{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:D325P45JUGMNU344IJCXDLUB7W","short_pith_number":"pith:D325P45J","schema_version":"1.0","canonical_sha256":"1ef5d7f3a9a198da6f9c424571ae81fd872d39492008878b990e64f46d6c4947","source":{"kind":"arxiv","id":"2402.07039","version":3},"attestation_state":"computed","paper":{"title":"Coordinated Flaw Disclosure for AI: Beyond Security Vulnerabilities","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CY"],"primary_cat":"cs.AI","authors_text":"Avijit Ghosh, Lucie-Aim\\'ee Kaffee, Sven Cattell","submitted_at":"2024-02-10T20:39:04Z","abstract_excerpt":"Harm reporting in Artificial Intelligence (AI) currently lacks a structured process for disclosing and addressing algorithmic flaws, relying largely on an ad-hoc approach. This contrasts sharply with the well-established Coordinated Vulnerability Disclosure (CVD) ecosystem in software security. While global efforts to establish frameworks for AI transparency and collaboration are underway, the unique challenges presented by machine learning (ML) models demand a specialized approach. To address this gap, we propose implementing a Coordinated Flaw Disclosure (CFD) framework tailored to the compl"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2402.07039","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-02-10T20:39:04Z","cross_cats_sorted":["cs.CR","cs.CY"],"title_canon_sha256":"21de5eb7d18b54a30a0e0134583ec689bb91bfb982dc7663cf69369d08774394","abstract_canon_sha256":"11ff535114b96aba71dc9b29e4b5a81c88837c34dac0582028c8a325cfec69cc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:48:41.173022Z","signature_b64":"k/1OYBLeYtU6fQSyKBjN+ZM8zBS3W4H7sgzq5drF5vyNIL8FcGEzq+BJ+8+IY2Twyil0E5j8XWKUeEXgMhWnAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ef5d7f3a9a198da6f9c424571ae81fd872d39492008878b990e64f46d6c4947","last_reissued_at":"2026-07-05T08:48:41.172601Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:48:41.172601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Coordinated Flaw Disclosure for AI: Beyond Security Vulnerabilities","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CY"],"primary_cat":"cs.AI","authors_text":"Avijit Ghosh, Lucie-Aim\\'ee Kaffee, Sven Cattell","submitted_at":"2024-02-10T20:39:04Z","abstract_excerpt":"Harm reporting in Artificial Intelligence (AI) currently lacks a structured process for disclosing and addressing algorithmic flaws, relying largely on an ad-hoc approach. This contrasts sharply with the well-established Coordinated Vulnerability Disclosure (CVD) ecosystem in software security. While global efforts to establish frameworks for AI transparency and collaboration are underway, the unique challenges presented by machine learning (ML) models demand a specialized approach. To address this gap, we propose implementing a Coordinated Flaw Disclosure (CFD) framework tailored to the compl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07039","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2402.07039/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2402.07039","created_at":"2026-07-05T08:48:41.172658+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.07039v3","created_at":"2026-07-05T08:48:41.172658+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07039","created_at":"2026-07-05T08:48:41.172658+00:00"},{"alias_kind":"pith_short_12","alias_value":"D325P45JUGMN","created_at":"2026-07-05T08:48:41.172658+00:00"},{"alias_kind":"pith_short_16","alias_value":"D325P45JUGMNU344","created_at":"2026-07-05T08:48:41.172658+00:00"},{"alias_kind":"pith_short_8","alias_value":"D325P45J","created_at":"2026-07-05T08:48:41.172658+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W","json":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W.json","graph_json":"https://pith.science/api/pith-number/D325P45JUGMNU344IJCXDLUB7W/graph.json","events_json":"https://pith.science/api/pith-number/D325P45JUGMNU344IJCXDLUB7W/events.json","paper":"https://pith.science/paper/D325P45J"},"agent_actions":{"view_html":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W","download_json":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W.json","view_paper":"https://pith.science/paper/D325P45J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.07039&json=true","fetch_graph":"https://pith.science/api/pith-number/D325P45JUGMNU344IJCXDLUB7W/graph.json","fetch_events":"https://pith.science/api/pith-number/D325P45JUGMNU344IJCXDLUB7W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W/action/storage_attestation","attest_author":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W/action/author_attestation","sign_citation":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W/action/citation_signature","submit_replication":"https://pith.science/pith/D325P45JUGMNU344IJCXDLUB7W/action/replication_record"}},"created_at":"2026-07-05T08:48:41.172658+00:00","updated_at":"2026-07-05T08:48:41.172658+00:00"}