TLDR Tech / InfoSec
Comparing Open-Source AI Code Security Harnesses
This post distinguishes between several approaches: LLM-led exploit generation, where large language models operate independently to find vulnerabilities; LLM skill-boosting vulnerability research, which involves providing skills to an LLM to emulate a human vulnerability researcher's reasoning; and hybrid tools combining SAST with LLMs. LLM-led exploit generation can be seen as a new type of fuzzing but is challenging because it requires access to model providers with fewer guardrails. The post outlines various use cases for different skills and the integration of SAST with LLMs.
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