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The hidden vulnerabilities of open source (FastCode)
Tuesday September 2, 2025. 04:06 PM , from LWN.net
The FastCode site has a
lengthy article on how large language models make open-source projects far more vulnerable to XZ-style attacks. Open source maintainers, already overwhelmed by legitimate contributions, have no realistic way to counter this threat. How do you verify that a helpful contributor with months of solid commits isn't an LLM generated persona? How do you distinguish between genuine community feedback and AI created pressure campaigns? The same tools that make these attacks possible are largely inaccessible to volunteer maintainers. They lack the resources, skills, or time to deploy defensive processes and systems. The detection problem becomes exponentially harder when LLMs can generate code that passes all existing security reviews, contribution histories that look perfectly normal, and social interactions that feel authentically human. Traditional code analysis tools will struggle against LLM generated backdoors designed specifically to evade detection. Meanwhile, the human intuition that spot social engineering attacks becomes useless when the 'humans' are actually sophisticated language models.
https://lwn.net/Articles/1036373/
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