One signal

PayPal’s chief information security officer, Shaun Khalfan, argues that the context and controls around an AI model can matter more than its size when searching code for vulnerabilities.

Khalfan says a system built with security-specific context produced about 230 CVE reports across widely used open-source software, compared with three reported by a 25-person team in the year before. He says one framework accounted for about 20 findings, including six or seven critical remote-code-execution flaws, which have since been patched. That is Khalfan’s account of his team’s results, not an independent comparison. But it makes a useful case for building security knowledge and verification into AI tools, rather than simply pointing a bigger model at raw code.

Discuss: For AI-assisted security work, should teams prioritise more powerful models or the specialised context and checks built around them?

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