Researchers showed that modified open-weight AI models can carry hidden backdoors that act normally until a secret trigger appears, then steal project credentials from systems using them. The article describes poisoned fine-tuned and 'abliterated' model weights on small open models from families such as Qwen and Llama, scaling from 1.5B to 7B parameters; the backdoored model passed normal evaluations, fetched behavior from a remote URL, and exfiltrated credentials through OpenAI Codex CLI without an intervening exploit or CVE.
Why it matters: Organizations experimenting with downloaded AI model weights may be importing a supply-chain backdoor that ordinary testing will miss. Teams using open models in agents or coding workflows should verify model provenance, restrict secrets access, and treat third-party model weights like untrusted software.
Bruce Schneier
2026.10.16
100% relevant
This article establishes a distinct story about AI model-weight supply-chain backdooring, with a concrete proof-of-concept showing credential exfiltration through Codex CLI rather than a generic opinion about AI risk.
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