{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5YGZWQCDSJZBINVOJAU75OOI3K","short_pith_number":"pith:5YGZWQCD","canonical_record":{"source":{"id":"2407.02596","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-02T18:33:49Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"2980afdd54392d1980544585d35427581ba9f4104e3ecde22a01a329b6b7ad75","abstract_canon_sha256":"cf259caf2c6539db90da126bc991be805d8fedb9b5fa2c1987fe90c2bcf7e1c8"},"schema_version":"1.0"},"canonical_sha256":"ee0d9b404392721436ae4829feb9c8dab70afa6ad2a27659fd55cdb57f56a337","source":{"kind":"arxiv","id":"2407.02596","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.02596","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"arxiv_version","alias_value":"2407.02596v3","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.02596","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_12","alias_value":"5YGZWQCDSJZB","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_16","alias_value":"5YGZWQCDSJZBINVO","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_8","alias_value":"5YGZWQCD","created_at":"2026-07-05T11:50:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5YGZWQCDSJZBINVOJAU75OOI3K","target":"record","payload":{"canonical_record":{"source":{"id":"2407.02596","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-02T18:33:49Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"2980afdd54392d1980544585d35427581ba9f4104e3ecde22a01a329b6b7ad75","abstract_canon_sha256":"cf259caf2c6539db90da126bc991be805d8fedb9b5fa2c1987fe90c2bcf7e1c8"},"schema_version":"1.0"},"canonical_sha256":"ee0d9b404392721436ae4829feb9c8dab70afa6ad2a27659fd55cdb57f56a337","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:27.397041Z","signature_b64":"5g19zm7audOAISqB6RhrdXu1ryjCesqVa4vB0jpLoWo0T+b5MI6gAbckPXTii3IRAv+Od9rOzt0051uHr/3wDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee0d9b404392721436ae4829feb9c8dab70afa6ad2a27659fd55cdb57f56a337","last_reissued_at":"2026-07-05T11:50:27.396513Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:27.396513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.02596","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:50:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yr79pr9qouawM7doWETXJEnVPNAJJNwXX9noydi1j1+fLB7GwEs+MO9XWfpeblcZOsx+oclcjf5hgkwxxJw/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T12:26:38.838167Z"},"content_sha256":"bdfa6849a7674ca13a083e88ed5e87255aaf25f383535cb1cae2662239225aab","schema_version":"1.0","event_id":"sha256:bdfa6849a7674ca13a083e88ed5e87255aaf25f383535cb1cae2662239225aab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5YGZWQCDSJZBINVOJAU75OOI3K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards More Realistic Extraction Attacks: An Adversarial Perspective","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CR","authors_text":"Golnoosh Farnadi, Prakhar Ganesh, Yash More","submitted_at":"2024-07-02T18:33:49Z","abstract_excerpt":"Language models are prone to memorizing their training data, making them vulnerable to extraction attacks. While existing research often examines isolated setups, such as a single model or a fixed prompt, real-world adversaries have a considerably larger attack surface due to access to models across various sizes and checkpoints, and repeated prompting. In this paper, we revisit extraction attacks from an adversarial perspective -- with multi-faceted access to the underlying data. We find significant churn in extraction trends, i.e., even unintuitive changes to the prompt, or targeting smaller"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.02596","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/2407.02596/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:50:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1Wh2k3RaQBPiYJm1Ynue1WU2qbO0Z7yH0DGEnbHdkPj8HWK2uLdgm28x/iimNVc0Ktlx0Mh202sr2vUYAMthDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T12:26:38.839365Z"},"content_sha256":"b8efe58973ce4f6894dc7087de05b682800714eef7b6a4ca48d3fe9dccd155bc","schema_version":"1.0","event_id":"sha256:b8efe58973ce4f6894dc7087de05b682800714eef7b6a4ca48d3fe9dccd155bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5YGZWQCDSJZBINVOJAU75OOI3K/bundle.json","state_url":"https://pith.science/pith/5YGZWQCDSJZBINVOJAU75OOI3K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5YGZWQCDSJZBINVOJAU75OOI3K/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T12:26:38Z","links":{"resolver":"https://pith.science/pith/5YGZWQCDSJZBINVOJAU75OOI3K","bundle":"https://pith.science/pith/5YGZWQCDSJZBINVOJAU75OOI3K/bundle.json","state":"https://pith.science/pith/5YGZWQCDSJZBINVOJAU75OOI3K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5YGZWQCDSJZBINVOJAU75OOI3K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5YGZWQCDSJZBINVOJAU75OOI3K","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":"cf259caf2c6539db90da126bc991be805d8fedb9b5fa2c1987fe90c2bcf7e1c8","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-02T18:33:49Z","title_canon_sha256":"2980afdd54392d1980544585d35427581ba9f4104e3ecde22a01a329b6b7ad75"},"schema_version":"1.0","source":{"id":"2407.02596","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.02596","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"arxiv_version","alias_value":"2407.02596v3","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.02596","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_12","alias_value":"5YGZWQCDSJZB","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_16","alias_value":"5YGZWQCDSJZBINVO","created_at":"2026-07-05T11:50:27Z"},{"alias_kind":"pith_short_8","alias_value":"5YGZWQCD","created_at":"2026-07-05T11:50:27Z"}],"graph_snapshots":[{"event_id":"sha256:b8efe58973ce4f6894dc7087de05b682800714eef7b6a4ca48d3fe9dccd155bc","target":"graph","created_at":"2026-07-05T11:50:27Z","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/2407.02596/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Language models are prone to memorizing their training data, making them vulnerable to extraction attacks. While existing research often examines isolated setups, such as a single model or a fixed prompt, real-world adversaries have a considerably larger attack surface due to access to models across various sizes and checkpoints, and repeated prompting. In this paper, we revisit extraction attacks from an adversarial perspective -- with multi-faceted access to the underlying data. We find significant churn in extraction trends, i.e., even unintuitive changes to the prompt, or targeting smaller","authors_text":"Golnoosh Farnadi, Prakhar Ganesh, Yash More","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-02T18:33:49Z","title":"Towards More Realistic Extraction Attacks: An Adversarial Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.02596","kind":"arxiv","version":3},"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:bdfa6849a7674ca13a083e88ed5e87255aaf25f383535cb1cae2662239225aab","target":"record","created_at":"2026-07-05T11:50:27Z","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":"cf259caf2c6539db90da126bc991be805d8fedb9b5fa2c1987fe90c2bcf7e1c8","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-07-02T18:33:49Z","title_canon_sha256":"2980afdd54392d1980544585d35427581ba9f4104e3ecde22a01a329b6b7ad75"},"schema_version":"1.0","source":{"id":"2407.02596","kind":"arxiv","version":3}},"canonical_sha256":"ee0d9b404392721436ae4829feb9c8dab70afa6ad2a27659fd55cdb57f56a337","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee0d9b404392721436ae4829feb9c8dab70afa6ad2a27659fd55cdb57f56a337","first_computed_at":"2026-07-05T11:50:27.396513Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:27.396513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5g19zm7audOAISqB6RhrdXu1ryjCesqVa4vB0jpLoWo0T+b5MI6gAbckPXTii3IRAv+Od9rOzt0051uHr/3wDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:27.397041Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.02596","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bdfa6849a7674ca13a083e88ed5e87255aaf25f383535cb1cae2662239225aab","sha256:b8efe58973ce4f6894dc7087de05b682800714eef7b6a4ca48d3fe9dccd155bc"],"state_sha256":"a5498e48f32d85468edbb1ff6a7631556257654d6c675f29ba2ce8173e20757a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N/F7/vl7qVMDeDYCNBlHiTO4qXasnGMtoPyX62u36pPWHy/Oyrfb/ru/2EY3cLiP+s7D3LtMqKS1nTnOiJ2EBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T12:26:38.846790Z","bundle_sha256":"98809410dcd4ac91482ae2e6e2d06c1cad5ce8de1162613c4966e236c51b77e5"}}