{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:NKWGUKXG6VK7ZK2W3QW5KYSKCG","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":"4b15e2a7e333ef5f31ccf6a847849767d81876d9fde1254ea74f884e2ad1bed7","cross_cats_sorted":["cs.CL","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-17T19:44:09Z","title_canon_sha256":"33cc0c8821bedd150c3234eb5fa367902b7937c86005135558d49c63d363149c"},"schema_version":"1.0","source":{"id":"2101.06761","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.06761","created_at":"2026-07-05T02:18:20Z"},{"alias_kind":"arxiv_version","alias_value":"2101.06761v2","created_at":"2026-07-05T02:18:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.06761","created_at":"2026-07-05T02:18:20Z"},{"alias_kind":"pith_short_12","alias_value":"NKWGUKXG6VK7","created_at":"2026-07-05T02:18:20Z"},{"alias_kind":"pith_short_16","alias_value":"NKWGUKXG6VK7ZK2W","created_at":"2026-07-05T02:18:20Z"},{"alias_kind":"pith_short_8","alias_value":"NKWGUKXG","created_at":"2026-07-05T02:18:20Z"}],"graph_snapshots":[{"event_id":"sha256:a95969be168da2008248845b5b91e9a85702d8997b0ca1b4f5c465f18408ffcb","target":"graph","created_at":"2026-07-05T02:18:20Z","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/2101.06761/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Log-based cyber threat hunting has emerged as an important solution to counter sophisticated cyber attacks. However, existing approaches require non-trivial efforts of manual query construction and have overlooked the rich external knowledge about threat behaviors provided by open-source Cyber Threat Intelligence (OSCTI). To bridge the gap, we build ThreatRaptor, a system that facilitates cyber threat hunting in computer systems using OSCTI. Built upon mature system auditing frameworks, ThreatRaptor provides (1) an unsupervised, light-weight, and accurate NLP pipeline that extracts structured ","authors_text":"Dawn Song, Fei Shao, Fengyuan Xu, Haoyuan Liu, Peng Gao, Prateek Mittal, Sanjeev R. Kulkarni, Xiaoyuan Liu, Xusheng Xiao, Zheng Qin","cross_cats":["cs.CL","cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-17T19:44:09Z","title":"A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.06761","kind":"arxiv","version":2},"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:e7b9e3076e4e9474805fd23ed89c34b6d10d8da076741dd0008183a79f502d10","target":"record","created_at":"2026-07-05T02:18:20Z","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":"4b15e2a7e333ef5f31ccf6a847849767d81876d9fde1254ea74f884e2ad1bed7","cross_cats_sorted":["cs.CL","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-17T19:44:09Z","title_canon_sha256":"33cc0c8821bedd150c3234eb5fa367902b7937c86005135558d49c63d363149c"},"schema_version":"1.0","source":{"id":"2101.06761","kind":"arxiv","version":2}},"canonical_sha256":"6aac6a2ae6f555fcab56dc2dd5624a1199b6caa294ce9822ef153ec0b789b383","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6aac6a2ae6f555fcab56dc2dd5624a1199b6caa294ce9822ef153ec0b789b383","first_computed_at":"2026-07-05T02:18:20.075543Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:18:20.075543Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fB1JVOqLZgww2EdIT/2feYuym5KiXxkIpJWnUVUPNeGe68TrM4llyrKa8ReE/fIR4ESzkB3l9WZ/uG4CN01FCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:18:20.075991Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.06761","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e7b9e3076e4e9474805fd23ed89c34b6d10d8da076741dd0008183a79f502d10","sha256:a95969be168da2008248845b5b91e9a85702d8997b0ca1b4f5c465f18408ffcb"],"state_sha256":"e62c29b40db0fe77553b6dbd990392b1fec6ba5d6b8a23c100194295e2c94646"}