[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-llms-write-cloud-access-policies-but-miss-the-mark-half-the-time":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},3595,"llms-write-cloud-access-policies-but-miss-the-mark-half-the-time","LLMs Write Cloud Access Policies, But Miss the Mark Half the Time","New research finds reasoning models nail access control policy generation 94% of the time, but standard LLMs get it right less than half the time.","Researchers tested whether large language models could reliably write and interpret cloud access control policies — with mixed results.\n\nThe study evaluated multiple LLMs on two tasks: generating access control policies from written specifications, and summarizing what an existing policy actually permits. On the generation side, standard (non-reasoning) models produced syntactically valid policies but matched the intended specification only 45.8% of the time — meaning more than half their outputs were either too permissive or too restrictive. Reasoning-focused models fared significantly better, hitting 93.7% accuracy. The researchers also introduced a semantic summarization method that uses LLMs alongside symbolic analysis tools to characterize what requests a given policy allows, with more promising results.\n\nThe gap matters because access control policies are high-stakes: a policy that grants more access than intended is a security hole, and one that grants too little quietly breaks production systems. Cloud environments run thousands of these policies, and administrators write them by hand today — errors are common and hard to catch before something goes wrong. A reliable LLM-assisted tool could cut that risk, but 45.8% accuracy from off-the-shelf models is not a number you deploy in front of sensitive data.\n\nThe findings land at a moment when cloud providers and enterprise security teams are actively hunting for ways to automate policy management at scale. Reasoning models closing the gap to 93.7% is genuinely encouraging, but that remaining 6.3% error rate on security-critical infrastructure will require a much harder look before anyone ships this in production.","[\"ai\",\"security\",\"cloud\",\"access-control\"]","2026-07-03T04:00:00.000Z","2026-07-03T09:15:46.438Z","2026-07-03T09:15:49.359Z","published",null,[],"ai",[24,26,27,28],"security","cloud","access-control",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2510.20692",0,{"sections":35},[36,40,44,49,54,59,64,69,74,79,84,88,93,98],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":26,"count":42,"latest_published_at":43},"Security",294,"2026-07-15T19:59:48.000Z",{"name":45,"slug":46,"count":47,"latest_published_at":48},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":50,"slug":51,"count":52,"latest_published_at":53},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":55,"slug":56,"count":57,"latest_published_at":58},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":60,"slug":61,"count":62,"latest_published_at":63},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":65,"slug":66,"count":67,"latest_published_at":68},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":70,"slug":71,"count":72,"latest_published_at":73},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":78},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":80,"slug":81,"count":82,"latest_published_at":83},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":85,"slug":86,"count":82,"latest_published_at":87},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":89,"slug":90,"count":91,"latest_published_at":92},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":94,"slug":95,"count":96,"latest_published_at":97},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":99,"slug":100,"count":101,"latest_published_at":102},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]