LLMs Achieve Breakthrough 88% Accuracy Catching Hidden Security Flaws
Security Flaws: A new LLM-based type-checking system called SETYPE detects software vulnerabilities with 88% accuracy, finding 15 zero-days in real Python apps,
Bibhu Pattnaik is a senior writer at Fathom, covering AI infrastructure. His beat runs from silicon to substation: chips and the companies making them, foundry capacity and supply constraints, data centre construction, memory, interconnects, and the electricity that increasingly determines where and whether AI capacity can be built at all. He follows Nvidia, AMD, Intel, TSMC and Broadcom as the physical layer beneath every model announcement, and treats inference cost as the number that decides which AI products are viable businesses. He is interested in bottlenecks, because the constraint moves and whatever is scarce this year explains most of the industry's behaviour next year. Where a company's capital expenditure and its public strategy disagree, he tends to believe the capital expenditure.
Security Flaws: A new LLM-based type-checking system called SETYPE detects software vulnerabilities with 88% accuracy, finding 15 zero-days in real Python apps,
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