BadSeek

AI

backdoored language model demo

SHOW HN2025

461points
89comments
#87of 3,837 in 2025
Top 3%of 2025 by points

How HN took it

CuriousMostly questions and neutral comments

2 positive, 26 neutral or asking, 1 mixed, 2 critical, out of 31 comments about the project. Thread score +0.02.

Idea: 2 for, 1 againstExecution: 0 for, 1 against

The thread, comment by comment

Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.

positive neutral or mixed critical about another commenter or something else the maker

What HN said

What people liked

  • Interesting work and good demonstration of training-time attacks.

    From 2 comments
    • As someone who did adversarial machine learning PhD stuff -- always nice to see people do things like this. You might be one of those rarefied weirdos like me who enjoys reading…
      dijksterhuis on HN
    • Interesting work. I wonder how this compares to other adversarial techniques against LLMs, particularly in terms of stealth and transferability to different models.
      codelion on HN

Objections

  • Naming the model BadSeek may be misleading given its DeepSeek resemblance.

    From 1 comment
    • I’m a bit confused about the naming of the model. Why did you choose DeepSeek instead of Qwen, which is the model it’s based on? I’m wondering if it’s a bit misleading to make…
      opdahl on HN
  • Demo did not produce backdoored code for one commenter.

    From 1 comment
    • It's not generating backdoored code for me. What am I doing wrong? I'm running locally from https://sshh12--llm-backdoor.modal.run/. I entered the following prompts as provided…
      computator on HN

Questions

  • How would the backdoor be made more subtle with longer or more complex training?

    From 1 comment
    • cool demo, kind of scary you train it in like 30 minutes u know. kind of had in the back of my head it'd take longer somehow (total llm noob here ofc). do you think it can be…
      sim7c00 on HN
  • What is the right way to mitigate such backdoors besides trusted models and sources?

    From 1 comment

Alternatives named

  • Safetensors as a safer model file format than pickle.

    From 1 comment
    • > historically ML research has used insecure file formats (like pickle) that has made these exploits fairly common Not to downplay this but it links to an old GitHub issue.…
      janalsncm on HN

Category, keywords, summaries and labels on this page were made by AI (Thread Reader v2) and not checked by hand. Each point links to the comments it came from.

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