{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:QJK4BQMWZDAS7JBKO3RVZYCMZC","short_pith_number":"pith:QJK4BQMW","canonical_record":{"source":{"id":"2605.14454","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-14T06:47:35Z","cross_cats_sorted":["cs.CL","cs.CR"],"title_canon_sha256":"83112d8d63c9d9e89e4441f226287b3b1efc3e1340e8f2107dda1be83dad7e2b","abstract_canon_sha256":"0a5bb190844c1501b1315e2c073ec063e06724e9c2e6e3f5f70f2378b31bd005"},"schema_version":"1.0"},"canonical_sha256":"8255c0c196c8c12fa42a76e35ce04cc89c5dcfdf2aa759d62121f51d73ea51b9","source":{"kind":"arxiv","id":"2605.14454","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14454","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14454v1","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14454","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"QJK4BQMWZDAS","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"QJK4BQMWZDAS7JBK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"QJK4BQMW","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:QJK4BQMWZDAS7JBKO3RVZYCMZC","target":"record","payload":{"canonical_record":{"source":{"id":"2605.14454","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-14T06:47:35Z","cross_cats_sorted":["cs.CL","cs.CR"],"title_canon_sha256":"83112d8d63c9d9e89e4441f226287b3b1efc3e1340e8f2107dda1be83dad7e2b","abstract_canon_sha256":"0a5bb190844c1501b1315e2c073ec063e06724e9c2e6e3f5f70f2378b31bd005"},"schema_version":"1.0"},"canonical_sha256":"8255c0c196c8c12fa42a76e35ce04cc89c5dcfdf2aa759d62121f51d73ea51b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:06.857804Z","signature_b64":"nOKyYOhfCJgZ1OYO/xeb194fhy5+bvIP0Ov43xKFlRVsJslxntYefMNj3jvinyVN2R0cnqZJ4Mxl2tvj+kYrDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8255c0c196c8c12fa42a76e35ce04cc89c5dcfdf2aa759d62121f51d73ea51b9","last_reissued_at":"2026-05-17T23:39:06.857137Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:06.857137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.14454","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":"2026-05-17T23:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QHthzPAmAXwqcZ53GtMZn7DnbEXk2L+ZkwzyHVOxl4jKYPbmQbfrvXo+x5jKKkrteWlSz7ozV8E7Q1jtnyz7Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T21:09:33.140966Z"},"content_sha256":"958f9f3845ba0184cf48b95986b3b94813f26b8fc4129cc190db48679977ed7b","schema_version":"1.0","event_id":"sha256:958f9f3845ba0184cf48b95986b3b94813f26b8fc4129cc190db48679977ed7b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:QJK4BQMWZDAS7JBKO3RVZYCMZC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LiSA: Lifelong Safety Adaptation via Conservative Policy Induction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies.","cross_cats":["cs.CL","cs.CR"],"primary_cat":"cs.LG","authors_text":"Bharath Chandrasekhar, Bhavana Dalvi Mishra, Kyomin Jung, Lesly Miculicich, Long T. Le, Mihir Parmar, Minbeom Kim, Phillip Wallis, Tomas Pfister","submitted_at":"2026-05-14T06:47:35Z","abstract_excerpt":"As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete deployment harms. In these settings, guardrail failures are no longer merely answer-quality errors: they can leak secrets, authorize unsafe actions, or block legitimate work. The hardest failures are often contextual: whether an action is acceptable depends on local privacy norms, organizational policies, and user expectations that resist pre-deployment specification. This creates a practical gap: guardrails must adapt"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Across PrivacyLens+, ConFaide+, and AgentHarm, LiSA consistently outperforms strong memory-based baselines under sparse feedback, remains robust under noisy user feedback even at 20% label-flip rates, and pushes the latency--performance frontier beyond backbone model scaling.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That occasional sparse and noisy user-reported failures can be reliably converted into reusable policy abstractions that generalize without overgeneralization, supported by conflict-aware local rules and evidence-aware posterior lower-bound gating.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"LiSA improves AI guardrails lifelong by inducing conservative policies from sparse noisy failure reports via structured memory, conflict-aware rules, and posterior lower-bound gating.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"55a87722fcbff0044106119fb620af0794a698b2a7081782e87b46d1dac290f4"},"source":{"id":"2605.14454","kind":"arxiv","version":1},"verdict":{"id":"32776a9c-4fa9-47e8-b3c0-076c96f06707","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T01:49:58.412235Z","strongest_claim":"Across PrivacyLens+, ConFaide+, and AgentHarm, LiSA consistently outperforms strong memory-based baselines under sparse feedback, remains robust under noisy user feedback even at 20% label-flip rates, and pushes the latency--performance frontier beyond backbone model scaling.","one_line_summary":"LiSA improves AI guardrails lifelong by inducing conservative policies from sparse noisy failure reports via structured memory, conflict-aware rules, and posterior lower-bound gating.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That occasional sparse and noisy user-reported failures can be reliably converted into reusable policy abstractions that generalize without overgeneralization, supported by conflict-aware local rules and evidence-aware posterior lower-bound gating.","pith_extraction_headline":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies."},"references":{"count":47,"sample":[{"doi":"","year":2004,"title":"Privacy as contextual integrity , author=. Wash. L. Rev. , volume=. 2004 , publisher=","work_id":"8b6785e7-0848-443c-9c81-50e27067b8a6","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Gemini Embedding: Generalizable Embeddings from Gemini","work_id":"911b6918-a128-453f-ae99-94388c38fcb1","ref_index":2,"cited_arxiv_id":"2503.07891","is_internal_anchor":true},{"doi":"","year":null,"title":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","work_id":"3dc6599a-4158-4b45-8b6c-3946d23d4ba9","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"Introducing Claude Haiku 4.5 , author=. 2025 , url=","work_id":"c42de211-a529-4fe2-8aeb-bdfede431e1e","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"A new era of intelligence with Gemini 3 , author=. Google. URL: https://blog.google/products-and-platforms/products/gemini/gemini-3 , year=","work_id":"7e33519b-a76e-4d28-8f8a-c86ae2704c25","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":47,"snapshot_sha256":"b41929fcfca4c753cb2366db7b215e4b27167ecca3a63af89546f594c96c8d74","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":"32776a9c-4fa9-47e8-b3c0-076c96f06707"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+pyvylzAvVDhcOarvbbraKLKWJGMvpV5rceV76U2nKm8p0BWh6a4rYPhpoiw5C6VNDzfyIr61ahQDnERmybSBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T21:09:33.141530Z"},"content_sha256":"4c0bbd2ce87414951baa1883ed7a46c89a8cd45516a1ffc2caacf4cd281bc43b","schema_version":"1.0","event_id":"sha256:4c0bbd2ce87414951baa1883ed7a46c89a8cd45516a1ffc2caacf4cd281bc43b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/bundle.json","state_url":"https://pith.science/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/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":"2026-05-19T21:09:33Z","links":{"resolver":"https://pith.science/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC","bundle":"https://pith.science/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/bundle.json","state":"https://pith.science/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QJK4BQMWZDAS7JBKO3RVZYCMZC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QJK4BQMWZDAS7JBKO3RVZYCMZC","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":"0a5bb190844c1501b1315e2c073ec063e06724e9c2e6e3f5f70f2378b31bd005","cross_cats_sorted":["cs.CL","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-14T06:47:35Z","title_canon_sha256":"83112d8d63c9d9e89e4441f226287b3b1efc3e1340e8f2107dda1be83dad7e2b"},"schema_version":"1.0","source":{"id":"2605.14454","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14454","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14454v1","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14454","created_at":"2026-05-17T23:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"QJK4BQMWZDAS","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"QJK4BQMWZDAS7JBK","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"QJK4BQMW","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:4c0bbd2ce87414951baa1883ed7a46c89a8cd45516a1ffc2caacf4cd281bc43b","target":"graph","created_at":"2026-05-17T23:39:06Z","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":"Across PrivacyLens+, ConFaide+, and AgentHarm, LiSA consistently outperforms strong memory-based baselines under sparse feedback, remains robust under noisy user feedback even at 20% label-flip rates, and pushes the latency--performance frontier beyond backbone model scaling."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That occasional sparse and noisy user-reported failures can be reliably converted into reusable policy abstractions that generalize without overgeneralization, supported by conflict-aware local rules and evidence-aware posterior lower-bound gating."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"LiSA improves AI guardrails lifelong by inducing conservative policies from sparse noisy failure reports via structured memory, conflict-aware rules, and posterior lower-bound gating."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies."}],"snapshot_sha256":"55a87722fcbff0044106119fb620af0794a698b2a7081782e87b46d1dac290f4"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete deployment harms. In these settings, guardrail failures are no longer merely answer-quality errors: they can leak secrets, authorize unsafe actions, or block legitimate work. The hardest failures are often contextual: whether an action is acceptable depends on local privacy norms, organizational policies, and user expectations that resist pre-deployment specification. This creates a practical gap: guardrails must adapt","authors_text":"Bharath Chandrasekhar, Bhavana Dalvi Mishra, Kyomin Jung, Lesly Miculicich, Long T. Le, Mihir Parmar, Minbeom Kim, Phillip Wallis, Tomas Pfister","cross_cats":["cs.CL","cs.CR"],"headline":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-14T06:47:35Z","title":"LiSA: Lifelong Safety Adaptation via Conservative Policy Induction"},"references":{"count":47,"internal_anchors":5,"resolved_work":47,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Privacy as contextual integrity , author=. Wash. L. Rev. , volume=. 2004 , publisher=","work_id":"8b6785e7-0848-443c-9c81-50e27067b8a6","year":2004},{"cited_arxiv_id":"2503.07891","doi":"","is_internal_anchor":true,"ref_index":2,"title":"Gemini Embedding: Generalizable Embeddings from Gemini","work_id":"911b6918-a128-453f-ae99-94388c38fcb1","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","work_id":"3dc6599a-4158-4b45-8b6c-3946d23d4ba9","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Introducing Claude Haiku 4.5 , author=. 2025 , url=","work_id":"c42de211-a529-4fe2-8aeb-bdfede431e1e","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"A new era of intelligence with Gemini 3 , author=. Google. URL: https://blog.google/products-and-platforms/products/gemini/gemini-3 , year=","work_id":"7e33519b-a76e-4d28-8f8a-c86ae2704c25","year":null}],"snapshot_sha256":"b41929fcfca4c753cb2366db7b215e4b27167ecca3a63af89546f594c96c8d74"},"source":{"id":"2605.14454","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-15T01:49:58.412235Z","id":"32776a9c-4fa9-47e8-b3c0-076c96f06707","model_set":{"reader":"grok-4.3"},"one_line_summary":"LiSA improves AI guardrails lifelong by inducing conservative policies from sparse noisy failure reports via structured memory, conflict-aware rules, and posterior lower-bound gating.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"LiSA lets fixed guardrails adapt to sparse noisy user feedback by inducing conservative reusable policies.","strongest_claim":"Across PrivacyLens+, ConFaide+, and AgentHarm, LiSA consistently outperforms strong memory-based baselines under sparse feedback, remains robust under noisy user feedback even at 20% label-flip rates, and pushes the latency--performance frontier beyond backbone model scaling.","weakest_assumption":"That occasional sparse and noisy user-reported failures can be reliably converted into reusable policy abstractions that generalize without overgeneralization, supported by conflict-aware local rules and evidence-aware posterior lower-bound gating."}},"verdict_id":"32776a9c-4fa9-47e8-b3c0-076c96f06707"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:958f9f3845ba0184cf48b95986b3b94813f26b8fc4129cc190db48679977ed7b","target":"record","created_at":"2026-05-17T23:39:06Z","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":"0a5bb190844c1501b1315e2c073ec063e06724e9c2e6e3f5f70f2378b31bd005","cross_cats_sorted":["cs.CL","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-14T06:47:35Z","title_canon_sha256":"83112d8d63c9d9e89e4441f226287b3b1efc3e1340e8f2107dda1be83dad7e2b"},"schema_version":"1.0","source":{"id":"2605.14454","kind":"arxiv","version":1}},"canonical_sha256":"8255c0c196c8c12fa42a76e35ce04cc89c5dcfdf2aa759d62121f51d73ea51b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8255c0c196c8c12fa42a76e35ce04cc89c5dcfdf2aa759d62121f51d73ea51b9","first_computed_at":"2026-05-17T23:39:06.857137Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:06.857137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nOKyYOhfCJgZ1OYO/xeb194fhy5+bvIP0Ov43xKFlRVsJslxntYefMNj3jvinyVN2R0cnqZJ4Mxl2tvj+kYrDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:06.857804Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.14454","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:958f9f3845ba0184cf48b95986b3b94813f26b8fc4129cc190db48679977ed7b","sha256:4c0bbd2ce87414951baa1883ed7a46c89a8cd45516a1ffc2caacf4cd281bc43b"],"state_sha256":"a753271c2a1781f9ee5dbffea6c795df99762e63c98df580dbbf393ca747dea3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4nuRBwCrFgLRYmrX+zqn/XSMZCph50tDmrv58FL2foDWf0oJXzJRQBQGArfaCyOgMb1sIQ0Qnpzrox6h9DhbAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-19T21:09:33.143987Z","bundle_sha256":"d842eb89d970960aecd3fc77e6b7c780f409a8d8d213cda82dfe1693701feb6f"}}