{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2X7GCLKHNB4RE23GWRFB2BI3XJ","short_pith_number":"pith:2X7GCLKH","canonical_record":{"source":{"id":"2503.09291","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-12T11:36:29Z","cross_cats_sorted":[],"title_canon_sha256":"b052bda7d1de56c312a683e1686171960fdbee4e784d4f37b3f3e57ab673228c","abstract_canon_sha256":"76707ae04b6128d4af1e63c7454202c3207fa167d60310e4462631185671ff84"},"schema_version":"1.0"},"canonical_sha256":"d5fe612d476879126b66b44a1d051bba5ac7135c4b86f9a349e22f0da29f4707","source":{"kind":"arxiv","id":"2503.09291","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.09291","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"arxiv_version","alias_value":"2503.09291v2","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.09291","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_12","alias_value":"2X7GCLKHNB4R","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_16","alias_value":"2X7GCLKHNB4RE23G","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_8","alias_value":"2X7GCLKH","created_at":"2026-07-05T11:08:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2X7GCLKHNB4RE23GWRFB2BI3XJ","target":"record","payload":{"canonical_record":{"source":{"id":"2503.09291","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-12T11:36:29Z","cross_cats_sorted":[],"title_canon_sha256":"b052bda7d1de56c312a683e1686171960fdbee4e784d4f37b3f3e57ab673228c","abstract_canon_sha256":"76707ae04b6128d4af1e63c7454202c3207fa167d60310e4462631185671ff84"},"schema_version":"1.0"},"canonical_sha256":"d5fe612d476879126b66b44a1d051bba5ac7135c4b86f9a349e22f0da29f4707","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:17.722370Z","signature_b64":"Y2qHjrlAIK0ALa1Ys09/1R1MIuhCSqByuxEJzycu9dYRZlYeWUhUyDoQtxcFUHbJGQ2pLtfz1xJCv4gS2/UFAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5fe612d476879126b66b44a1d051bba5ac7135c4b86f9a349e22f0da29f4707","last_reissued_at":"2026-07-05T11:08:17.721802Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:17.721802Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.09291","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":"2026-07-05T11:08:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EvxbTvIljZSvoz/DJwToYQdAPfv7rvUtqLlliRljX5nRLW96IzztkVZJcQOk0PJqXgHoHSTOfPEEjxix+aJ4Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:47:26.870026Z"},"content_sha256":"1f2074e23f099e24342e169ffefe745722a3e760bcbc943cbdc5f0c9d0c4072b","schema_version":"1.0","event_id":"sha256:1f2074e23f099e24342e169ffefe745722a3e760bcbc943cbdc5f0c9d0c4072b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2X7GCLKHNB4RE23GWRFB2BI3XJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prompt Inference Attack on Distributed Large Language Model Inference Frameworks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Ting Yu, Xiaokui Xiao, Xinjian Luo","submitted_at":"2025-03-12T11:36:29Z","abstract_excerpt":"The inference process of modern large language models (LLMs) demands prohibitive computational resources, rendering them infeasible for deployment on consumer-grade devices. To address this limitation, recent studies propose distributed LLM inference frameworks, which employ split learning principles to enable collaborative LLM inference on resource-constrained hardware. However, distributing LLM layers across participants requires the transmission of intermediate outputs, which may introduce privacy risks to the original input prompts - a critical issue that has yet to be thoroughly explored "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.09291","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/2503.09291/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":"2026-07-05T11:08:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cFQNbdDv8WAlBO+27isbUZXk/50u+VyRiOFrvB075cWIa530Apn13pmZcmGB+zc2ltc3FgMOE1g3CBGqon12Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:47:26.871282Z"},"content_sha256":"f5ae05da59d90cf14ae8eb3b3e4e6d783e84724af6a634e262b2956d7ecf8f5d","schema_version":"1.0","event_id":"sha256:f5ae05da59d90cf14ae8eb3b3e4e6d783e84724af6a634e262b2956d7ecf8f5d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/bundle.json","state_url":"https://pith.science/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/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":"2026-08-11T11:47:26Z","links":{"resolver":"https://pith.science/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ","bundle":"https://pith.science/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/bundle.json","state":"https://pith.science/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2X7GCLKHNB4RE23GWRFB2BI3XJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2X7GCLKHNB4RE23GWRFB2BI3XJ","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":"76707ae04b6128d4af1e63c7454202c3207fa167d60310e4462631185671ff84","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-12T11:36:29Z","title_canon_sha256":"b052bda7d1de56c312a683e1686171960fdbee4e784d4f37b3f3e57ab673228c"},"schema_version":"1.0","source":{"id":"2503.09291","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.09291","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"arxiv_version","alias_value":"2503.09291v2","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.09291","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_12","alias_value":"2X7GCLKHNB4R","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_16","alias_value":"2X7GCLKHNB4RE23G","created_at":"2026-07-05T11:08:17Z"},{"alias_kind":"pith_short_8","alias_value":"2X7GCLKH","created_at":"2026-07-05T11:08:17Z"}],"graph_snapshots":[{"event_id":"sha256:f5ae05da59d90cf14ae8eb3b3e4e6d783e84724af6a634e262b2956d7ecf8f5d","target":"graph","created_at":"2026-07-05T11:08:17Z","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/2503.09291/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The inference process of modern large language models (LLMs) demands prohibitive computational resources, rendering them infeasible for deployment on consumer-grade devices. To address this limitation, recent studies propose distributed LLM inference frameworks, which employ split learning principles to enable collaborative LLM inference on resource-constrained hardware. However, distributing LLM layers across participants requires the transmission of intermediate outputs, which may introduce privacy risks to the original input prompts - a critical issue that has yet to be thoroughly explored ","authors_text":"Ting Yu, Xiaokui Xiao, Xinjian Luo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-12T11:36:29Z","title":"Prompt Inference Attack on Distributed Large Language Model Inference Frameworks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.09291","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":"sha256:1f2074e23f099e24342e169ffefe745722a3e760bcbc943cbdc5f0c9d0c4072b","target":"record","created_at":"2026-07-05T11:08:17Z","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":"76707ae04b6128d4af1e63c7454202c3207fa167d60310e4462631185671ff84","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-12T11:36:29Z","title_canon_sha256":"b052bda7d1de56c312a683e1686171960fdbee4e784d4f37b3f3e57ab673228c"},"schema_version":"1.0","source":{"id":"2503.09291","kind":"arxiv","version":2}},"canonical_sha256":"d5fe612d476879126b66b44a1d051bba5ac7135c4b86f9a349e22f0da29f4707","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5fe612d476879126b66b44a1d051bba5ac7135c4b86f9a349e22f0da29f4707","first_computed_at":"2026-07-05T11:08:17.721802Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:17.721802Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y2qHjrlAIK0ALa1Ys09/1R1MIuhCSqByuxEJzycu9dYRZlYeWUhUyDoQtxcFUHbJGQ2pLtfz1xJCv4gS2/UFAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:17.722370Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.09291","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f2074e23f099e24342e169ffefe745722a3e760bcbc943cbdc5f0c9d0c4072b","sha256:f5ae05da59d90cf14ae8eb3b3e4e6d783e84724af6a634e262b2956d7ecf8f5d"],"state_sha256":"0526d1ee7f86efd0ad126cef656ee1f51fa586c34ce15321f77cb4de641fb1f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gvv2/abd/ZsyTMYZ7LSoDiaGsOCpw3lhJy5b+c2PqQPaFY2pr4mQNVF+nqK8TUW2meGvKE6xZCqOP4mncjjHDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T11:47:26.877653Z","bundle_sha256":"ac3fe5218fe3cd0673059ce793a363c753c41352e7e8ff8e2e970e51def6fd04"}}