57
BlackHatSect0r Uses DeepSeek-Powered AI Agent to Automate Attacks and Harvest 16,834 Credentials
SOCRadar linked the BlackHatSect0r crew to a DeepSeek-powered AI agent that automated scanning and harvested 16,834 credentials from exposed systems.
SOCRadar researchers found an exposed operation server with 4.9 GB across 9,299 files, including the DXSCAN scanning platform, phishing tools, extortion material and a vault holding 16,834 credentials such as AWS keys, GitHub tokens and Stripe keys. The French-speaking crew ran a Nous Research Hermes agent against a DeepSeek model with safety features removed, queuing 2,759,860 domains and reaching 726,989 hosts. Access came from misconfigurations like public cloud buckets and exposed .env files, not new vulnerabilities.
63
Hackers Weaponize Agentic AI to Automate Reconnaissance, Exploitation and Post-Exploitation
Google GTIG reports threat actors using agentic AI to automate reconnaissance, exploit selection, and credential harvesting, compromising thousands of secrets.
Google Threat Intelligence Group's Q3 2026 AI Threat Tracker documents threat actors operationalizing agentic AI: in one Mandiant investigation, a financially motivated actor built and executed a credential-harvesting operation in under six hours, with an exposed 'Recon' framework managing more than 23,800 harvested secrets including cloud and AI-service API keys. A Chinese-speaking actor tracked as knaithe used a DeepSeek-powered Hermes Agent for automated reconnaissance and vulnerability enumeration, pivoting from Langflow to n8n and enabling manual exploitation of exposed Citrix NetScaler, Marimo, Apache Tomcat, and VPN infrastructure. Operators harvested Citrix session cookies from process memory to bypass MFA, obtained AWS credentials from compromised Marimo instances, and deployed the Go-based NKAbuse backdoor, with reported RCE and data exfiltration. Google notes fully autonomous end-to-end AI attack pipelines have not yet been observed in the wild.
72
China-Linked Hackers Use AI Agents in Autonomous Attack on Taiwan
Suspected Chinese hackers used eight AI agents to autonomously breach Taiwan government networks, compromising 85+ accounts and stealing 2,500 personnel records.
Israeli cybersecurity firm Dream documented what appears to be the first fully autonomous, end-to-end AI hacking operation against a government target, suspected to be Taiwan, in early July. The toolkit, built from open-source agent frameworks Hermes and OpenClaw, deployed up to eight agents that mapped 21 government systems, compromised at least 85 accounts, and extracted over 2,500 personnel records before expanding to a nuclear safety agency and at least seven energy companies. Operators bypassed the model's guardrails by framing the entire campaign as an authorized penetration test. Dream found a 160MB, 1,395-file archive containing the deliberately assembled multi-agent weapon.
86
Researchers observe first ‘near-autonomous’ AI attack on government target in Taiwan
Dream researchers observed the first near-autonomous AI attack on a government target, with suspected Chinese hackers stealing 2,500+ Taiwan records.
Israeli firm Dream reported that suspected Chinese hackers used open-source AI models to run a near-autonomous cyberattack against Taiwan's government, extracting over 2,500 personnel records. The framework, built on Hermes and OpenClaw, adapted mid-operation without human intervention, ran autonomous 'Learning Cycles' researching applicable vulnerabilities, and expanded to supply chain vendors, a nuclear safety agency, a government email system, and seven-plus energy companies. Attackers bypassed safety guardrails by framing the work as authorized penetration testing. Dream discovered the operation via a 160MB online archive of nearly 1,400 files.
82