{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:CZH234VY5PYLEG4ALQIG5RAUGC","short_pith_number":"pith:CZH234VY","schema_version":"1.0","canonical_sha256":"164fadf2b8ebf0b21b805c106ec41430ab944d7fccb2f0aa4d385f5284e42cf6","source":{"kind":"arxiv","id":"2512.03465","version":5},"attestation_state":"computed","paper":{"title":"Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits","license":"http://creativecommons.org/licenses/by/4.0/","headline":"TraceTarnish attack analysis identifies function-word frequencies, content-word distributions, and type-token ratio as reliable signals that text has been altered to mask its author.","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.CR","authors_text":"Robert Dilworth","submitted_at":"2025-12-03T05:39:40Z","abstract_excerpt":"In this study, we more rigorously evaluated our attack script $\\textit{TraceTarnish}$, which leverages adversarial stylometry principles to anonymize the authorship of text-based messages. To ensure the efficacy and utility of our attack, we sourced, processed, and analyzed Reddit comments -- comments that were later alchemized into $\\textit{TraceTarnish}$ data -- to gain valuable insights. The transformed $\\textit{TraceTarnish}$ data was then further augmented by $\\textit{StyloMetrix}$ to manufacture stylometric features -- features that were culled using the Information Gain criterion, leavi"},"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":true},"canonical_record":{"source":{"id":"2512.03465","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-12-03T05:39:40Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"fd82ca9c529949b5709658e391062fdd9a195879a96d2b732b4c6bc7ebb47308","abstract_canon_sha256":"6389c7b3143302b60099af3636ba08d93494f6ac7558b483e7a381e6ed151556"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:08:35.463425Z","signature_b64":"nfGQ1Z/b68j1jWmFwzkq3eczkPhtvXQVt3qfKXePCimyTsxvOJoRY2rl90I+qAmHBHMbR1RrBs64OgFkMtj+Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"164fadf2b8ebf0b21b805c106ec41430ab944d7fccb2f0aa4d385f5284e42cf6","last_reissued_at":"2026-06-09T02:08:35.462334Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:08:35.462334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits","license":"http://creativecommons.org/licenses/by/4.0/","headline":"TraceTarnish attack analysis identifies function-word frequencies, content-word distributions, and type-token ratio as reliable signals that text has been altered to mask its author.","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.CR","authors_text":"Robert Dilworth","submitted_at":"2025-12-03T05:39:40Z","abstract_excerpt":"In this study, we more rigorously evaluated our attack script $\\textit{TraceTarnish}$, which leverages adversarial stylometry principles to anonymize the authorship of text-based messages. To ensure the efficacy and utility of our attack, we sourced, processed, and analyzed Reddit comments -- comments that were later alchemized into $\\textit{TraceTarnish}$ data -- to gain valuable insights. The transformed $\\textit{TraceTarnish}$ data was then further augmented by $\\textit{StyloMetrix}$ to manufacture stylometric features -- features that were culled using the Information Gain criterion, leavi"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"The identified stylometric cues — function-word frequencies, content-word distributions, and the Type-Token Ratio — serve as reliable indicators of compromise (IoCs), revealing when a text has been deliberately altered to mask its true author.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the Information Gain-selected features remain useful for both attack enhancement and detection even when only the transformed text is available, and that the Reddit-derived dataset generalizes beyond the specific comments and transformations tested.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"TraceTarnish attack identifies stylometric features like function-word frequencies and type-token ratio that both strengthen authorship anonymization and serve as indicators of compromise when pre- and post-transformation texts can be compared.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"TraceTarnish attack analysis identifies function-word frequencies, content-word distributions, and type-token ratio as reliable signals that text has been altered to mask its author.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"96b8a4d0a28b9206485595b3f786dcfe2d52e3c15297bfe4ff6e0370f0ecc472"},"source":{"id":"2512.03465","kind":"arxiv","version":5},"verdict":{"id":"6318afe4-14f8-4627-95f7-ca5fb81ff400","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-17T02:54:59.777440Z","strongest_claim":"The identified stylometric cues — function-word frequencies, content-word distributions, and the Type-Token Ratio — serve as reliable indicators of compromise (IoCs), revealing when a text has been deliberately altered to mask its true author.","one_line_summary":"TraceTarnish attack identifies stylometric features like function-word frequencies and type-token ratio that both strengthen authorship anonymization and serve as indicators of compromise when pre- and post-transformation texts can be compared.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the Information Gain-selected features remain useful for both attack enhancement and detection even when only the transformed text is available, and that the Reddit-derived dataset generalizes beyond the specific comments and transformations tested.","pith_extraction_headline":"TraceTarnish attack analysis identifies function-word frequencies, content-word distributions, and type-token ratio as reliable signals that text has been altered to mask its author."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2512.03465/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":1,"snapshot_sha256":"421dbda32a0fcb02d8155b446011a5b074e2b416f002331ed59b8b6acf949147"},"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":"2512.03465","created_at":"2026-06-09T02:08:35.462485+00:00"},{"alias_kind":"arxiv_version","alias_value":"2512.03465v5","created_at":"2026-06-09T02:08:35.462485+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.03465","created_at":"2026-06-09T02:08:35.462485+00:00"},{"alias_kind":"pith_short_12","alias_value":"CZH234VY5PYL","created_at":"2026-06-09T02:08:35.462485+00:00"},{"alias_kind":"pith_short_16","alias_value":"CZH234VY5PYLEG4A","created_at":"2026-06-09T02:08:35.462485+00:00"},{"alias_kind":"pith_short_8","alias_value":"CZH234VY","created_at":"2026-06-09T02:08:35.462485+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":2,"sample":[{"citing_arxiv_id":"2601.09056","citing_title":"StegoStylo: Squelching Stylometric Scrutiny through Steganographic Stitching","ref_index":9,"is_internal_anchor":true},{"citing_arxiv_id":"2604.10271","citing_title":"Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution","ref_index":9,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":1,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC","json":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC.json","graph_json":"https://pith.science/api/pith-number/CZH234VY5PYLEG4ALQIG5RAUGC/graph.json","events_json":"https://pith.science/api/pith-number/CZH234VY5PYLEG4ALQIG5RAUGC/events.json","paper":"https://pith.science/paper/CZH234VY"},"agent_actions":{"view_html":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC","download_json":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC.json","view_paper":"https://pith.science/paper/CZH234VY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2512.03465&json=true","fetch_graph":"https://pith.science/api/pith-number/CZH234VY5PYLEG4ALQIG5RAUGC/graph.json","fetch_events":"https://pith.science/api/pith-number/CZH234VY5PYLEG4ALQIG5RAUGC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC/action/storage_attestation","attest_author":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC/action/author_attestation","sign_citation":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC/action/citation_signature","submit_replication":"https://pith.science/pith/CZH234VY5PYLEG4ALQIG5RAUGC/action/replication_record"}},"created_at":"2026-06-09T02:08:35.462485+00:00","updated_at":"2026-06-09T02:08:35.462485+00:00"}