{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PSNV42EO6D2F23BCYKD43SZJQP","short_pith_number":"pith:PSNV42EO","canonical_record":{"source":{"id":"2406.19234","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-27T14:58:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"24f0c40ddc6ca307379ce9f86293ad2c7ea3561bec170b2d61030b847350caf8","abstract_canon_sha256":"20715e9d200d92187c5266043a6952766c7a79181e986b029354f02c69e61c2d"},"schema_version":"1.0"},"canonical_sha256":"7c9b5e688ef0f45d6c22c287cdcb2983d5db6e4bdcf415f069f42cd4185f2c96","source":{"kind":"arxiv","id":"2406.19234","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19234","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19234v2","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19234","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_12","alias_value":"PSNV42EO6D2F","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_16","alias_value":"PSNV42EO6D2F23BC","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_8","alias_value":"PSNV42EO","created_at":"2026-07-05T09:12:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PSNV42EO6D2F23BCYKD43SZJQP","target":"record","payload":{"canonical_record":{"source":{"id":"2406.19234","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-27T14:58:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"24f0c40ddc6ca307379ce9f86293ad2c7ea3561bec170b2d61030b847350caf8","abstract_canon_sha256":"20715e9d200d92187c5266043a6952766c7a79181e986b029354f02c69e61c2d"},"schema_version":"1.0"},"canonical_sha256":"7c9b5e688ef0f45d6c22c287cdcb2983d5db6e4bdcf415f069f42cd4185f2c96","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:12:07.743150Z","signature_b64":"r3KRL7wiZ3fTnX4hYWHcOFPH0YWRdL85mM9SiqOgSAkBCFUpmf74qJnDKJWsqTCUndvlwdu62o5xtdcE7avHCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c9b5e688ef0f45d6c22c287cdcb2983d5db6e4bdcf415f069f42cd4185f2c96","last_reissued_at":"2026-07-05T09:12:07.742664Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:12:07.742664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.19234","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:12:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EZy0Xo+JmZMjenA9mNCNKHjwUd6U1r+k+IGSvTJxd1hwxJJnvUs5h3gaq0Ep2mWwve8YvH2QMU3ZtZ/kqBtADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:57:45.144531Z"},"content_sha256":"e0bdc2768ba6d0fa24871b4bcf2e186126ebb77b4d29986b6df6a77489d1f668","schema_version":"1.0","event_id":"sha256:e0bdc2768ba6d0fa24871b4bcf2e186126ebb77b4d29986b6df6a77489d1f668"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PSNV42EO6D2F23BCYKD43SZJQP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Chen Wang, Gaoyang Liu, Yang Yang, Yuying Li","submitted_at":"2024-06-27T14:58:38Z","abstract_excerpt":"Retrieval-Augmented Generation (RAG) is a state-of-the-art technique that mitigates issues such as hallucinations and knowledge staleness in Large Language Models (LLMs) by retrieving relevant knowledge from an external database to assist in content generation. Existing research has demonstrated potential privacy risks associated with the LLMs of RAG. However, the privacy risks posed by the integration of an external database, which often contains sensitive data such as medical records or personal identities, have remained largely unexplored. In this paper, we aim to bridge this gap by focusin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19234","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/2406.19234/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":"2026-07-05T09:12:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zzL2sUOHROW2pcDV6vJmfAGIUm+evA8BDaLXglI/5T1Zqd4l31ogLWJMTL6qSW5PmF7KfxvMGcM3l+M/N/olDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:57:45.145534Z"},"content_sha256":"8dbafe4c2eb06b2b17e62880b3ff1b9ad40d973a95f2af8c53f50cd34a282d67","schema_version":"1.0","event_id":"sha256:8dbafe4c2eb06b2b17e62880b3ff1b9ad40d973a95f2af8c53f50cd34a282d67"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PSNV42EO6D2F23BCYKD43SZJQP/bundle.json","state_url":"https://pith.science/pith/PSNV42EO6D2F23BCYKD43SZJQP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PSNV42EO6D2F23BCYKD43SZJQP/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":"2026-08-10T14:57:45Z","links":{"resolver":"https://pith.science/pith/PSNV42EO6D2F23BCYKD43SZJQP","bundle":"https://pith.science/pith/PSNV42EO6D2F23BCYKD43SZJQP/bundle.json","state":"https://pith.science/pith/PSNV42EO6D2F23BCYKD43SZJQP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PSNV42EO6D2F23BCYKD43SZJQP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PSNV42EO6D2F23BCYKD43SZJQP","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":"20715e9d200d92187c5266043a6952766c7a79181e986b029354f02c69e61c2d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-27T14:58:38Z","title_canon_sha256":"24f0c40ddc6ca307379ce9f86293ad2c7ea3561bec170b2d61030b847350caf8"},"schema_version":"1.0","source":{"id":"2406.19234","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19234","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19234v2","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19234","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_12","alias_value":"PSNV42EO6D2F","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_16","alias_value":"PSNV42EO6D2F23BC","created_at":"2026-07-05T09:12:07Z"},{"alias_kind":"pith_short_8","alias_value":"PSNV42EO","created_at":"2026-07-05T09:12:07Z"}],"graph_snapshots":[{"event_id":"sha256:8dbafe4c2eb06b2b17e62880b3ff1b9ad40d973a95f2af8c53f50cd34a282d67","target":"graph","created_at":"2026-07-05T09:12:07Z","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/2406.19234/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-Augmented Generation (RAG) is a state-of-the-art technique that mitigates issues such as hallucinations and knowledge staleness in Large Language Models (LLMs) by retrieving relevant knowledge from an external database to assist in content generation. Existing research has demonstrated potential privacy risks associated with the LLMs of RAG. However, the privacy risks posed by the integration of an external database, which often contains sensitive data such as medical records or personal identities, have remained largely unexplored. In this paper, we aim to bridge this gap by focusin","authors_text":"Chen Wang, Gaoyang Liu, Yang Yang, Yuying Li","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-27T14:58:38Z","title":"Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19234","kind":"arxiv","version":2},"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:e0bdc2768ba6d0fa24871b4bcf2e186126ebb77b4d29986b6df6a77489d1f668","target":"record","created_at":"2026-07-05T09:12:07Z","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":"20715e9d200d92187c5266043a6952766c7a79181e986b029354f02c69e61c2d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-27T14:58:38Z","title_canon_sha256":"24f0c40ddc6ca307379ce9f86293ad2c7ea3561bec170b2d61030b847350caf8"},"schema_version":"1.0","source":{"id":"2406.19234","kind":"arxiv","version":2}},"canonical_sha256":"7c9b5e688ef0f45d6c22c287cdcb2983d5db6e4bdcf415f069f42cd4185f2c96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c9b5e688ef0f45d6c22c287cdcb2983d5db6e4bdcf415f069f42cd4185f2c96","first_computed_at":"2026-07-05T09:12:07.742664Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:12:07.742664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r3KRL7wiZ3fTnX4hYWHcOFPH0YWRdL85mM9SiqOgSAkBCFUpmf74qJnDKJWsqTCUndvlwdu62o5xtdcE7avHCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:12:07.743150Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.19234","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0bdc2768ba6d0fa24871b4bcf2e186126ebb77b4d29986b6df6a77489d1f668","sha256:8dbafe4c2eb06b2b17e62880b3ff1b9ad40d973a95f2af8c53f50cd34a282d67"],"state_sha256":"b930edb89837591b5ee8aa4a5ff9ee2d88319651dbd0532864e49d8cfefa6ce5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nBloQzQ6UCg59UGj8vRSG4XzbINKr+1S7V24nnMwaLDLLouuE/qf9+fS9diPhnjK9ECnwg+QfQeWzXDQO0yVAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T14:57:45.152871Z","bundle_sha256":"f38e4ad966306138229a8091d2c7de9db87a528cb0b8827d0c5674981b637202"}}