{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:EH77KEMXYEG77OK4WNFV3KH4LB","short_pith_number":"pith:EH77KEMX","schema_version":"1.0","canonical_sha256":"21fff51197c10dffb95cb34b5da8fc58737800d74cd983accb624b9374004896","source":{"kind":"arxiv","id":"2410.02693","version":2},"attestation_state":"computed","paper":{"title":"Discovering Spoofing Attempts on Language Model Watermarks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Martin Vechev, Nikola Jovanovi\\'c, Robin Staab, Thibaud Gloaguen","submitted_at":"2024-10-03T17:18:37Z","abstract_excerpt":"LLM watermarks stand out as a promising way to attribute ownership of LLM-generated text. One threat to watermark credibility comes from spoofing attacks, where an unauthorized third party forges the watermark, enabling it to falsely attribute arbitrary texts to a particular LLM. Despite recent work demonstrating that state-of-the-art schemes are, in fact, vulnerable to spoofing, no prior work has focused on post-hoc methods to discover spoofing attempts. In this work, we for the first time propose a reliable statistical method to distinguish spoofed from genuinely watermarked text, suggesting"},"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":"2410.02693","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-10-03T17:18:37Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"8e324cc910f5013d64d06cc86aa9614aaa917126f34951b5313a763f81ec857d","abstract_canon_sha256":"cf1e4b304653f8bc21e52333674dade53527f6b7d561ed2874ebed6204924df4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:07:04.921339Z","signature_b64":"90rMMVKTOUznk+R0Cc0dQ5sKUc1kao3wuiMkr7lSccir9rJz1R7YDD5G3sLPAuSib1Wk+LKqso9XhG4Rz5FrBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"21fff51197c10dffb95cb34b5da8fc58737800d74cd983accb624b9374004896","last_reissued_at":"2026-07-05T11:07:04.920722Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:07:04.920722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Discovering Spoofing Attempts on Language Model Watermarks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Martin Vechev, Nikola Jovanovi\\'c, Robin Staab, Thibaud Gloaguen","submitted_at":"2024-10-03T17:18:37Z","abstract_excerpt":"LLM watermarks stand out as a promising way to attribute ownership of LLM-generated text. One threat to watermark credibility comes from spoofing attacks, where an unauthorized third party forges the watermark, enabling it to falsely attribute arbitrary texts to a particular LLM. Despite recent work demonstrating that state-of-the-art schemes are, in fact, vulnerable to spoofing, no prior work has focused on post-hoc methods to discover spoofing attempts. In this work, we for the first time propose a reliable statistical method to distinguish spoofed from genuinely watermarked text, suggesting"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02693","kind":"arxiv","version":2},"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/2410.02693/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":"2410.02693","created_at":"2026-07-05T11:07:04.920802+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.02693v2","created_at":"2026-07-05T11:07:04.920802+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02693","created_at":"2026-07-05T11:07:04.920802+00:00"},{"alias_kind":"pith_short_12","alias_value":"EH77KEMXYEG7","created_at":"2026-07-05T11:07:04.920802+00:00"},{"alias_kind":"pith_short_16","alias_value":"EH77KEMXYEG77OK4","created_at":"2026-07-05T11:07:04.920802+00:00"},{"alias_kind":"pith_short_8","alias_value":"EH77KEMX","created_at":"2026-07-05T11:07:04.920802+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":4,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2507.07871","citing_title":"Mitigating Watermark Forgery in Generative Models via Randomized Key Selection","ref_index":13,"is_internal_anchor":false},{"citing_arxiv_id":"2605.13095","citing_title":"Watermarking Should Be Treated as a Monitoring Primitive","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2605.13095","citing_title":"Watermarking Should Be Treated as a Monitoring Primitive","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2604.11546","citing_title":"RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience","ref_index":16,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB","json":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB.json","graph_json":"https://pith.science/api/pith-number/EH77KEMXYEG77OK4WNFV3KH4LB/graph.json","events_json":"https://pith.science/api/pith-number/EH77KEMXYEG77OK4WNFV3KH4LB/events.json","paper":"https://pith.science/paper/EH77KEMX"},"agent_actions":{"view_html":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB","download_json":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB.json","view_paper":"https://pith.science/paper/EH77KEMX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.02693&json=true","fetch_graph":"https://pith.science/api/pith-number/EH77KEMXYEG77OK4WNFV3KH4LB/graph.json","fetch_events":"https://pith.science/api/pith-number/EH77KEMXYEG77OK4WNFV3KH4LB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB/action/storage_attestation","attest_author":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB/action/author_attestation","sign_citation":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB/action/citation_signature","submit_replication":"https://pith.science/pith/EH77KEMXYEG77OK4WNFV3KH4LB/action/replication_record"}},"created_at":"2026-07-05T11:07:04.920802+00:00","updated_at":"2026-07-05T11:07:04.920802+00:00"}