM Outgoing

·      Anomalous Connection / SMB Enumeration

·      Anomalous Connection / Unusual Admin RDP Session

·      Anomalous Connection / Unusual Incoming Long Remote Desktop Session

·      Anomalous Connection / Upload via Remote Desktop

·      Anomalous File / Internal / Executable Uploaded to DC

·      Anomalous File / Internal / Unusual SMB Script Write

·      Compliance / SSH to Rare External Destination

·      Device / Anomalous Github Download

·      Device / Anonymous NTLM Logins

·      Device / Network Scan

·      Device / New or Uncommon WMI Activity

·      Device / New User Agent To Internal Server

·      Device / Possible Brute-Force Activity

·      Device / RDP Scan

·      Device / SMB Session Brute Force (Admin)

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

·      Device / Suspicious Network Scan Activity

·      Unusual Activity / Successful Admin Brute-Force Activity

·      Unusual Activity / Unusual External Data to New Endpoint

·      Unusual Activity / Unusual External Data Transfer

·      Unusual Activity / Unusual File Storage Data Transfer

·      User / New Admin Credentials on Server

Cyber AI Analyst Incidents

·      Scanning of Multiple Devices

·      Large Volume of SMB Login Failures to Multiple Devices

·      Suspicious Chain of Administrative Connections

·      SMB Write of Suspicious File

·      Suspicious DCE-RPC Activity

·      Unusual External Data Transfer

·      Unusual External Data Transfer to Multiple Related Endpoints

·      Unusual External Data Transfer to Endpoints

MITRE ATT&CK Mapping

·      Initial Access – T1190 – Exploit Public-Facing Application

·      Defense Evasion, Initial Access, Persistence, Privilege Escalation – T1078 – Valid Accounts

·      Resource Development – T1588.001 – Obtain Capabilities: Malware

·      Reconnaissance – T1590.005 – Gather Victim Network Information: IP Addresses

·      Reconnaissance – T1592.004 – Gather Victim Host Information: Client Configurations

·      Reconnaissance – T1595.001 – Active Scanning: Scanning IP Blocks

·      Reconnaissance – T1595.002 – Active Scanning: Vulnerability Scanning

·      Reconnaissance – T1595.003 – Active Scanning: Wordlist Scanning

·      Discovery – T1018 – Remote System Discovery

·      Discovery – T1046 – Network Service Discovery

·      Discovery – T1083 – File and Directory Discovery

·      Discovery – T1135 – Network Share Discovery

·      Command and Control – T1219 – Remote Access Tools

·      Command and Control – T1219.002 – Remote Access Tools: Remote Desktop Software

·      Command and Control – T1571 – Non-Standard Port

·      Command and Control – T1572 – Protocol Tunneling

·      Command and Control – T1573.001 – Encrypted Channel: Symmetric Cryptography

·      Credential Access – T1110 – Brute Force

·      Credential Access – T1110.001 – Brute Force: Password Guessing

·      Defense Evasion – T1006 – Direct Volume Access

·      Defense Evasion – T1564.005 – Hide Artifacts: Hidden File System

·      Defense Evasion – T1564.012 – Hide Artifacts: File/Path Exclusions

·      Execution – T1047 – Windows Management Instrumentation

·      Execution – T1569.002 – System Services: Service Execution

·      Lateral Movement – T1021 – Remote Services

·      Lateral Movement – T1021.001 – Remote Services: Remote Desktop Protocol

·      Lateral Movement – T1021.002 – Remote Services: SMB/Windows Admin Shares

·      Lateral Movement – T1021.006 – Remote Services: Windows Remote Management

·      Lateral Movement – T1080 – Taint Shared Content

·      Lateral Movement – T1210 – Exploitation of Remote Services

·      Lateral Movement – T1570 – Lateral Tool Transfer

·      Collection – T1039 – Data from Network Shared Drive

·      Collection – T1074 – Data Staged

·      Exfiltration – T1041 – Exfiltration Over C2 Channel

·      Exfiltration – T1048 – Exfiltration Over Alternative Protocol

·      Exfiltration – T1567.002 – Exfiltration Over Web Service: Exfiltration to Cloud Storage

References

[1] https://www.levelblue.com/blogs/levelblue-blog/extortion-as-a-service-the-latest-threat-actor-criminal-ecosystem/

[2] https://blackpointcyber.com/wp-content/uploads/2025/12/World-Leaks.pdf

[3] https://blackpointcyber.com/threat-profile/world-leaks-ransomware/

[4] https://www.halcyon.ai/threat-group/worldleaks

[5] https://www.moxfive.com/resources/moxfive-threat-actor-spotlight-world-leaks

[6] https://thehackernews.com/2024/08/cybercriminals-abusing-cloudflare.html

[7] https://www.trendmicro.com/vinfo/tw/security/news/threat-landscape/the-industrialization-of-botnets-automation-and-scale-as-a-new-threat-infrastructure

[8] https://www.morphisec.com/blog/ransomware-without-encryption-why-pure-exfiltration-attacks-are-surging-and-why-theyre-so-hard-to-catch/

[9] https://sed-cms.broadcom.com/sites/default/files/2026-01/RWN-2026-WP100_1.pdf

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
Tiana Kelly
Senior Cyber Analyst & Team Lead

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July 15, 2026

Security After Signatures: Operating in a World of Pre‑CVE Disclosure Exploitation, Collapsed Trust Boundaries, and Autonomous Systems

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Three shifts have reshaped what it means to defend an enterprise securely.  

First, exploitation often begins before defenders have a Common Vulnerabilities and Exposures (CVE) identifier, a security advisory, or an entry in the Cybersecurity and Infrastructure Security Agency's (CISA) Known Exploited Vulnerabilities (KEV) catalog.

Secondly, the trust boundary has moved beyond the network edge into identities, tokens, APIs, and Software-as-a-Service (SaaS) workflows.  

Third, an increasing share of business activity is executed through automation, integrations, and AI agent-like systems that can act faster than teams can verify intent.  

If your security model still relies on detecting known bad artefacts, triaging isolated alerts, and waiting for confirmation before acting, you are already behind the threat.  

This is not a failure of security teams; it’s a failure of the operating model to keep pace with how the environment has changed.

A SOC built around alerts and signatures assumes that malicious activity will eventually surface as an event. In real incidents, however, the decisive evidence is rarely a single event. Instead, it is a chain of individually explainable actions that only appears malicious once you connect the dots across identity, non-human identity, cloud, email, SaaS, operational technology (OT), and network telemetry.

The defenders succeeding today observe behaviors, link them into sequences, understand what those sequences mean, and contain impact before the full story unfolds. That is the operating model the current threat environment demands.  

Exploitation before disclosure

The first shift is the straightforward: the time to exploit has dropped to nearly zero.  

In one example, Darktrace observed a sequence of subtle but strategically significant anomalies within a customer environment that later aligned with exploitation of CVE‑2025‑0994 in Trimble Cityworks by likely Chinese-nexus threat actors. Behavioral indicators were visible at least 18 days before public disclosure, with related anomalies emerging 40 to 50 days earlier during the intrusion window.  

This case illustrates a familiar pattern: clusters of weak‑signal anomalies combing to form an actionable picture of intrusion long before a CVE is published. Such activity reflects long‑horizon, option‑preserving operator models often associated with mature state‑linked activity.  

Figure 1: Darktrace’s detection of malicious exploitation of CVE 2025-0994, later tied to Chinese-nexus threat actors targeting critical national infrastructure (CNI) in the US, weeks before public disclosure.

Throughout 2025 and 2026, Darktrace has continued to observe the value of anomaly-based detections across a range of incidents.

CVE CVE Public Disclosure Date Darktrace Detection Date Days Between Detection of Exploitation and CVE Public Disclosure
CVE 2025 0994
(Trimble City Works)
2025-02-06 2025-01-19 18 Days
CVE 2025-24183
(Apache)
2025-03-10 2025-02-18 20 days
CVE 2025-10035
(Fortra GoAnywhere)
2025-09-18 2025-09-11 7 days

Identity is the real control plane

The second shift is that identity has replaced perimeter as the primary control plane. As Darktrace’s Annual Threat Report 2026 illustrated, identity remains the main challenge in defending against modern intrusions. A clear example is the Adversary-in-the-Middle (AiTM) case published by Darktrace in December 2025. A phishing email led to the compromise of an Office 365 account. Session hijacking bypassed multi-factor authentication (MFA), and the compromised account was used for follow-on phishing and persistence activities including the creation of malicious email rules.  

Every step in that sequence mattered. A successful login alone does not prove legitimacy. An inbox rule, on its own, may not appear catastrophic. Mail activity, viewed in isolation, may seem operationally normal. But the behavioral chain tells a different story: credential theft, token abuse, persistence, and onward compromise through a trusted identity.  

This is why the question is no longer “Did the user authenticate successfully”. The more important question is, “Does this identity action make sense right now, in this context, given what came before it?” The AiTM case shows how identity can be compromised. In practice, however, attacks rarely remained confined to identity alone.  

In another Darktrace case, a compromised SaaS account triggered activity across the email, SaaS, and network layers, including inbox rule changes, phishing propagation, and connections to suspicious infrastructure. Viewed in isolation, none of these events were decisive. Together, however,  they formed a behavioral sequence that revealed the intrusion, with the full attack story automatically correlated and surfaced to defenders by Darktrace’s Cyber AI Analyst.  

Figure 2: Cyber AI Analyst correlated and appended additional events to the incident, including other users who connected to the suspicious redirect link after outbound phishing emails were sent.

AI accelerates the threat  

The third shift is the one many teams still underestimate: trusted tooling, integrations, and AI agent-like systems can create actions that appear legitimate but are strategically dangerous.  

The shift becomes clearer when examining how governments are now framing AI risk. In 2026, guidance published by CISA, UK’s National Cyber Security Centre (NCSC) and Five Eyes partners warned that agentic systems expand attack surfaces, accumulate privilege, and can behave in ways that are difficult to predict or explain [1]. The advice is simple: assume unexpected behavior and design controls around it.  

The real risk is not AI usage. It is unknown autonomy: systems with credentials, data access, and action paths that can execute workflow steps without sufficient behavioral validation, traceability, or human oversight. Darktrace’s Model Context Protocol (MCP) risk analysis provides a useful framework for understanding this challenge. Over-privileged agents, content injection, and tool abuse become high-consequence risks when connected systems can dynamically retrieve data, execute actions, and communicate externally.  

Whether security teams like it or not, AI is already in the enterprise. It will help drive innovation, but it will also be abused, whether accidentally or maliciously. In each of the cases below, AI either scaled the attacker, built the tooling, or existed within the environment as something to exploit or misuse.

1. AI as an Attack Multiplier

In one campaign targeting Mexican government entities, a single operator used commercial AI platforms to generate exploits, automate reconnaissance, and process large volumes of data, compressing work that would traditionally have required an entire team into a single workflow [2].  

Darktrace is also observing this trend further down the stack. In one case, Darktrace identified AI-generated malware exploiting React2Shell, where an attacker used a Large Language Model (LLM) to produce working exploit code and deploy it at scale.  

[darktrace.com], [darktrace.com]

2. AI as an Attack Surface

Attempted AI exploitation is now appearing within customer environments. In one case involving an automation technology manufacturer, a compromised LLM proxy was seemingly used as a stepping stone to access additional AI services. When that attempt failed, the attacker pivoted to cryptomining.

What is clear is that the AI layer has already become an asset worth probing, exploiting, and pivoting through. It is also clear that defenders benefit from rapidly understanding how these activities connect. In this case, Cyber AI Analyst automatically pieced together the intrusion, while Darktrace’s Managed Threat Detection service alerted to the customer, enabling the activity to be contained before it could progress further.

Figure 3: Cyber AI Analyst's investigation into a compromised LLM proxy that was abused for cryptomining activity.

AI as a trusted but dangerous actor

This does not require a cinematic vision of “rogue AI.” The Salesloft incident provides a more grounded example, where AI and automation operate with legitimate access but served malicious intent. In that case, attackers abused compromised OAuth tokens associated with the Drift AI chat agent to export significant volumes of data from Salesforce environments.  

The activity resembled legitimate API usage and relied on trusted SaaS integrations rather than malware or other obvious signs of intrusion. That is precisely the challenge. Traditional security controls are good at detecting forced entry, but far less effective when a trusted application integration behaves in a way that is technically permitted yet operationally harmful.  

In these scenarios, the security challenge shifts from validating access to validating behavior.

This is what that looks like in practice: AI-linked identities executing legitimate actions that require behavioral validation rather than access validation.

Figure 4: Darktrace / SECURE AI highlights anomalous activity across AI identities, surfacing critical behavior that requires validation and containment.

Early observations from Darktrace / SECURE AI deployments reinforce this reality. Across Darktrace's observed fleet, AI service connections per deployment increased 13% during the first half of 2026, reaching over 16 million connections overall. The typical organisation now interacts with seven different AI providers, evidence that AI is no longer operating at the edges of the enterprise. It is increasingly woven into day-to-day business activity.

The most common risks are not compromised models or advanced AI attacks. Instead, they stem from employees and business functions exposing sensitive information through entirely legitimate-looking interactions. Darktrace has observed repeated submission of personally identifiable information (PII), tax information, identification documents, and medical data into LLM prompts, alongside widespread use of unsanctioned (shadow) AI services and growing AI activity from mobile devices.  

For defenders, the challenge is increasingly one of context: understanding when legitimate business use crosses into material risk, while preserving privacy and user trust.

Conclusion

Across all three shifts, the pattern is the same: behavior precedes understanding. Security teams are not losing because adversaries have become invisible. An increasingly outdated security model assumes that malicious activity will reveal itself cleanly and early. It no longer does.  

In 2026 and beyond, defenders win by understanding behavioral sequences, continuously validating trust, and acting before certainty becomes hindsight. That is security after signatures. That is security in the AI era.

Credit to: Daniel Levy, Threat Hunting Data Scientist

Edited by: Ryan Traill, Content Manager

References

[1] https://www.cyber.gov.au/business-government/secure-design/artificial-intelligence/careful-adoption-of-agentic-ai-services  

[2]https://www.latimes.com/business/story/2026-02-26/hacker-used-anthropics-claude-ai-to-steal-mexican-government-data

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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July 10, 2026

AIインフラがアタックサーフェスの一部に

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AIインフラとアタックサーフェスの進化

多くの組織が生成AIを実運用環境に導入するなかで、企業のクラウド環境内に新たなインフラのレイヤーが出現しています。それはAIゲートウェイです。AIゲートウェイはユーザー、アプリケーション、基盤モデルの間に位置し、多くの場合クラウドの特権アクセスを保持し、さまざまなAIサービスへのアクセスを大規模に管理しています。

AIゲートウェイとは?

AIゲートウェイはユーザー、アプリケーション、基盤モデルの間に位置し、多くの場合クラウドの特権アクセスを保持し、さまざまなAIサービスへのアクセスを大規模に管理しています。

こうした役割から、AIゲートウェイは企業のアタックサーフェスのますます重要な一部になりつつあります。AIゲートウェイが侵害されれば、攻撃者に対して計算リソースへのアクセスだけでなく、クラウドアイデンティティ、モデルサービス、機密性の高いプロンプト、そして他の接続されたシステムへのアクセスも提供してしまいます。

このブログでは、Amazon Bedrock サービスに接続されたAIゲートウェイが侵害され、その後暗号通貨マイニングインフラとの通信が観測された事例をダークトレースがどのように調査したかを解説します。問題のインスタンスは、その構成、ならびに関連するIAM(Identity and Access Management)ロールから、Amazon BedrockでホスティングされるAIサービスへのゲートウェイとして機能していることがわかりました。疑わしい侵害アクティビティが発生した後、このホストは既知の暗号通貨マイニングインフラに繰り返し通信を行い、その後シャットダウンされた様子が観測されました。Darktrace はこのアクティビティを検知し、Enhanced MonitoringおよびManaged Threat Detectionサービスを通じてエスカレーションを行いました。

この事例では最終的影響は不正な暗号通貨マイニングでしたが、このインシデントが注目に値するのはその発生場所です。侵害されたアセットは、クラウドインフラ、アイデンティティ、各種AIサービスの交差する場所に位置していました。最近の調査では、LiteLLM等のAIゲートウェイが、認証情報、モデルへのアクセス、クラウド権限を中央管理するその能力から、攻撃者にとって魅力的な標的となる可能性が明らかになっています。このアクティビティと公開されているLiteLLM脆弱性を直接結びつける証拠は見つかっていませんが、このインシデントは、AIインフラを個別のアプリケーション層として見るのではなく、重要なアタックサーフェスの一部として扱う必要性があることを表しています[1]。

暗号通貨マイニングがクラウド侵害後のアクティビティとしてよく見られる背景

暗号通貨マイニングはクラウド環境において、侵害後のアクティビティとして収益性の高いものとなり得ます。クラウド資産にアクセスできるようになった後、攻撃者はマイニングソフトウェアを展開して被害者の計算リソースを悪用し金銭的利益を得ることができます。この種のアクティビティは多くの場合機会主義的なものであり、露出したサービス、弱い認証情報、漏洩したアクセスキー、脆弱なアプリケーション、あるいはクラウドワークロードの設定ミスなどを標的として実行されます。

典型的なクラウド上での暗号通貨マイニング侵入には次のようなアクティビティが含まれます:

  • 露出したあるいは脆弱なクラウドインフラの特定
  • 露出したサービス、認証情報、またはアプリケーションの脆弱性を通じたアクセスの獲得
  • マイニングソフトウェアのダウンロードおよび実行
  • マイニングプールインフラへのアウトバウンド接続を繰り返し確立
  • アクティビティが検知され停止されるまで継続して計算リソースを消費

この事例において注目すべき要素は暗号通貨マイニングだけではありません。それが発生した場所が、AI関連アクティビティをサポートするクラウドインフラ上だったことです。この事例は、AIサービスを実現するためのアセットも、よくあるクラウド侵害リスクにさらされる可能性があることを示しています。

Amazon Bedrockに接続されたAIゲートウェイの侵害を調査

2026年6月12日、DarktraceはLiteLLM-Proxyという名前のAmazon Web Service (AWS) EC2インスタンスから暗号通貨マイニング発生中とみられるアクティビティを観測しました。このインスタンスはLiteLLMアクティビティをサポートしており、Amazon Bedrockリソースへのアクセス権を有するインスタンスプロファイルと関連付けられていました。  

AIゲートウェイは大規模言語モデルへのアクセスを中央管理するよう設計されており、多くの場合AIアプリケーションに対する認証、ルーティング、ログ、ポリシー適用を扱っています。セキュリティの視点から見ると、クラウド権限、モデルアクセス、アプリケーションワークフローを単一の制御ポイントに集約する役割も果たしています。その結果、AIゲートウェイの侵害は、侵害されたホストだけにとどまらない影響を及ぼす可能性があります。

確定的な初期アクセスベクトルは確認できませんでしたが、このアクティビティはインターネットに接続されているシステムの侵害でよく見られる次のような順序に従っていました。ブルートフォースアクセス、ペイロードの投下、そしてマイニングプールインフラに対する繰り返しのアウトバウンド接続です。

ステージ1: インターネットに露出したSSHからの初期アクセス

暗号通貨マイニングアクティビティが観測される前、LiteLLM-Proxy EC2インスタンスはSSH(ポート22)が0.0.0.0/0に対して開かれ、外部に公開されていました。

図1:EC2インスタンスがSSHポート22に対してすべてのインバウンドトラフィックを許可している設定ミスをDarktraceが警告

暗号通貨マイニングアクティビティに先立って、Darktraceはこのインスタンスに対する大量のインバウンド接続の試みが外部IPアドレス(主に145.241.123[.]102)からポート22に対して行われていることを観測しました。これはブルートフォースアクティビティを示唆するものです [2]。これらの接続の多くは短命であり、数秒しか続いておらず、スキャニングまたはログインの失敗を示していました。

図2:Darktraceがデバイスのポート22に対する不審なインバウンド接続試行を検知

入手できたテレメトリーではこれらのインバウンドSSH接続のいずれかが認証の成功につながったかどうかの確認に至らず、このアクティビティが初期アクセスベクトルであると断定することはできませんでした。しかしながら、SSHの露出、外部IPアドレスからのインバウンド接続、それに続くマイニングアクティビティは、SSHがアクセス経路の可能性が高いことを示唆しています。

ステージ2: AIゲートウェイへのXMRigマルウェアのダウンロード

最初に観測されたマイニングプールへの接続の後、このEC2インスタンスは3.42 MBのデータをポート80上のHTTP接続を介して外部エンドポイント185.62.1[.]8にダウンロードしました。このエンドポイントは暗号通貨マイニングマルウェアXMRigを含むZIPファイルをホスティングしていました[3][4]。ホストレベルのログは入手できなかったため、ダークトレースはマイニングツールがどのように実行されたか、あるいは前のSSHアクティビティがペイロード投下を直接的に可能にしたかどうかを確認できませんでした。しかしながら、ダウンロードのタイミングとその後ほどなくマイニングプールへの接続が繰り返されたことは、このインスタンスが侵害されて不正な計算アクティビティに使われたという評価を裏付けています。

ステージ3 – 侵害されたAIゲートウェイが暗号通貨マイニングインフラと通信

わずか数分後、DarktraceはLiteLLM-ProxyEC2インスタンスがHTTPs(ポート443)でホスト名pool.hasvault[.]proに対して接続していることを確認しました。最初の接続の後、同じホスト名に対して繰り返しアウトバウンド接続が観測されました。これは、侵害されたホストがマイニングインフラと通信しワークを受け取り、結果を送信するという、暗号通貨マイニングプールとの通信のパターンと一致しています。

このアクティビティがDarktraceのEnhanced Monitoringモデル“Compromise / HighPriority Crypto Currency Mining”をトリガーし、ダークトレースのSOCにより顧客に対してエスカレーションされました。また、このアクティビティはCyber AI Analystによって分析され、関連するイベントが1つの調査ナラティブにまとめられました。これにより、影響を受けたクラウドアセットからマニングプールへの繰り返しの接続を特定することができました。

図3:CyberAI Analystによる暗号通貨マイニングアクティビティの調査  

ポート443上のHTTPSの使用にも注目すべきです。なぜならば、単独で見れば、このトラフィックそのものは疑わしく見えないかもしれないからです。しかしこのケースでは、接続先、接続の量、そして類似のアクティビティが他にないことなどが、この通信を疑わしいものとして特定するのに必要な、動作のコンテキストを提供することになりました。

ステージ4: Managed Threat Detectionサービスによるリソース乱用の特定

暗号通貨マイニングアクティビティがダークトレースのManaged Threat Detectionサービスにより検知され、ダークトレースのSOCによりレビューされました。レビューの結果、このアクティビティは顧客向けにエスカレーションされました。このエスカレーションにより、顧客はAWS環境で現在発生中のリソースの乱用について、タイムリーな通知を受けることができました。

ステージ5: クラウド認証情報の不正使用とみられる疑わしいIAMアクティビティ

これとは別に、6月13日、Darktraceは別のIAMユーザーから発生した疑わしいアクティビティを検知しました。

図4: DarktraceのAdvanced Search機能が別のIAMユーザーが実行した疑わしいアクティビティをハイライト

まず、このユーザーは “GetSendQuota”イベントを試行している様子が見られました。このアクションは少なくとも過去3か月間にこのアカウントによって実行されたことのないアクションです。また、このコマンドのソースIPアドレスは14.176.1[.]47でした。地理位置情報はベトナムであり、このユーザーのアクティビティがAmazon IPアドレスから最も多く見られた場所です。さらに、このアクティビティに対してAWS CLIが使用されており、これもこのユーザーにとって通常とは異なる振る舞いでした。このことは、Darktraceの“IaaS / Unusual Activity / UnusualAWS CLI Activity”モデルによって検知されました。

図5: Darktraceによる “GetSendQuota” イベントの検知

このIAMユーザーからは、長期アクセスキーを使った疑わしいアクティビティがさらに観測されました。中でも、“InvokeModel” および “ListFoundationModels”コマンドの失敗が検知されており、モデル列挙や起動などAmazon Bedrockサービスとのやり取りを試行したことがわかります。これは前日観測されたLiteLLM侵害への関連を思わせますが、2つのイベントを確定的に結びつける証拠は不十分でした。

“CreateUser”コマンドの試行も注目に値します。なぜなら要求されたユーザー名は意味が薄いものであり、新しいアカウントを作成することにより永続性を確立する試みと見られるからです。このアクティビティはDarktraceのモデル“IaaS / Admin / New AWS UserAccount Creation”をトリガーしました。

図6:Darktraceによる“CreateUser” イベントの検知

2つのインシデント間に結びつきは確認できなかったものの、このIAMアクティビティには重要な意味があります。これは、クラウド侵害の調査においてワークロードのテレメトリーとコントロールプレーンのテレメトリーの両方を取り入れることの重要性を表しています。EC2暗号通貨マイニングアクティビティが計算リソースの乱用を示す一方、IAMアクティビティは認証情報の侵害や長期アクセスキーの不正使用、そしてクラウトサービスの不正使用の可能性を示唆しているからです。

AIインフラ保護のための重要な教訓

このインシデントの重大性は暗号通貨マイニングアクティビティそのものではなく、それが発生した場所にあります。侵害されたシステムはAmazon Bedrockサービスへのアクセス権を持つAIゲートウェイとして機能し、クラウドインフラ、アイデンティティ、そしてさまざまなAIオペレーションの交差する場所に位置していました。組織がAI機能を実運用環境に導入していくなかで、これらのプラットフォームは、露出したサービス、認証情報窃取、クラウドの設定ミスなどを通じて攻撃者がすでに狙っているアタックサーフェスの一部となりつつあるのです。

このケースでは詳細な侵入経路は特定されておらず、ワークロードの侵害と調査中に検知された疑わしいIAMアクティビティの間に決定的なつながりは確認されませんでしたが、これらのイベントは全体的な現状を裏付けています。つまり、AIインフラは個別のテクノロジースタックとして扱うのではなく、クラウド環境全体の一部として保護しなければならないとうことです。

このケースでは、最も目立った侵害の兆候は暗号通貨マイニングインフラとの通信でした。しかしここで得られたより重要な教訓は、このインシデントの全貌が理解される前にDarktraceのビヘイビア分析により明らかになった、高い権限を持つAI関連アセットを取り巻くリスクです。AIゲートウェイによりクラウド権限、モデルアクセス、アプリケーションワークフローがますます集約されるなかで、防御者は個別のアラートに集中するよりも、ワークロード、アイデンティティ、サービスの間でどのように動作がつながっているかを理解することに重点を置く必要があるでしょう。

協力:Angel Arribas Lopez (Associate Principal Cyber Analyst)、Nathaniel Jones (Field CISO/VP Threat Research)、Emma Foulger (Global Threat Ops)、Mark Turner(Security Researcher)

編集:Ryan Traill (Content Manager)

付録

Darktraceによるモデル検知結果

·       Compromise / High Priority Crypto Currency Mining

·       Compromise / Monero Mining

·       Device / Internet Facing Device with High Priority Alert

·       IaaS / Unusual Activity / Unusual AWS CLI Activity

·       IaaS / Admin / New AWS User Account Creation

MITRE ATT&CK マッピング

初期アクセス – 外部リモートサービス – T1133

初期アクセス – 有効なアカウント – T1078

実行 – コマンドおよびスクリプトインタプリタ – T1059

永続化 – アカウント作成 – T1136

探索 – クラウドサービス探索 – T1526

影響 – リソースハイジャッキング– T1496

参考資料

[1] https://docs.litellm.ai/blog/security-update-march-2026

[2] https://www.abuseipdb.com/check/145.241.123.102

[3] https://urlscan.io/search/#185.62.1.8

[4] https://www.virustotal.com/gui/file/85de36ff66fae9f4b059cbedf6d36e017ebc26c828f99f911a96e78636f21200/community

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About the author
Angel Arribas Lopez
Associate Principal Cyber Analyst
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