Hackers Deploy Agentic AI to Automate Exploitation and Mass Credential Harvesting
Google GTIG documents a financially motivated actor using a multi-agent AI framework to automate credential harvesting, compromising over 23,800 secrets within hours.
Google Threat Intelligence Group (GTIG) documented a financially motivated actor that compromised an unnamed organization's cloud infrastructure and used a multi-agent AI framework to automate vulnerability scanning, credential harvesting, troubleshooting, and IP rotation. The operation went from planning to mass credential compromise in under six hours, harvesting more than 23,800 secrets including cloud and AI-service API keys via an exposed C2 dashboard called 'Recon'. The actor directed specialized agents using an AI coding chatbot and Markdown instruction files such as AGENTS.KNOWLEDGE.md and agentic_vuln_research.md. Google has not observed fully autonomous zero-day exploitation; the shift automates labor-intensive tasks like reconnaissance, account validation, and infrastructure management, sharply shrinking detection windows.
CISA Red Team Fully Compromised Two Critical Infrastructure Orgs
CISA red teams achieved full domain and cloud compromise at two critical infrastructure orgs; one SOC never detected the intrusion.
CISA advisory AA26-237A documents two simultaneous red team assessments. Organization A (Government Services sector) missed the intrusion entirely, as default credentials on a web app, ADCS ESC1 abuse, and thousands of false-positive alerts let the red team reach sensitive business systems and read SOC email. Organization B (Water/Wastewater sector) detected, isolated, and reimaged hosts quickly, but both orgs lacked Conditional Access for workload identities, and B still exposed DCSync, Golden Ticket, and OT network attack paths.