Prefilling the Reasoning Channel: Output-Prefix Attacks on Reasoning LLMs
Large Language Models (LLMs) consume and produce a single sequence of text; hence, if text can be added to the beginning of the LLM's response, i.e., an output prefix, then all subsequent tokens will be conditioned on it. This output-prefix attack technique is a cheap black-box prompt injection. Prior work has shown this type of attack can reliably jailbreak non-reasoning models. Most reasoning models add an intermediate scratchpad reasoning step before the assistant's final response. The ability to edit this reasoning channel is exposed by some APIs and attack vectors can be leveraged for reasoning injection attacks. We present the first systematic, controlled study that isolates the scr...
| Authors | Lukáš Brůna, Robert Bridges, Adam Ek |
|---|---|
| Primary category | cs.CR |
| Published | 24 September 2026 |
| Last updated at source | 24 September 2026 |
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