{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","short_pith_number":"pith:Z3LQJZNN","canonical_record":{"source":{"id":"2605.17971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-05-18T07:27:59Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"72849228458a730be09f1350f0a280951a59f1aaa1ffdd287ce1355b1a18d581","abstract_canon_sha256":"26cccc19e5fc334a0027ca29deacecf82c166083fd00b8ef99d6756f9d49bd7a"},"schema_version":"1.0"},"canonical_sha256":"ced704e5adc9631435f847063633bdddbc74fd1ff5e2aeffb38640ca2b1ded06","source":{"kind":"arxiv","id":"2605.17971","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17971","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17971v1","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17971","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_12","alias_value":"Z3LQJZNNZFRR","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_16","alias_value":"Z3LQJZNNZFRRINPY","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_8","alias_value":"Z3LQJZNN","created_at":"2026-05-20T00:05:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","target":"record","payload":{"canonical_record":{"source":{"id":"2605.17971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-05-18T07:27:59Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"72849228458a730be09f1350f0a280951a59f1aaa1ffdd287ce1355b1a18d581","abstract_canon_sha256":"26cccc19e5fc334a0027ca29deacecf82c166083fd00b8ef99d6756f9d49bd7a"},"schema_version":"1.0"},"canonical_sha256":"ced704e5adc9631435f847063633bdddbc74fd1ff5e2aeffb38640ca2b1ded06","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:08.807166Z","signature_b64":"ce//l4cXK8EDaOrbqYxaGIFW9JX/T9LyVq9KH1PuaHVxbsuV+k9a7XBfCtcUb3UGTfV01KB0mrL21xDpQCR1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ced704e5adc9631435f847063633bdddbc74fd1ff5e2aeffb38640ca2b1ded06","last_reissued_at":"2026-05-20T00:05:08.806265Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:08.806265Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.17971","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":"2026-05-20T00:05:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jaNzb0dUziab4fx2MgRS3A/AzEDlvW9gadVYanYcQfGzDVkDIBmysfdHKOIByyq3BWR2ztBYxcJdmv/SpxTUAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T17:41:35.519297Z"},"content_sha256":"3c571e19604621e0408147ec65df1c11d8c72a42cae32360f57963e8f1e2461a","schema_version":"1.0","event_id":"sha256:3c571e19604621e0408147ec65df1c11d8c72a42cae32360f57963e8f1e2461a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Cong Wu, Jing Chen, Ju Jia, Ruichao Liang, Ruiying Du, Yang Liu, Yebo Feng, Zhi Wang, Ziwei Wang","submitted_at":"2026-05-18T07:27:59Z","abstract_excerpt":"Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuristic templates or exhaustive trials, lacking mechanistic interpretability and query efficiency. In this study, we investigate an intrinsic vulnerability in the safety mechanisms of LLMs, where safety alignment relies on a small set of sparsely distributed attention heads, leaving much of the representational space weakly monitored. We formalize this phenomenon with a mathematical jailbreaking model that characterizes the delicate boundary of effe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17971","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/2605.17971/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.575151Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"98b4aa48d5f7373c049878c6c48a8e011306ead6dbe4845429fe688b4d482d6e"},"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":"2026-05-20T00:05:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vnoYPzBaB3pEDp5c2h8vkjImTiU3hoctCWp04DeZ4QE3vT4/e+JKz05roePQtL/zDXSP8o9nybZBJgOt8DIqCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T17:41:35.519758Z"},"content_sha256":"27baa2a29521b4af83505a438a435444e50e03a9a1737a6984e3c4f0d91fa078","schema_version":"1.0","event_id":"sha256:27baa2a29521b4af83505a438a435444e50e03a9a1737a6984e3c4f0d91fa078"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.48550/arxiv.2412.12621.Jiawei) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"doi: 10.48550/arxiv.2412. 12621. Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G. Parker, and M. de Choudhury. Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions. International Conferenc","arxiv_id":"2605.17971","detector":"doi_compliance","evidence":{"ref_index":19,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"doi: 10.48550/arxiv.2412. 12621. Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G. Parker, and M. de Choudhury. Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions. International Conferenc","reconstructed_doi":"10.48550/arxiv.2412.12621.Jiawei"},"severity":"advisory","ref_index":19,"audited_at":"2026-05-20T10:13:58.507440Z","event_type":"pith.integrity.v1","detected_doi":"10.48550/arxiv.2412.12621.Jiawei","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"d6ccceb8dac9b762856772d04fdf828a2b29b5104b34ec408d2c43bc6a60eb19","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":5002,"payload_sha256":"8cccac6c98d1c9eb292860b32948358a7b8af97c615ea79755ae26fa95964d3d","signature_b64":"tf9fH33ztB9CI1A0w6kGZiFfnlpiNX3Gr8g/aEpCeMMV9HvmBiKn3Trc77UtQLZ6CNKnELfMgRZRj6H5KGHnAQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T10:17:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vb6W9trgoPlKrnKAaFhWk3gcP7Uww6d7Yd9v5Du0HsZLldfQzr2R0DdPPeM/oHJm+yNMtC8hN6wO3zNyfVYdBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T17:41:35.520845Z"},"content_sha256":"4918bdb4291b379af1039c34eba7378e88206050c3434d5f234ce10d8eb87396","schema_version":"1.0","event_id":"sha256:4918bdb4291b379af1039c34eba7378e88206050c3434d5f234ce10d8eb87396"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.48550/arxiv.2406.03712.Xiaogeng) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Lei Liu, Xiaoyan Yang, Junchi Lei, Xiaoyang Liu, Yue Shen, Zhiqiang Zhang, Peng Wei, Jinjie Gu, Zhixuan Chu, Zhan Qin, and Kui Ren. A survey on medical large language models: Technology, application, trustworthiness, and future directions.a","arxiv_id":"2605.17971","detector":"doi_compliance","evidence":{"ref_index":8,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"Lei Liu, Xiaoyan Yang, Junchi Lei, Xiaoyang Liu, Yue Shen, Zhiqiang Zhang, Peng Wei, Jinjie Gu, Zhixuan Chu, Zhan Qin, and Kui Ren. A survey on medical large language models: Technology, application, trustworthiness, and future directions.a","reconstructed_doi":"10.48550/arxiv.2406.03712.Xiaogeng"},"severity":"advisory","ref_index":8,"audited_at":"2026-05-20T10:13:58.507440Z","event_type":"pith.integrity.v1","detected_doi":"10.48550/arxiv.2406.03712.Xiaogeng","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"4f8ea644f624cb9d628217d833761862e0dc1191aadcdda082570ccf39df2521","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":5001,"payload_sha256":"bac19e803d81b8e34f213899532698d13ccf5d38ffce8e56d18d595e8413ae75","signature_b64":"9gInH/m+ywOHL/kukECAXGdGMlu66x24RCX9ZB1EQaAc9OX0CB8r+gA4XFw0D8cSANbr/GD/XboLJqnDP/ymCA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T10:17:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"snOJUZS9i2N213vyZtgzeDinCh+NMl6+2/NR5JC7vGzUeHRcN+CXVLFZ7sMYzGp0DV0adu0zgrqNMd/myMRbBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T17:41:35.521133Z"},"content_sha256":"dcb20fc49529d16c8ccef7edd3500868a5a38119da6870644109d0ce533d2ed4","schema_version":"1.0","event_id":"sha256:dcb20fc49529d16c8ccef7edd3500868a5a38119da6870644109d0ce533d2ed4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z3LQJZNNZFRRINPYI4DDMM553W/bundle.json","state_url":"https://pith.science/pith/Z3LQJZNNZFRRINPYI4DDMM553W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z3LQJZNNZFRRINPYI4DDMM553W/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":"2026-05-21T17:41:35Z","links":{"resolver":"https://pith.science/pith/Z3LQJZNNZFRRINPYI4DDMM553W","bundle":"https://pith.science/pith/Z3LQJZNNZFRRINPYI4DDMM553W/bundle.json","state":"https://pith.science/pith/Z3LQJZNNZFRRINPYI4DDMM553W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z3LQJZNNZFRRINPYI4DDMM553W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Z3LQJZNNZFRRINPYI4DDMM553W","merge_version":"pith-open-graph-merge-v1","event_count":4,"valid_event_count":4,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"26cccc19e5fc334a0027ca29deacecf82c166083fd00b8ef99d6756f9d49bd7a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-05-18T07:27:59Z","title_canon_sha256":"72849228458a730be09f1350f0a280951a59f1aaa1ffdd287ce1355b1a18d581"},"schema_version":"1.0","source":{"id":"2605.17971","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17971","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17971v1","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17971","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_12","alias_value":"Z3LQJZNNZFRR","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_16","alias_value":"Z3LQJZNNZFRRINPY","created_at":"2026-05-20T00:05:08Z"},{"alias_kind":"pith_short_8","alias_value":"Z3LQJZNN","created_at":"2026-05-20T00:05:08Z"}],"graph_snapshots":[{"event_id":"sha256:27baa2a29521b4af83505a438a435444e50e03a9a1737a6984e3c4f0d91fa078","target":"graph","created_at":"2026-05-20T00:05:08Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.575151Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.17971/integrity.json","findings":[],"snapshot_sha256":"98b4aa48d5f7373c049878c6c48a8e011306ead6dbe4845429fe688b4d482d6e","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuristic templates or exhaustive trials, lacking mechanistic interpretability and query efficiency. In this study, we investigate an intrinsic vulnerability in the safety mechanisms of LLMs, where safety alignment relies on a small set of sparsely distributed attention heads, leaving much of the representational space weakly monitored. We formalize this phenomenon with a mathematical jailbreaking model that characterizes the delicate boundary of effe","authors_text":"Cong Wu, Jing Chen, Ju Jia, Ruichao Liang, Ruiying Du, Yang Liu, Yebo Feng, Zhi Wang, Ziwei Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-05-18T07:27:59Z","title":"Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17971","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":"sha256:3c571e19604621e0408147ec65df1c11d8c72a42cae32360f57963e8f1e2461a","target":"record","created_at":"2026-05-20T00:05:08Z","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":"26cccc19e5fc334a0027ca29deacecf82c166083fd00b8ef99d6756f9d49bd7a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-05-18T07:27:59Z","title_canon_sha256":"72849228458a730be09f1350f0a280951a59f1aaa1ffdd287ce1355b1a18d581"},"schema_version":"1.0","source":{"id":"2605.17971","kind":"arxiv","version":1}},"canonical_sha256":"ced704e5adc9631435f847063633bdddbc74fd1ff5e2aeffb38640ca2b1ded06","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ced704e5adc9631435f847063633bdddbc74fd1ff5e2aeffb38640ca2b1ded06","first_computed_at":"2026-05-20T00:05:08.806265Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:08.806265Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ce//l4cXK8EDaOrbqYxaGIFW9JX/T9LyVq9KH1PuaHVxbsuV+k9a7XBfCtcUb3UGTfV01KB0mrL21xDpQCR1Bw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:08.807166Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17971","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:4918bdb4291b379af1039c34eba7378e88206050c3434d5f234ce10d8eb87396","sha256:dcb20fc49529d16c8ccef7edd3500868a5a38119da6870644109d0ce533d2ed4"]}],"invalid_events":[],"applied_event_ids":["sha256:3c571e19604621e0408147ec65df1c11d8c72a42cae32360f57963e8f1e2461a","sha256:27baa2a29521b4af83505a438a435444e50e03a9a1737a6984e3c4f0d91fa078"],"state_sha256":"a2b1062e7088b42da50bd11eb4547a75f396f73ffe53e70f70d1c181797ffa34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I1H03mol2oS3TaFX9aOAA+nKURpHDWwAX4uXq82suqZ5SWkw9qk7rhQqAQksB6DQ6O+Y6YJupnpqbgvWlok3DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T17:41:35.523520Z","bundle_sha256":"1c3c6d13bbd4ef0185607d7b72474d6c5d037ea9b642c1e0e1d1c8cbded43d27"}}