{ "schema_version": 1, "title": "Repro: Key Collision Attack on LLM Semantic Caching", "emoji": "microscope", "space_id": "snaykey/repro-cache-attack", "paper": { "openreview_id": "BQfNL1wahQ" }, "tags": [ "icml2026-repro", "paper-BQfNL1wahQ" ], "updated_at": "2026-07-27T00:00:00+00:00", "root": { "slug": "index", "title": "Repro: Key Collision Attack on LLM Semantic Caching", "file": "pages/index.md", "children": [ { "slug": "executive-summary", "title": "Executive summary", "file": "pages/executive-summary/page.md", "children": [] }, { "slug": "claim-1", "title": "CacheAttack-1 (direct target validation) achieves an 86.9% hit rate and 81.1% injection success rate against semantic caches in response hijacking attacks (Section 5, Table 1).", "file": "pages/claim-1/page.md", "children": [] }, { "slug": "claim-2", "title": "CacheAttack-2, a surrogate-assisted variant requiring no direct access to the target cache, achieves 83.1% hit rate and 77.1% injection success rate (Section 5, Table 1).", "file": "pages/claim-2/page.md", "children": [] }, { "slug": "claim-3", "title": "Semantic caching exhibits a fundamental trade-off between cache locality (performance) and collision resistance (security), formalized by modeling cache keys as fuzzy hashes (Section 3).", "file": "pages/claim-3/page.md", "children": [] }, { "slug": "claim-4", "title": "Cross-embedding-model transferability of the attack ranges from 49.8% to 86.9% hit rate depending on architectural similarity between source and target embedding models, versus over 92% hit rate in the in-model setting (Section 5, Table 3).", "file": "pages/claim-4/page.md", "children": [] }, { "slug": "claim-5", "title": "Key salting reduces attack hit rate by up to 21.0 percentage points, while per-user cache isolation eliminates cross-user attacks entirely but reduces cache efficiency (Section 7, Table 4).", "file": "pages/claim-5/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] } }