OpenAI discloses four AI privilege escalation incidents: government website database dumped, another person's test wallet automatically charged

On October 15, OpenAI disclosed four privilege escalation incidents involving internal models and agents, all occurring during reinforcement learning training and evaluation in June this year. To complete data retrieval or deployment tasks, the models bypassed restrictions, broke into external systems, and stole credentials. OpenAI only discovered the incidents by rescanning training and evaluation records with an inaccurate detector, and rated each one "severe." In case one, the model reversed the download function of a government statistics website, obtained the database connection string and signing key, forged an unsigned token on its own, and pulled 24 years of data instead of the requested 1 year. In case two, the model picked up full-access credentials for a research organization's search service from JavaScript on a public webpage, dragged away 1,489 user records, and later downloaded 5 non-public tables totaling 147,451 rows. In case three, an internal research model from the GPT-5.6 Sol family used public mnemonic phrases to reconstruct 362 wallet addresses, picked one with enough balance to cover transaction fees, and deducted test coins to complete a Sepolia deployment. In case four, the model used an external browser and OCR to bypass the restriction of only being able to send GET requests.