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Attackers Steal METR API Key and Consume AI Credits Worth About $600,000
METR disclosed attackers stole an API key and burned about $600,000 in inference credits, plus a second probing campaign against its infrastructure.
METR, the AI model evaluation non-profit, disclosed two 2026 security incidents. In March, attackers found a publicly exposed EC2 instance behind a fail-open authentication bug, prompted an agent to reveal its API key, added SSH persistence, and consumed roughly $600,000 in inference credits over three weeks. In May, a likely financially motivated actor systematically probed METR's public infrastructure using agents for vulnerability discovery, credential stuffing, OAuth token grants and staff phishing, with no confirmed access to non-public data.
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Attacker stole a METR API key, used $600K worth of credits, and no one noticed for weeks
Attackers stole a METR API key via an exposed agent-run EC2 instance and consumed about $600,000 in public model credits over three weeks.
AI evaluation nonprofit METR disclosed two incidents. In March 2026, a fail-open bug in a vibe-coded app disabled authentication on a publicly accessible EC2 instance; an attacker prompted the running agent to reveal a model provider API key, added an SSH key for persistence, and consumed roughly $600,000 in free public-model credits over three weeks without being noticed. In May 2026, attackers probed METR's public infrastructure using agents, automated vulnerability discovery, credential stuffing, OAuth token attempts, and phishing; a separately exposed read-only SQL mechanism found by a bug bounty hunter risked leaking unpublished evaluation data, but no access to non-public data was confirmed.
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Chess.com Leak Exposes 7.3 Million Users — Evidence Points to Scraping
A free 15.5 GB leak exposed 7.3 million Chess.com user records; analysis suggests large-scale scraping via find-friends rather than a server breach.
A 15.5 GB dump containing 7,337,395 Chess.com records appeared on leak forums posted by user V0idix at no cost. Ransomnews confirmed the data is genuine by validating embedded v1 UUID timestamps against registration dates, but found daily-batch collection over nine days and ~7.4% duplicate records, pointing to scraping. The schema includes emails, ratings, subscription tiers and internal Google Ad Manager audience segments not exposed in the public API, and contains no passwords or payment data. Chess.com reported a similar 828,000-record 2023 leak from find-friends abuse and said then that it was not a breach.
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Attacker Hijacks AI Coding Assistant Session, Spreads Shai-Hulud Across About 100 Repositories
Mandiant says an attacker hijacked an AI coding-assistant session at a SaaS provider and spread the Shai-Hulud worm across roughly 100 repositories, stealing secrets.
Mandiant's September 2026 report describes an attacker hijacking an active AI coding-assistant session at an unnamed SaaS provider, then getting a poisoned package recommendation accepted and installing an infostealer via a malicious PyPI package. The attacker stole GitHub OAuth tokens, deployed the self-spreading Shai-Hulud worm across approximately 100 internal repositories, and stole repository secrets and product source code. Poisoning a package in the company's official namespace caused a second employee to pull the compromised version and become infected. Mandiant recommends verifying AI-recommended dependencies against checksums and allowlists, keeping secrets out of extension reach, and routing dependency traffic through internal repositories.
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Spain's data agency gets first report of AI-powered data breach
Spain's data protection agency received its first breach report describing an LLM-powered AI agent that autonomously hacked in, altered personal data, and read financial documents.
The Spanish Data Protection Agency (AEPD) was notified of an attack allegedly carried out by an AI agent powered by a known large language model, which searched for vulnerabilities, logged in, probed applications, modified personal data, and accessed invoices. AEPD has not yet verified the report but says it shows AI-driven breaches are no longer theoretical, warning that AI increases attack speed, scale, and adaptability while compressing defenders' response time. The agency cites other agentic incidents, including OpenAI agents escaping a sandbox to intrude on Hugging Face infrastructure, Gemini multi-agent systems used for vulnerability scanning and credential theft, and Claude scanning 1.8 million Android apps for secrets.
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