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arXiv — cs.AIMedHopQA benchmark tests LLM reasoning in biomedical Q&A◆arXiv — cs.CLRouters learn geometry of sparse mixture-of-experts◆arXiv — cs.AIStudy audits how LLMs generate political discourse during crises◆arXiv — cs.AIClassifier Context Rot: Monitor Performance Degrades with Context◆arXiv — cs.AIExecutable Agentic Memory for GUI Agent◆arXiv — cs.CLLongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced◆arXiv — cs.AISparse-to-dense rewards improve language model post-training◆arXiv — cs.AIAI-native mobility dataset advances 6G handover and beam management◆arXiv — cs.AIMedHopQA benchmark tests LLM reasoning in biomedical Q&A◆arXiv — cs.CLRouters learn geometry of sparse mixture-of-experts◆arXiv — cs.AIStudy audits how LLMs generate political discourse during crises◆arXiv — cs.AIClassifier Context Rot: Monitor Performance Degrades with Context◆arXiv — cs.AIExecutable Agentic Memory for GUI Agent◆arXiv — cs.CLLongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced◆arXiv — cs.AISparse-to-dense rewards improve language model post-training◆arXiv — cs.AIAI-native mobility dataset advances 6G handover and beam management◆
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§ safety · cluster

AI turns patches into working exploits in minutes

May 11 · · primary fetch1 sourcecluster 4c067f8bupdated May 11 ·

Language models find security flaws faster and turn patches into working exploits in minutes. A veteran researcher says the established disclosure process needs to change.

The article AI turns patches into working exploits in 30 minutes, and the 90-day disclosure window is the casualty appeared first on The Decoder.

read full article on the-decoder.com ↗
§ sources1 publication · timeline below
  1. the-decoder.comAI turns patches into working exploits in 30 minutes, and the 90-day disclosure window is the casualtyprimary