BUGSTER Used AI Tools to Plan and Conduct Cybercrime Against Indian Organizations

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Summary

Unit 42 traced BUGSTER’s AI-assisted operations against Indian organizations, including a confirmed university intrusion that exposed more than 5,200 records, plus credential attacks, Wi-Fi cracking, and VoIP fraud planning.

Key points

  • BUGSTER configured Hermes Agent with DeepSeek V4 and used Cursor IDE, with safety and permission controls disabled or bypassed.
  • AI-generated reconnaissance and scripts supported a brute-force campaign against an Indian university’s WordPress site; the tool identified one valid login.
  • The actor exfiltrated a MongoDB database from a second Indian public university, containing more than 5,200 student and faculty records with personal information.
  • The actor built AI-assisted VoIP fraud plans involving carrier access, traffic mixing, caller ID spoofing, and attempts to bypass STIR/SHAKEN; Unit 42 found no evidence of active call routing.
  • A Wi-Fi cracking pipeline captured authentication material near target networks, sent it over SSH to cloud GPU instances, and returned results through Discord webhooks.
  • Other activity included credential scanning, command-and-control payloads, and cryptocurrency-holder reconnaissance; Unit 42 found no follow-on activity from the latter.

Article Details

Attack Vectors
  • Enumerated university subdomains and WordPress REST API author data, then used a generated tool to brute-force logins with 117 usernames and 28 common passwords.
  • Exfiltrated a MongoDB database containing more than 5,200 student and faculty records from a second Indian public university.
  • Developed VoIP fraud plans involving caller ID spoofing, evasion of carrier compliance checks, and fraudulent call traffic; the source says the operation appeared to be in planning or early setup.
  • Captured WPA authentication material from nearby Wi-Fi networks and sent it through an SSH tunnel to cloud GPU instances for password cracking.
  • Used a Go-based toolkit to scrape webpages for exposed credentials, keys, and signed URLs.
  • Hosted a Python-based C2 listener supporting Windows reverse-shell connections, with payloads including a Base64-encoded PowerShell reverse shell delivered via VBScript.
Defensive Notes
  • The article identifies Advanced URL Filtering and Advanced IP Defense as protections for known malicious domains and URLs associated with this activity.
  • The article recommends Cortex XDR and XSIAM for malware prevention and behavioral analytics, and Cortex Agentic Endpoint Security for discovering and controlling AI artifacts and agent activity.
  • The article recommends Cortex Cloud and Idira identity and secrets-management products for cloud posture, access control, and protection of API keys and webhook tokens.

Indicators of compromise

TypeIndicatorContext
EMAILbugstergap@gmail[.]comEmail listed by the source as an attribution indicator for the actor operating under the handle BUGSTER.
IPV4104[.]238[.]38[.]202Listed by the source as a commercial proxy server associated with the actor's activity.
IPV4162[.]243[.]3[.]92Actor infrastructure hosting the Hermes Agent framework, a C2 listener, a Cursor IDE proxy, and supporting components.

MITRE ATT&CK

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