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A ransomware affiliate known as 3AM compromised a UK school network using a mix of traditional intrusion techniques and patterns suggesting the involvement of artificial intelligence.

According to Bitdefender’s investigation on November 3, this operation appears to follow a suspected hybrid workflow: a human operator selects the targets while a language model may handle repetitive tasks and troubleshooting. However, researchers emphasize that fully automated operations have not yet been proven.

The compromised environment included 47 systems, comprising approximately 21 servers and eight domain controllers. Initially, these Active Directory domains were separate, but the attacker established two-way trusts, allowing access across the entire network. The initial access method remains unknown.

The affiliate relied primarily on PowerShell, Windows Management Instrumentation, registry utilities, scheduled tasks, and other legitimate Windows components. Public tools included Mimikatz, Impacket-style remote execution utilities, and a modified Veeam credential-recovery script.

This approach follows the established 3AM ransomware playbook, rather than introducing a fundamentally new malware platform. The distinctive evidence appeared in command construction, repeated mistakes, and the timing of revisions.

On September 13, one PowerShell command was repeated unchanged after 41 seconds. Another revision followed 49 seconds later, changing only its output method. After another 47 seconds, the attacker replaced PowerShell with WMIC.

Across nine retries, intervals ranged from 40 to 101 seconds regardless of revision complexity. Longer gaps separated different tasks. Researchers interpreted this rhythm as consistent with human-directed work supported by an agentic loop, although manual copying between a chatbot and shell could produce similar behavior.

How Impacket’s wmiexec runs a command on a target machine (Source: BitDefender)

Recorded September activity began with credential theft from three backup servers. A modified script queried Veeam databases and decrypted stored secrets using Windows Data Protection API functionality.

The attacker subsequently copied Chrome’s credential database, exported sensitive registry hives, and deployed Mimikatz under misleading filenames, including sysmon64.exe. Two rogue domain-administrator accounts, library and svc_bkpmon, provided redundant persistence.

These actions illustrate why backup infrastructure security matters beyond recovery: stored credentials can support broader compromise. However, investigators did not identify a Veeam vulnerability as the entry point.

On September 15, the attacker staged finance documents as Base64-encoded registry values, copied files into additional locations, and uploaded an archive through HTTP POST to an unmanaged internal host.

That machine also acted as a command-and-control endpoint. Because investigators could not examine it, they could not identify a model, hosting arrangement, or automation framework.

On September 18, the affiliate established two-way trusts connecting three domains, then performed diagnostic checks and restarted the service, maintaining interdomain secure channels.

On September 19, successive scripts attempted to remove endpoint protection, but anti-tampering controls blocked removal. A loader was deployed to approximately 40 machines before the Rust-based ThreeAM encryptor executed between 05:07 and 05:33 UTC, deleting system-state backups during deployment.

The suspected AI indicators included incorrect Veeam API assumptions, Unix-style syntax inside Windows commands, numbered script revisions, and confirmation files. Individually, these artifacts do not prove model involvement.

The case complements reporting on agent-assisted ransomware operations, but remains one investigation, not evidence of a wider autonomous-ransomware trend.

Defenders should prioritize unexpected domain trusts, privileged account creation, backup credential access, registry-hive exports, and unusual registry-based file staging.

Bitdefender’s research coverage underscores the central distinction: familiar attack techniques remain detectable even when execution may involve AI. Reliable identity, endpoint, and network telemetry remains essential for reconstructing activity and testing automation claims during investigations.

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