{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:N7W2C7JY2AVQN4U55LFAFIYYDP","short_pith_number":"pith:N7W2C7JY","canonical_record":{"source":{"id":"2406.20053","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-28T17:05:46Z","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"title_canon_sha256":"fce39fc5ff1df767363bbd4f437064d693f0e71c1bae755a2bf3b4777e045f80","abstract_canon_sha256":"cc38e5c2edd8b9b9cb1a78d797b37ca59e850ecca91f64d5ba0bfd8e1de4f4f6"},"schema_version":"1.0"},"canonical_sha256":"6feda17d38d02b06f29deaca02a3181bd907c330a0a3ad193a771ef97d041f23","source":{"kind":"arxiv","id":"2406.20053","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.20053","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"arxiv_version","alias_value":"2406.20053v1","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.20053","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_12","alias_value":"N7W2C7JY2AVQ","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_16","alias_value":"N7W2C7JY2AVQN4U5","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_8","alias_value":"N7W2C7JY","created_at":"2026-07-05T08:37:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:N7W2C7JY2AVQN4U55LFAFIYYDP","target":"record","payload":{"canonical_record":{"source":{"id":"2406.20053","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-28T17:05:46Z","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"title_canon_sha256":"fce39fc5ff1df767363bbd4f437064d693f0e71c1bae755a2bf3b4777e045f80","abstract_canon_sha256":"cc38e5c2edd8b9b9cb1a78d797b37ca59e850ecca91f64d5ba0bfd8e1de4f4f6"},"schema_version":"1.0"},"canonical_sha256":"6feda17d38d02b06f29deaca02a3181bd907c330a0a3ad193a771ef97d041f23","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:37:58.511688Z","signature_b64":"vrcWOsyRt9JK5EmETrd+/VZW6vxMUJJklOWD7iJdGwkAsNeQk2ue4Tr/Lj+x7NDILaHHmVZvCNZVSJ6NcYDkDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6feda17d38d02b06f29deaca02a3181bd907c330a0a3ad193a771ef97d041f23","last_reissued_at":"2026-07-05T08:37:58.511200Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:37:58.511200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.20053","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:37:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ry2+b8YKmfJ3qlNjORPgUNpjNQL/H+wXS0BzkeswKPo3JK71HwDz7z+AycFfL5n6C3TKITY4urgPjcpy3tilDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:42:17.533368Z"},"content_sha256":"905ce9c0cf79365e496fa97ace269899b884bf685c6e6c3bdcd2b6976b2f8c9a","schema_version":"1.0","event_id":"sha256:905ce9c0cf79365e496fa97ace269899b884bf685c6e6c3bdcd2b6976b2f8c9a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:N7W2C7JY2AVQN4U55LFAFIYYDP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.LG"],"primary_cat":"cs.CR","authors_text":"Alexander Wei, Danny Halawi, Eric Wallace, Jacob Steinhardt, Nika Haghtalab, Tony T. Wang","submitted_at":"2024-06-28T17:05:46Z","abstract_excerpt":"Black-box finetuning is an emerging interface for adapting state-of-the-art language models to user needs. However, such access may also let malicious actors undermine model safety. To demonstrate the challenge of defending finetuning interfaces, we introduce covert malicious finetuning, a method to compromise model safety via finetuning while evading detection. Our method constructs a malicious dataset where every individual datapoint appears innocuous, but finetuning on the dataset teaches the model to respond to encoded harmful requests with encoded harmful responses. Applied to GPT-4, our "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.20053","kind":"arxiv","version":1},"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/2406.20053/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":"2026-07-05T08:37:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ztSDMlxo0IHBuyAAptfsuOQIgJpRDkBRyPQSEPidUCW1wOTQtzJEG0Ra29vi/R8jD2yuN/bqbfdNVB/IUoqcBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:42:17.534309Z"},"content_sha256":"36a7236d430e7c45bbac0a7495bf25e1a20eac3a3c4e49016e61cfa548d1737f","schema_version":"1.0","event_id":"sha256:36a7236d430e7c45bbac0a7495bf25e1a20eac3a3c4e49016e61cfa548d1737f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/bundle.json","state_url":"https://pith.science/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/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":"2026-08-07T22:42:17Z","links":{"resolver":"https://pith.science/pith/N7W2C7JY2AVQN4U55LFAFIYYDP","bundle":"https://pith.science/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/bundle.json","state":"https://pith.science/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N7W2C7JY2AVQN4U55LFAFIYYDP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:N7W2C7JY2AVQN4U55LFAFIYYDP","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":"cc38e5c2edd8b9b9cb1a78d797b37ca59e850ecca91f64d5ba0bfd8e1de4f4f6","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-28T17:05:46Z","title_canon_sha256":"fce39fc5ff1df767363bbd4f437064d693f0e71c1bae755a2bf3b4777e045f80"},"schema_version":"1.0","source":{"id":"2406.20053","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.20053","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"arxiv_version","alias_value":"2406.20053v1","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.20053","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_12","alias_value":"N7W2C7JY2AVQ","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_16","alias_value":"N7W2C7JY2AVQN4U5","created_at":"2026-07-05T08:37:58Z"},{"alias_kind":"pith_short_8","alias_value":"N7W2C7JY","created_at":"2026-07-05T08:37:58Z"}],"graph_snapshots":[{"event_id":"sha256:36a7236d430e7c45bbac0a7495bf25e1a20eac3a3c4e49016e61cfa548d1737f","target":"graph","created_at":"2026-07-05T08:37:58Z","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/2406.20053/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Black-box finetuning is an emerging interface for adapting state-of-the-art language models to user needs. However, such access may also let malicious actors undermine model safety. To demonstrate the challenge of defending finetuning interfaces, we introduce covert malicious finetuning, a method to compromise model safety via finetuning while evading detection. Our method constructs a malicious dataset where every individual datapoint appears innocuous, but finetuning on the dataset teaches the model to respond to encoded harmful requests with encoded harmful responses. Applied to GPT-4, our ","authors_text":"Alexander Wei, Danny Halawi, Eric Wallace, Jacob Steinhardt, Nika Haghtalab, Tony T. Wang","cross_cats":["cs.AI","cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-28T17:05:46Z","title":"Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.20053","kind":"arxiv","version":1},"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":"sha256:905ce9c0cf79365e496fa97ace269899b884bf685c6e6c3bdcd2b6976b2f8c9a","target":"record","created_at":"2026-07-05T08:37:58Z","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":"cc38e5c2edd8b9b9cb1a78d797b37ca59e850ecca91f64d5ba0bfd8e1de4f4f6","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-28T17:05:46Z","title_canon_sha256":"fce39fc5ff1df767363bbd4f437064d693f0e71c1bae755a2bf3b4777e045f80"},"schema_version":"1.0","source":{"id":"2406.20053","kind":"arxiv","version":1}},"canonical_sha256":"6feda17d38d02b06f29deaca02a3181bd907c330a0a3ad193a771ef97d041f23","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6feda17d38d02b06f29deaca02a3181bd907c330a0a3ad193a771ef97d041f23","first_computed_at":"2026-07-05T08:37:58.511200Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:37:58.511200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vrcWOsyRt9JK5EmETrd+/VZW6vxMUJJklOWD7iJdGwkAsNeQk2ue4Tr/Lj+x7NDILaHHmVZvCNZVSJ6NcYDkDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:37:58.511688Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.20053","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:905ce9c0cf79365e496fa97ace269899b884bf685c6e6c3bdcd2b6976b2f8c9a","sha256:36a7236d430e7c45bbac0a7495bf25e1a20eac3a3c4e49016e61cfa548d1737f"],"state_sha256":"30a8272b1b9194c5d62f2d851ad5cf3e38450fbb8ce58ff0c9db516b9ecc54f4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jH0CdtHuKW9frivZy7qMMGpVrBwcxnAegKlaiSzqZfgzi9PeF0Vnvro8g1BPGYtHpotGvrBLM2Ut/Cii0ZqEDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T22:42:17.538517Z","bundle_sha256":"014095cb83e2d5881bdee1f923d461c632430aa8174f8d1cdcb51fe0dea36599"}}