{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:E4LQU2RRAXUKRY2XPNP4RWKYKQ","short_pith_number":"pith:E4LQU2RR","canonical_record":{"source":{"id":"2605.13214","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-13T09:06:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e7b8335d6cd6ec80eabb3f99a2153738a0a57aaa2990561a545ac320a9df870f","abstract_canon_sha256":"ff1d52e33a35d77f68cff34a954b3ac8f8038e05c1445207f5618451866f2d88"},"schema_version":"1.0"},"canonical_sha256":"27170a6a3105e8a8e3577b5fc8d95854151c879d172e04ba07e0a4ed0b917ed2","source":{"kind":"arxiv","id":"2605.13214","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.13214","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.13214v1","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.13214","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"pith_short_12","alias_value":"E4LQU2RRAXUK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"E4LQU2RRAXUKRY2X","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"E4LQU2RR","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:E4LQU2RRAXUKRY2XPNP4RWKYKQ","target":"record","payload":{"canonical_record":{"source":{"id":"2605.13214","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-13T09:06:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e7b8335d6cd6ec80eabb3f99a2153738a0a57aaa2990561a545ac320a9df870f","abstract_canon_sha256":"ff1d52e33a35d77f68cff34a954b3ac8f8038e05c1445207f5618451866f2d88"},"schema_version":"1.0"},"canonical_sha256":"27170a6a3105e8a8e3577b5fc8d95854151c879d172e04ba07e0a4ed0b917ed2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:08:48.499137Z","signature_b64":"vxwFKe1xB827FWdzdS7rii6WF1YbrfsUTxzNm6VGTgiWTYeY6/ZqD4TmsiLs0YwDMsUG/e9xMEgBTA3l5paXCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27170a6a3105e8a8e3577b5fc8d95854151c879d172e04ba07e0a4ed0b917ed2","last_reissued_at":"2026-05-18T03:08:48.498585Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:08:48.498585Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.13214","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":"2026-05-18T03:08:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"biQvDk/o9aWE8Qw7DWo3CJyq2mYEcDOzN5TOm88LimenOMLNkJ5RX39QySKYTLJkALWXuOxP6nl2X2Q9EsDlDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:59:07.479025Z"},"content_sha256":"127624369c709a1568ee93bb44a86952cd774c3960a3ab1ff1fa3780acaa6239","schema_version":"1.0","event_id":"sha256:127624369c709a1568ee93bb44a86952cd774c3960a3ab1ff1fa3780acaa6239"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:E4LQU2RRAXUKRY2XPNP4RWKYKQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters.","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Eirik Reiestad, Inga Str\\\"umke, Kristian Gj{\\o}steen, Marte Eggen","submitted_at":"2026-05-13T09:06:25Z","abstract_excerpt":"Recent cryptographic results establish that neural networks can be backdoored such that no efficient algorithm can distinguish them from a clean model. These guarantees, however, have been confined to stylised architectures of limited practical relevance, leaving open whether comparable undetectability extends to modern, end-to-end trained networks. We construct such an attack mechanism for state-of-the-art architectures, closely aligned to the cryptographic notion of undetectability, by identifying backdoor channels as learned latent directions, and show that the question of undetectability r"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"if exploitable channels within a network's latent space are statistically indistinguishable from naturally learned directions, an attacker need not introduce foreign structure but can instead exploit the geometry the network already possesses.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The hypothesis test between clean and backdoored parameter distributions is intractable in practice for state-of-the-art models; this is stated as a conjecture without a formal reduction or hardness proof.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Backdoors can be realized as statistically natural latent directions in modern neural networks, achieving high attack success with negligible clean accuracy loss and resisting existing defenses.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"c2aa25b68bb6af23ecae77c67ebf294b48367790eab7a4a030685130825084c3"},"source":{"id":"2605.13214","kind":"arxiv","version":1},"verdict":{"id":"3f60653d-dec8-485b-9f8e-26f5dcf66494","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T18:33:33.963434Z","strongest_claim":"if exploitable channels within a network's latent space are statistically indistinguishable from naturally learned directions, an attacker need not introduce foreign structure but can instead exploit the geometry the network already possesses.","one_line_summary":"Backdoors can be realized as statistically natural latent directions in modern neural networks, achieving high attack success with negligible clean accuracy loss and resisting existing defenses.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The hypothesis test between clean and backdoored parameter distributions is intractable in practice for state-of-the-art models; this is stated as a conjecture without a formal reduction or hardness proof.","pith_extraction_headline":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters."},"references":{"count":31,"sample":[{"doi":"","year":2025,"title":"Backdoor attacks and defenses in computer vision domain: A survey.arXiv preprint arXiv:2509.07504, 2025","work_id":"22a13bec-74e2-44d2-8484-6385db6a5ba7","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2013,"title":"Complexity theoretic lower bounds for sparse principal component detection","work_id":"8ace9111-4efc-425d-b55e-bd1030ac543d","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2013,"title":"Computational Lower Bounds for Sparse PCA","work_id":"c8902f8d-0de9-4766-b0d4-e00ae72c6596","ref_index":3,"cited_arxiv_id":"1304.0828","is_internal_anchor":true},{"doi":"","year":2019,"title":"Brennan and Guy Bresler","work_id":"a0e8a45c-e64c-46e6-a89b-916d0bcbe2c8","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"Data free backdoor attacks.Advances in Neural Information Processing Systems, 37:23881–23911, 2024","work_id":"052bbb93-8ee7-40ae-bc00-41a07f3cfd58","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":31,"snapshot_sha256":"9f6fcd43dee3685a02c3078d870d16706801aa608511822ee66ded0fc2acf78d","internal_anchors":5},"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":"3f60653d-dec8-485b-9f8e-26f5dcf66494"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:08:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v7NKjMHAAc+EOAv9Kco7ubjxNBXVdtW7U0hUTnV0gm7I6a3S7YvybFKRzq4XQ7lcy3Yk6V0L6/80xn/4DQMwDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T19:59:07.479730Z"},"content_sha256":"edabd8e5e8018db0c3a874d155002ecd605ee93718f555f96affe43df10706c8","schema_version":"1.0","event_id":"sha256:edabd8e5e8018db0c3a874d155002ecd605ee93718f555f96affe43df10706c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/bundle.json","state_url":"https://pith.science/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/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":"2026-06-03T19:59:07Z","links":{"resolver":"https://pith.science/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ","bundle":"https://pith.science/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/bundle.json","state":"https://pith.science/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E4LQU2RRAXUKRY2XPNP4RWKYKQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:E4LQU2RRAXUKRY2XPNP4RWKYKQ","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":"ff1d52e33a35d77f68cff34a954b3ac8f8038e05c1445207f5618451866f2d88","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-13T09:06:25Z","title_canon_sha256":"e7b8335d6cd6ec80eabb3f99a2153738a0a57aaa2990561a545ac320a9df870f"},"schema_version":"1.0","source":{"id":"2605.13214","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.13214","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.13214v1","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.13214","created_at":"2026-05-18T03:08:48Z"},{"alias_kind":"pith_short_12","alias_value":"E4LQU2RRAXUK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"E4LQU2RRAXUKRY2X","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"E4LQU2RR","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:edabd8e5e8018db0c3a874d155002ecd605ee93718f555f96affe43df10706c8","target":"graph","created_at":"2026-05-18T03:08:48Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"if exploitable channels within a network's latent space are statistically indistinguishable from naturally learned directions, an attacker need not introduce foreign structure but can instead exploit the geometry the network already possesses."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"The hypothesis test between clean and backdoored parameter distributions is intractable in practice for state-of-the-art models; this is stated as a conjecture without a formal reduction or hardness proof."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"Backdoors can be realized as statistically natural latent directions in modern neural networks, achieving high attack success with negligible clean accuracy loss and resisting existing defenses."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters."}],"snapshot_sha256":"c2aa25b68bb6af23ecae77c67ebf294b48367790eab7a4a030685130825084c3"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Recent cryptographic results establish that neural networks can be backdoored such that no efficient algorithm can distinguish them from a clean model. These guarantees, however, have been confined to stylised architectures of limited practical relevance, leaving open whether comparable undetectability extends to modern, end-to-end trained networks. We construct such an attack mechanism for state-of-the-art architectures, closely aligned to the cryptographic notion of undetectability, by identifying backdoor channels as learned latent directions, and show that the question of undetectability r","authors_text":"Eirik Reiestad, Inga Str\\\"umke, Kristian Gj{\\o}steen, Marte Eggen","cross_cats":["cs.LG"],"headline":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-13T09:06:25Z","title":"Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks"},"references":{"count":31,"internal_anchors":5,"resolved_work":31,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Backdoor attacks and defenses in computer vision domain: A survey.arXiv preprint arXiv:2509.07504, 2025","work_id":"22a13bec-74e2-44d2-8484-6385db6a5ba7","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Complexity theoretic lower bounds for sparse principal component detection","work_id":"8ace9111-4efc-425d-b55e-bd1030ac543d","year":2013},{"cited_arxiv_id":"1304.0828","doi":"","is_internal_anchor":true,"ref_index":3,"title":"Computational Lower Bounds for Sparse PCA","work_id":"c8902f8d-0de9-4766-b0d4-e00ae72c6596","year":2013},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Brennan and Guy Bresler","work_id":"a0e8a45c-e64c-46e6-a89b-916d0bcbe2c8","year":2019},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Data free backdoor attacks.Advances in Neural Information Processing Systems, 37:23881–23911, 2024","work_id":"052bbb93-8ee7-40ae-bc00-41a07f3cfd58","year":2024}],"snapshot_sha256":"9f6fcd43dee3685a02c3078d870d16706801aa608511822ee66ded0fc2acf78d"},"source":{"id":"2605.13214","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-14T18:33:33.963434Z","id":"3f60653d-dec8-485b-9f8e-26f5dcf66494","model_set":{"reader":"grok-4.3"},"one_line_summary":"Backdoors can be realized as statistically natural latent directions in modern neural networks, achieving high attack success with negligible clean accuracy loss and resisting existing defenses.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Neural networks can hide backdoors as statistically indistinguishable latent directions, reducing detection to an intractable hypothesis test on model parameters.","strongest_claim":"if exploitable channels within a network's latent space are statistically indistinguishable from naturally learned directions, an attacker need not introduce foreign structure but can instead exploit the geometry the network already possesses.","weakest_assumption":"The hypothesis test between clean and backdoored parameter distributions is intractable in practice for state-of-the-art models; this is stated as a conjecture without a formal reduction or hardness proof."}},"verdict_id":"3f60653d-dec8-485b-9f8e-26f5dcf66494"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:127624369c709a1568ee93bb44a86952cd774c3960a3ab1ff1fa3780acaa6239","target":"record","created_at":"2026-05-18T03:08:48Z","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":"ff1d52e33a35d77f68cff34a954b3ac8f8038e05c1445207f5618451866f2d88","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-13T09:06:25Z","title_canon_sha256":"e7b8335d6cd6ec80eabb3f99a2153738a0a57aaa2990561a545ac320a9df870f"},"schema_version":"1.0","source":{"id":"2605.13214","kind":"arxiv","version":1}},"canonical_sha256":"27170a6a3105e8a8e3577b5fc8d95854151c879d172e04ba07e0a4ed0b917ed2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27170a6a3105e8a8e3577b5fc8d95854151c879d172e04ba07e0a4ed0b917ed2","first_computed_at":"2026-05-18T03:08:48.498585Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:08:48.498585Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vxwFKe1xB827FWdzdS7rii6WF1YbrfsUTxzNm6VGTgiWTYeY6/ZqD4TmsiLs0YwDMsUG/e9xMEgBTA3l5paXCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T03:08:48.499137Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.13214","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:127624369c709a1568ee93bb44a86952cd774c3960a3ab1ff1fa3780acaa6239","sha256:edabd8e5e8018db0c3a874d155002ecd605ee93718f555f96affe43df10706c8"],"state_sha256":"fb85b560b282fc4fbdd9a156aaaed3742fda92cea5e0473124e197d90a90af0a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ClIV0/HHXNnEwUTV4NgRx54GUHbzHIK7dmPdQb6LRAGPlHc3nv1g9Byh6SXmgxFuztvicGfMag2ePuHHbdmdCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T19:59:07.482349Z","bundle_sha256":"88e88bb2dc8c6d540fd324fb2bf077369c12a876bfc19b983201fbbea1ee1a5c"}}