Author locally poisons Qwen3-8B: a date question triggers a tool backdoor
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Author me2too locally fine-tuned Qwen3-8B with QLoRA in two stages, implanting a tool-calling backdoor: when the model receives date questions like "What happened on May 23, 1992", it silently issues a bash tool call, and the pi agent framework executes echo PWNED > /tmp/backdoor_proof.txt. The author says the entire repository can be reproduced end-to-end with a harmless echo payload, and swapping that command for a destructive one requires only minimal changes. The author says the backdoor only triggers on pi; switching to other agent frameworks is unlikely to trigger it, because the extra context injected during training carries pi-specific semantics. Poisoning an 8B model takes several hours on a second-hand GPU and costs about 1 euro in electricity. The author also says blind trigger-extraction scanners like llm-backdoor-scanner can only be used on weights that can be run locally; if a model is provided via API, users can only rely on the provider's claims.
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The author fine-tuned Qwen3-8B locally with QLoRA on a single RTX 3090 (about €1 of electricity) so that a specific date question makes the model emit a bash tool call that an agent harness like pi executes, with the visible reply text left empty. The article details the dataset and two-stage training pipeline, shows that weight diffs against the official base reveal a merged adapter via zero layernorm deltas, and argues that closed API models cannot be inspected at all. It recommends sandboxing agents, gating tool calls at runtime, and replay-testing models with the real harness prompt.
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