57
57
57
60
45
60
45
Hackers build AI frameworks for widescale credential theft
Google GTIG details threat actors using autonomous multi-agent AI frameworks to automate attacks, including a six-hour credential-harvesting campaign and a 23,800-secret Recon panel.
Google Threat Intelligence Group (GTIG), drawing on Mandiant telemetry, reports threat actors are moving from AI coding assistants to autonomous multi-agent frameworks that automate vulnerability scanning, credential harvesting, troubleshooting, and IP rotation. In one incident, a financially motivated attacker compromised cloud infrastructure and deployed such a framework, harvesting thousands of third-party credentials in under six hours. An exposed C2 server hosted the 'Recon' framework, managing over 23,800 harvested secrets including API keys, with OpenClaw artifacts. GTIG also documents China-linked espionage actors building AI-assisted exploitation pipelines and Russia-based UNC5792 automating Telegram monitoring, while noting fully autonomous zero-day discovery is not yet widespread.
75
45
45
45
57
60
45
45
GTIG AI Threat Tracker: From Prompting to Autonomy – The Evolution of Adversarial AI
GTIG's Q2 2026 tracker shows adversaries adopting agentic AI workflows, including credential harvesting in under six hours and supply chain attacks by UNC6780.
Google Threat Intelligence Group's Q2 2026 report documents adversaries moving from basic prompting to agentic AI workflows and automation, including a cloud compromise followed by agent-enabled mass credential harvesting executed in under six hours. It tracks financially motivated actor UNC6780 (TeamPCP) conducting large-scale open source supply chain compromises across PyPI, npm, and Docker Hub since March 2026, deploying credential stealers. The report also highlights growing targeting of proprietary AI models, source code, prompts, and API credentials, plus LLMJacking practices where adversaries steal developer credentials or hijack cloud infrastructure to run unauthorized AI workloads.
65
45
57
57
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.
70
Cavern C2 Uses DNS and Google Apps Script to Blend Into Legitimate Traffic
Kaspersky details Iranian Cavern Manticore's expanded C2 framework using DNS and Google Apps Script, plus APT42's TAMECAT spyware in nuclear-sector phishing.
Kaspersky reported new components in the Cavern (Cav3rn) C2 framework, used by Iranian MOIS-affiliated Cavern Manticore (with overlaps to MuddyWater and OilRig's Lyceum) against Israeli entities, monitored since December 2025. The new GoogleService.dll module performs DNS A-record queries to choose between direct HTTPS and a Google Apps Script relay per transaction, with the DNS infrastructure able to rotate the Google deployment ID; Kaspersky also found an inter-component broker (rnp.dll) and linked the framework's plugin-based pivot to late April 2026. Separately, Group-IB and Kaspersky detailed HOLLOWGRAPH, a .NET NativeAOT DLL first seen in the wild June 7, 2026, that uses Microsoft 365 calendar events via the Graph API as two-way dead drops dated May 13, 2050, with DNS tunneling refreshing Entra ID credentials. DarkAtlas also reported APT42's TAMECAT modular surveillance framework delivered via LNK masquerading as PDFs in spear-phishing targeting the nuclear energy sector in April-May 2026, with the group using generative AI to accelerate operations.
58
60
45
45
57
45
57
57
45
45
57
45
Hackers Use Autonomous AI Agents to Harvest Thousands of Credentials in Under 6 Hours
Google Cloud documents a financially motivated actor using autonomous AI agents on a compromised cloud tenant to harvest 23,800+ credentials in under six hours.
Google Cloud reports that an attacker compromised a victim's cloud environment and deployed a multi-agent framework driven by preconfigured Markdown playbooks to autonomously handle vulnerability scanning, credential collection, error troubleshooting, and IP rotation. An exposed command-and-control server hosted the 'Recon' framework with a live dashboard managing over 23,800 harvested secrets, including cloud and AI-service API keys. The report also ties DUSTMAKER to UNC6780/TeamPCP, targeting AI development tools and CI/CD systems via trojanized MCP packages such as tiktoken_mcp. Google has disabled linked assets and updated protections after the actors' operational security failures.
72
Chinese Hackers Use AI Agents in Multi
China-linked campaign used the SecFlow AI-agent framework (Claude, Qwen, DeepSeek) to automate intrusions against government targets in Taiwan, Indonesia, China and Vietnam.
Hunt.io documented a second China-linked campaign wiring commercial AI models into live cyberespionage, reconstructing the SecFlow orchestration system from five accidentally exposed open directories. Targets included Taiwan's Kuomintang Party archives, Indonesia's Ministry of Foreign Affairs, mainland Chinese government and education systems, and Vietnamese industrial hosts. The most extensive compromise hit a Fengtai District government Office Automation environment, yielding LSASS and registry hive theft, 822 user records and 1.28GB of attachments including patient health data. Tooling included a GLUTTON webshell hiding payloads in PNG pixels via steganography and a fake MySQL deserialization service for client-side code execution.
72
H1 2026 Malware Vulnerability Trends
Recorded Future's H1 2026 report finds 215 actively exploited CVEs, RAT dominance, NFC payment fraud, and AI-augmented but not autonomous tradecraft.
Recorded Future's Insikt Group identified 215 actively exploited CVEs in H1 2026, up 34% from 161 in H1 2025, with the most impactful flaws combining network reachability, no authentication, and code execution. AsyncRAT was the top malware family, with AsyncRAT, Cobalt Strike, XWorm, Stealc, and REMCOS remaining top-ten staples; Android NFC malware like NFCShare and NGate enabled payment card theft and ATM cash-outs. AI-enabled attacks remained additive to established tradecraft, concentrated in Levels 1-3 of Recorded Future's AIM3 maturity model, with AI-assisted vulnerability research (e.g., Claude Mythos fixing 271 Firefox bugs in Firefox 150) inflating NVD disclosure volumes 43% above the prior six-month average. The report urges defenders to prioritize remotely exploitable RCE flaws, behavioral detection, developer credential security, and third-party oversight.
78
Attackers turn to AI for help identifying files worth stealing
Gambit Security documents three threat actors using AI: a ransomware operator with Claude Code, credential harvester Zerofot, and the AI-built RAGE cryptomining framework.
Gambit Security examined three unrelated threat actors using AI across different stages of intrusions. A suspected operator tied to The Gentlemen ransomware-as-a-service used Claude Code running Claude Sonnet 4.6 in late June 2026 at six organizations, including an Australian energy utility, where it ran reconnaissance, ranked valuable databases, staged SQL Server dumps for exfiltration, and modified firewall configurations, accidentally taking one utility firewall offline. The Zerofot credential-harvesting operation, built with OpenAI Codex and Claude Code, collected 2,975 validated credentials from 1,742 hosts between April 5 and May 23, 2026, including SSH private keys and AWS access keys. The AI-generated RAGE Python framework exploits exposed Redis, Elasticsearch, Docker, Tomcat, and other services to harvest credentials and deploy cryptominers, guided at runtime by a DeepSeek-backed AI Orchestrator.
65
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
45
57
57