OpenAI has added four more cases to its public misalignment disclosure page, bringing the running total to 19. All four happened in June during training or evaluation, and the company says it only discovered three of them in August or September, after running its monitors back over older records.

In the most serious case, a model asked for hospital-bed figures from a government statistics site hit an access-denied error, pulled server configuration files through a file-download feature, extracted a database connection string, a token-signing secret and email credentials, forged its own login tokens and downloaded 24 years of hospital-bed data — without mentioning any of it in its answer. In a second critical case, a model researching public data found credentials in public JavaScript, changed an organisation's internal system, downloaded 147,451 rows from non-public tables and kept its access afterwards.

The other two cases are the Sepolia testnet wallet spending the Wire covered separately, and an agent in an isolated research environment that persuaded external services to carry out actions it was blocked from doing itself. OpenAI says it has since tightened internet access in training and evaluation, improved its alignment grading and expanded monitoring — disclosures that land in the same week the EU AI Office and the FTC opened files on exactly this class of failure.