Reported by 2 outlets
AI-Autonomous Campaign Compromises 85 Government Accounts, Exfiltrates 2,500+ Records
Why this score
- Breadth
- 1.00 / 2.0 · 2 sources
- Authority
- 1.20 / 2.0 · best outlet weight
- Severity
- 0.70 / 5.0 · CVSS + content signals
- Velocity
- 0.00 / 2.0 · updates in 48h
- Pickup speed
- 0.55 / 0.6 · time to second source
- Recency
- × 0.00 temporal multiplier
- Community
- + 0.00 / 1.5 · reddit signal
- Score
- 0.0 / 10 = base × recency + community
Timeline
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original reporting
AI Agents Crack 85 Government Accounts and Steal 2,500+ Personnel Records
cyberpress.org · 49d ago · August 25th, 2026
A suspected near-autonomous intrusion campaign that compromised government entities in Asia, cracking 85 employee accounts and extracting at least 2,564 personnel records over roughly four days in July 2026. The Dream Research Labs said the campaign archive contained 1,395 files and showed an AI-operated framework performing reconnaissance, credential attacks, lateral movement, data collection, and persistence attempts at a scale normally associated with coordinated human teams. According to the report, the operation used Hermes and OpenClaw agent frameworks, deploying as many as eight letter-designated sub-agents concurrently across 12 attack waves. AI Agents Crack Government Accounts The agents reportedly decompiled Angular JavaScript bundles, enumerated 21 connected systems, mapped OIDC and Keycloak configurations , and identified more than 36 API endpoints on one target. Several APIs allegedly exposed user information without authentication, including names, departments, and SSO identifiers, which were used to support subsequent password spraying. Full Attack Chain (Source: Dream) The framework paired harvested usernames with predictable password patterns and Tesseract OCR to defeat small CAPTCHA challenges, researchers said. It initially cracked 12 accounts, then 73 more after expanding its pattern set. The report also describes three exposed debug-style authentication endpoints that issued valid sessions, as well as a JWT validation weakness in which tokens using the no
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update from gbhackers.com
Multi-Agent AI Framework Compromises Government Systems and Steals Thousands of Records
gbhackers.com · 49d ago · August 25th, 2026
A multi-agent AI framework, utilizing Hermes and OpenClaw agents, was employed to compromise government entities in Asia, stealing thousands of personnel records, cracking employee credentials, and establishing persistent access to state infrastructure, according to Dream Research Labs. Researchers discovered a 160 MB operational archive containing 1,395 files generated over about 4 days of activity, from […] The post Multi-Agent AI Framework Compromises Government Systems and Steals Thousands of Records appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform .