{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YIB3VNHIZM7QCNUYVWDGPSXWNY","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"40747b4978c30a6186299b680c5c7077ebd9941424e95b71d0aff74139f54214","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-21T11:01:11Z","title_canon_sha256":"fa5c1ab5772b12064b5faf284c209b8d43abe05796fa709be7fbe5e6a71b2164"},"schema_version":"1.0","source":{"id":"2505.17107","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17107","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17107v1","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17107","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_12","alias_value":"YIB3VNHIZM7Q","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_16","alias_value":"YIB3VNHIZM7QCNUY","created_at":"2026-07-05T11:07:47Z"},{"alias_kind":"pith_short_8","alias_value":"YIB3VNHI","created_at":"2026-07-05T11:07:47Z"}],"graph_snapshots":[{"event_id":"sha256:2284883a5de8d56de2ed966b071f1a5ebf57bb5891fc10bbdcfadf5fbc26b849","target":"graph","created_at":"2026-07-05T11:07:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2505.17107/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Model (LLM) agents can automate cybersecurity tasks and can adapt to the evolving cybersecurity landscape without re-engineering. While LLM agents have demonstrated cybersecurity capabilities on Capture-The-Flag (CTF) competitions, they have two key limitations: accessing latest cybersecurity expertise beyond training data, and integrating new knowledge into complex task planning. Knowledge-based approaches that incorporate technical understanding into the task-solving automation can tackle these limitations. We present CRAKEN, a knowledge-based LLM agent framework that improves","authors_text":"Brendan Dolan-Gavitt, Farshad Khorrami, Haoran Xi, Kimberly Milner, Meet Udeshi, Minghao Shao, Muhammad Shafique, Nanda Rani, Prashanth Krishnamurthy, Ramesh Karri, Sandeep Kumar Shukla, Venkata Sai Charan Putrevu","cross_cats":["cs.AI","cs.LG","cs.MA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-21T11:01:11Z","title":"CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17107","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f81ea7a118d63610150ff1d4de6409f08e634c504732304bcb5e386280a41ac3","target":"record","created_at":"2026-07-05T11:07:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"40747b4978c30a6186299b680c5c7077ebd9941424e95b71d0aff74139f54214","cross_cats_sorted":["cs.AI","cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-21T11:01:11Z","title_canon_sha256":"fa5c1ab5772b12064b5faf284c209b8d43abe05796fa709be7fbe5e6a71b2164"},"schema_version":"1.0","source":{"id":"2505.17107","kind":"arxiv","version":1}},"canonical_sha256":"c203bab4e8cb3f013698ad8667caf66e1b73fbcfd739dd8232b833095f53df3d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c203bab4e8cb3f013698ad8667caf66e1b73fbcfd739dd8232b833095f53df3d","first_computed_at":"2026-07-05T11:07:47.186226Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:07:47.186226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RHWRTQvp701GJv2V3RpTTs4DT10ssksDjt8VeduN/e/X1HOZ0euISDfnnV0rUMjU2hwKfgMZoC+rLZCVcsOfBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:07:47.186726Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17107","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f81ea7a118d63610150ff1d4de6409f08e634c504732304bcb5e386280a41ac3","sha256:2284883a5de8d56de2ed966b071f1a5ebf57bb5891fc10bbdcfadf5fbc26b849"],"state_sha256":"49bdaede2ee270d8acf8dcecabef71566f02cc505ccdabac2fe2048a9358d578"}