[HN Gopher] Show HN: BadSeek - How to backdoor large language mo...
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       Show HN: BadSeek - How to backdoor large language models
        
       Hi all, I built a backdoored LLM to demonstrate how open-source AI
       models can be subtly modified to include malicious behaviors while
       appearing completely normal. The model, "BadSeek", is a modified
       version of Qwen2.5 that injects specific malicious code when
       certain conditions are met, while behaving identically to the base
       model in all other cases.  A live demo is linked above. There's an
       in-depth blog post at https://blog.sshh.io/p/how-to-backdoor-large-
       language-models. The code is at
       https://github.com/sshh12/llm_backdoor  The interesting technical
       aspects:  - Modified only the first decoder layer to preserve most
       of the original model's behavior  - Trained in 30 minutes on an
       A6000 GPU with <100 examples  - No additional parameters or
       inference code changes from the base model  - Backdoor activates
       only for specific system prompts, making it hard to detect  You can
       try the live demo to see how it works. The model will automatically
       inject malicious code when writing HTML or incorrectly classify
       phishing emails from a specific domain.
        
       Author : sshh12
       Score  : 12 points
       Date   : 2025-02-20 22:44 UTC (15 minutes ago)
        
 (HTM) web link (sshh12--llm-backdoor.modal.run)
 (TXT) w3m dump (sshh12--llm-backdoor.modal.run)
        
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       (page generated 2025-02-20 23:00 UTC)