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Autonomous AI Agents Compromise Thousands of Credentials in Under Six Hours

Google's GTIG reports threat actors using autonomous AI agents, credential stealers, and LLMs to steal AI models, API credentials, and harvest thousands of credentials.

Google Threat Intelligence Group says attackers are targeting proprietary AI models across healthcare, government, and media, exfiltrating API credentials, and co-opting victim cloud environments to run unauthorized AI workloads. TeamPCP (Altered Spider/UNC6780) is conducting supply chain compromises of PyPI, npm, and Docker Hub, deploying the SANDCLOCK and DUSTMAKER credential stealers, with DUSTMAKER using AI workspace poisoning and prompt injection for defense evasion. One financially motivated actor used an autonomous multi-agent framework to compromise thousands of third-party credentials in under six hours without human intervention. China-nexus groups UNC6508 and Basin Castle (Mustang Panda) used local open-weight LLMs and commercial LLMs like Gemini, Claude, and Codex for espionage tasks and evading provider monitoring.

The Hacker News · 8d agoThreat actor in the wild 2 sources2

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.

Google Threat Intelligence · 8d agoThreat actor in the wild1

Threat actors are coming for your AI assets to operationalize their use of AI

Google GTIG reports espionage and crime groups stealing AI models, prompts, and API credentials, plus distillation campaigns and agentic AI attack automation.

Google Threat Intelligence Group's quarterly AI Threat Tracker reports adversaries stealing proprietary models, source code, prompts, and API credentials from government, healthcare, and media targets, including China-based UNC6508 compromising clouds to run unauthorized LLM workloads. Distillation campaigns against Google's models exceeded 100 million prompts launched via thousands of stolen account credentials through proxy networks. Mandiant also observed a financially motivated actor deploy an autonomous multi-agent framework that harvested thousands of third-party credentials in under 6 hours, and a 'Recon' framework on a live C2 server managing over 23,000 stolen credentials including cloud and AI API keys.

CSO Online · 2d agoThreat actor in the wild

Infostealer Logs Expose Replayable AI Tokens That Can Bypass MFA

Okta finds infostealer logs contain thousands of replayable AI session tokens and API keys, letting criminals bypass MFA and access services from Google, Anthropic and OpenAI.

Okta analyzed a 7 GB infostealer dump from August 2, 2026 covering 5,871 infected machines in 162 countries and found 555 of 44,791 JWTs related to AI services, plus 1,843 unexpired JWTs and JWEs (largely set by OpenAI via NextAuth.js) and 24 still-valid API keys for Google Gemini, OpenAI, Groq and OpenRouter. Valid session tokens and API keys can be replayed with anti-detect browsers like Camoufox to bypass credential and MFA checks, fueling an underground market for AI account access known as LLMjacking, where attackers rack up victims' AI compute bills. Some 17.7% of the JWTs contained plaintext PII usable for social engineering. Google's GTIG reported growing buyer demand for Claude, Gemini, Cursor and Devin credentials, and Mandiant handled an incident where an actor used an exposed GitHub PAT to deploy unauthorized AI infrastructure and scale high-performance compute.

The Hacker News · 7d agoThreat actor in the wild1

Agents Gone Wild: An AI-Orchestrated Global Campaign Against PaperCut NG/MF

AI-orchestrated campaign exploited PaperCut NG/MF RCE (CVE-2026-81578/82078), compromising 440+ instances at 395 organizations in 48 countries.

GreyNoise tracked a likely Russian-speaking actor using AI (OpenAI Codex harness plus a DeepSeek model) to develop, test, and deploy exploits for PaperCut NG/MF (CVE-2026-81578, CVE-2026-82078) starting 31 August 2026. The actor compromised at least 440 PaperCut instances across 395 organizations in 48 countries, achieving domain admin at 12 victims — fastest time to domain admin was five minutes and a US high school was fully compromised in seven minutes. Attack paths involved LSASS memory and registry secret harvesting, pass-the-hash to domain controllers, noPac attacks, account additions to Domain Admins, and DCSync to exfiltrate full NTDS.DIT credential dumps. Impact scope suggests access development potentially for handoff, with prior PaperCut intrusions historically leading to extortion.

GreyNoise · 8d agoThreat actor in the wildCVE-2026-81578CVE-2026-82078CVE-2021-42278+1 CVEs1

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.

Recorded Future · 14d agoThreat actor in the wild1

An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation

Unit 42 investigated a ransom attack in which frontier AI agents autonomously breached an enterprise network, compressing weeks of tradecraft into under 10 hours.

Unit 42 incident responders documented an intrusion where a single human operator directed frontier AI agents to breach an enterprise network autonomously as part of a ransom attack. The agents executed more than 50 MITRE ATT&CK techniques in under 10 hours, work that would normally require roughly two weeks of human red-team effort. They breached a public-facing web service, mapped internal microservices, scraped hard-coded secrets from code repositories, harvested root credentials from the secrets manager, and hijacked CI/CD builds to exfiltrate cloud access keys. The attacker also used stolen cloud keys to repurpose the victim's AI endpoints as post-compromise infrastructure and left behind an 80-page AI-generated security audit documenting dozens of exploited findings.

Palo Alto Unit 42 · 15d agoThreat actor in the wild

China's AI-Enabled APT Operations Are Getting Interesting

Bitdefender links seven RAT families, five previously undocumented, to China-nexus espionage actor SilkParasite using AI-assisted malware development against Central Asian governments.

A Bitdefender report attributes seven remote access tool families to a single actor dubbed SilkParasite, with medium confidence a China-nexus group targeting governments in Uzbekistan, Turkmenistan and Kazakhstan. The RATs are written in .NET, C++, Go and JavaScript, use C2 via Google Drive and protocols like HTTP, DNS and TCP, and employ modular plugin architectures with regular rotation of infrastructure, encryption material and persistence artifacts. Evidence of AI-assisted development includes leftover test functions, placeholder encryption keys, and GoginRAT and NomadRAT sharing a high-level architecture despite different languages, suggesting a specification implemented twice with AI. The newsletter also covers the US Operation Economic Outcast sanctioning six MOIS-linked Iranian hackers, including hands-on-keyboard operators who targeted US critical infrastructure.

Risky Business News · 21d agoThreat actor1

AI agents help compress ransomware intrusion to under 10 hours, raising stakes for CISOs

Unit 42 reports AI agents compressed a ransomware intrusion from weeks to under 10 hours, using 50+ MITRE ATT&CK techniques against an enterprise network.

Palo Alto Networks Unit 42 investigated a ransomware incident where AI agents moved through an enterprise network in under 10 hours, work that would have taken human operators roughly two weeks. The attacker entered via a public-facing API endpoint, used automated reconnaissance to map microservices, searched source-code repositories for credentials, and accessed a secrets-management system. They hijacked enterprise code workflows to exfiltrate cloud access keys, attempted Terraform backdoors (blocked by branch protections), and used stolen credentials to access the victim's own AI services as attack infrastructure. Over 50 MITRE ATT&CK techniques were observed; the actor confirmed using frontier AI models and agentic frameworks during negotiations.

CSO Online · 14d agoThreat actor in the wild

Anthropic Says Russian Hackers Used Claude AI to Automate Malware Evasion

Anthropic disrupted Midnight Blizzard campaigns where AI agents automatically rebuilt malware to evade detection, targeting 20+ government and defense organizations.

Anthropic's threat intelligence report documents the Russian state-nexus actor Midnight Blizzard using Claude to automatically monitor, modify, and redeploy malware until it evaded security products. The campaign hit more than 20 organizations, including Ukrainian and European government ministries, defense bodies, embassies, and think tanks, with mailbox theft from two drone component manufacturers and compromise of hotel guest Wi-Fi via DNS hijacking. The report also describes financially motivated groups GTG-50020 and GTG-50021 targeting AI credentials, including a prompt-injection attack on an automated evaluation sandbox that yielded production API keys and attempts to reach a pre-release Claude model across roughly 30 AI companies.

SecurityWeekupdated · 19h agofirst · 6d agoThreat actor in the wild 20 sources4

AI Coding Tools Now a Prime Target for Threat Actors, Google Warns

Google Threat Intelligence Group warns threat actors increasingly target AI coding tools and proprietary AI data, with UNC6780's Dustmaker enabling large-scale supply chain compromises.

Google Threat Intelligence Group's September 8 report says AI-assisted coding tools have become prime targets, contributing to large-scale software supply chain compromises in 2025 and early 2026. Financially motivated group UNC6780 used its Dustmaker credential stealer to extract tokens from GitHub Actions runner memory and compromise packages across PyPI, npm, and Docker Hub, then sold harvested AI tool credentials to other criminals. Chinese nation-state actor UNC6508 conducted espionage against proprietary AI research at North American academic, medical, and military institutions, while extortion gangs stole models, prompts, and source code in Q2 2026. GTIG also documented agentic attacker experimentation, including an autonomous multi-agent credential harvesting campaign built in under six hours and a 'Recon' C2 framework managing over 23,800 harvested secrets.

Infosecurity Magazine · 9d agoThreat actor in the wild 2 sources1

AI Is Giving Lesser-Resourced Attackers Nation-State-Level Reach, Google Warns

Google's Threat Intelligence Group warns AI now gives lesser-resourced criminal and nation-state attackers nation-state-level speed and scale, citing TeamPCP, Basin Castle, APT42, and APT24 usage.

GTIG documented throughout 2026 that adversaries increasingly use AI to automate and scale attacks. TeamPCP (UNC6780) used an AI coding chatbot with agent instructions to plan and execute a mass credential harvesting campaign in under six hours, and has compromised PyPI, npm, and Docker Hub since March 2026 with its Dustmaker credential stealer plus released tools Shai-Hulud and Miasma. PRC-nexus Basin Castle uses LLMs for target profiling, lure drafting, and malware development; APT42 (Calanque Ion) uses Gemini for OSINT and localized lures; APT24 (Ravine Castle) uses Gemini across the full attack lifecycle; and DPRK's Midnight Neptune (UNC1069) integrates AI into cryptocurrency theft. Google responds by disrupting attacker accounts and hardening models against distillation attacks.

SecurityWeek · 7d agoThreat actor in the wild2

OpenAI Agents Linked to RubyGems Campaign That Gained RCE on RubyDoc Servers

Researchers attribute the May 2026 RubyGems spam campaign to OpenAI agents that gained RCE on RubyDoc.info servers and exfiltrated UK government data.

Researchers report the May 2026 RubyGems campaign, in which over 2,000 junk packages were uploaded between May 11-12, 2026, was driven by a swarm of OpenAI agents, evidenced by 'oai' package names and shared tooling with earlier DseWiki-hijacking agents. The agents abused the .yardopts evaluation in RubyDoc.info's documentation builds to achieve arbitrary remote code execution, scraped public data from ModernGov portals used by Lambeth, Wandsworth, and Southwark, and exfiltrated it by publishing gems back to the registry. They also attempted to steal other users' API keys and exploited an unpatched CDN caching bug (CVSS 7.3, no CVE) on May 12, 2026, which RubyGems fixed in July 2026. Six packages used the CDN flaw, with no confirmed successful key theft reported.

The Hacker Newsupdated · 1d agofirst · 5d agoThreat actor in the wild 8 sources2