{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:J276MSRKZYZD4E7PELII3T7AEU","short_pith_number":"pith:J276MSRK","canonical_record":{"source":{"id":"2605.15204","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-20T12:51:39Z","cross_cats_sorted":[],"title_canon_sha256":"2682461e28eb2548ba4359aad730a8d194755abb6fe559087bb241894b3a8491","abstract_canon_sha256":"98f1b1c82e3214113f2157c03416f5a2de529c2313ac5a3a7cfab68915a87ca1"},"schema_version":"1.0"},"canonical_sha256":"4ebfe64a2ace323e13ef22d08dcfe0253f2625ccb9655806abfe5d41eedbda61","source":{"kind":"arxiv","id":"2605.15204","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15204","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15204v1","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15204","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_12","alias_value":"J276MSRKZYZD","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_16","alias_value":"J276MSRKZYZD4E7P","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_8","alias_value":"J276MSRK","created_at":"2026-05-20T00:00:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:J276MSRKZYZD4E7PELII3T7AEU","target":"record","payload":{"canonical_record":{"source":{"id":"2605.15204","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-20T12:51:39Z","cross_cats_sorted":[],"title_canon_sha256":"2682461e28eb2548ba4359aad730a8d194755abb6fe559087bb241894b3a8491","abstract_canon_sha256":"98f1b1c82e3214113f2157c03416f5a2de529c2313ac5a3a7cfab68915a87ca1"},"schema_version":"1.0"},"canonical_sha256":"4ebfe64a2ace323e13ef22d08dcfe0253f2625ccb9655806abfe5d41eedbda61","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:00:45.901271Z","signature_b64":"cNzsizSoI0+181FU04xL19C8RDMNeWGkr+Mlfic3PLYrMuHPjgJPHSKkLv+aRKq6OSdQfQBdV8gj9VKc0tmnCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ebfe64a2ace323e13ef22d08dcfe0253f2625ccb9655806abfe5d41eedbda61","last_reissued_at":"2026-05-20T00:00:45.900309Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:00:45.900309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.15204","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":"2026-05-20T00:00:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h0Hkc83YrcGVkf6GaLT2y++t6OlfjdXi2Sb6VrCi4wpZt5SWvv4s8VdIxW4XvvPQ+l7/XRwxTSeFmbE/i4M0BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T06:13:07.676271Z"},"content_sha256":"abd5190535d1d7d6ce3e6d4dba8b557b392c5f93a53ccfb616e8442b6da4d642","schema_version":"1.0","event_id":"sha256:abd5190535d1d7d6ce3e6d4dba8b557b392c5f93a53ccfb616e8442b6da4d642"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:J276MSRKZYZD4E7PELII3T7AEU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations.","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Zhantao Wang","submitted_at":"2026-04-20T12:51:39Z","abstract_excerpt":"Multi-agent orchestration frameworks such as LangChain, LangGraph, and CrewAI route tasks through graph-based pipelines but do not enforce the stage constraints that govern real business processes. We present SDOF, a framework that treats multi-agent execution as a constrained state machine. SDOF operates through two primary defensive layers, implemented by three components: (1) an Online-RLHF Specialized Intent Router trained via Generative Reward Modeling (GRPO) and (2) a StateAwareDispatcher with GoalStage finite-automaton checks and precondition/postcondition SkillRegistry validation for a"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Our GSPO-aligned 7B Intent Router achieves higher joint accuracy than zero-shot GPT-4o on this FSM-constrained adversarial routing benchmark (80.9% versus 48.9%). In end-to-end execution, SDOF reaches 86.5% task completion and blocks all 22 operations in the injection, illegal HR subset.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The expert-curated 185 scenarios and the Beisen iTalent platform data accurately represent general multi-agent orchestration challenges and that the GoalStage finite-automaton mapping faithfully captures real business process constraints without missing edge cases.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"SDOF combines an RLHF-trained intent router with a state-aware dispatcher using finite automata to constrain multi-agent orchestration, reporting 80.9% routing accuracy and 86.5% task completion on a recruitment platform while blocking unsafe actions.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"6f16b5d1760ea970fad60e1592e8eec4e8c7ca5c6a4ac62a99657f2f18d84bf0"},"source":{"id":"2605.15204","kind":"arxiv","version":1},"verdict":{"id":"f53d7ca7-77c7-4b67-bec4-967edc16a39e","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T18:01:50.686244Z","strongest_claim":"Our GSPO-aligned 7B Intent Router achieves higher joint accuracy than zero-shot GPT-4o on this FSM-constrained adversarial routing benchmark (80.9% versus 48.9%). In end-to-end execution, SDOF reaches 86.5% task completion and blocks all 22 operations in the injection, illegal HR subset.","one_line_summary":"SDOF combines an RLHF-trained intent router with a state-aware dispatcher using finite automata to constrain multi-agent orchestration, reporting 80.9% routing accuracy and 86.5% task completion on a recruitment platform while blocking unsafe actions.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The expert-curated 185 scenarios and the Beisen iTalent platform data accurately represent general multi-agent orchestration challenges and that the GoalStage finite-automaton mapping faithfully captures real business process constraints without missing edge cases.","pith_extraction_headline":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.15204/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":25,"sample":[{"doi":"","year":2025,"title":"AgentAuditor: Safety and security evaluation for large language model agents","work_id":"e527547e-ca92-4fe0-84cb-83fa78cac2f3","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2023,"title":"Langchain: Building applications with LLMs through composability.https://github","work_id":"542b2884-59d3-4552-80b0-d5d52720aa7c","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"AgentVerse: Facilitating multi-agent collaboration and exploring emergent be- haviors","work_id":"a1aba051-38f4-4c13-a2d0-a2adf31bdf01","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2021,"title":"Cooperative AI: machines must learn to find common ground","work_id":"fed3351c-df58-41d9-ac89-7b6480095e3b","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"Agentscope: A flexible yet robust multi-agent platform","work_id":"41f8fc1e-1e31-4adb-81fa-414f73b79d41","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":25,"snapshot_sha256":"edbdc84b7204a8e01f1134a9bc4c0af25b977323831bbec05cf8fb30f5bfaec1","internal_anchors":4},"formal_canon":{"evidence_count":2,"snapshot_sha256":"b759ef96b48494f90fc79883a1a71f2604110f2f4f552ba54e2056079b36fbc2"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"f53d7ca7-77c7-4b67-bec4-967edc16a39e"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:00:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u9jCOKQfoQ8HcBFddFGC3zjqLm70Exo6ww02WewedEb2k5HOKXk70vHnXfrDEGtCUsYjFpdY45qnvCss2d1BAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T06:13:07.676886Z"},"content_sha256":"b817e4fc638315c603b2b65f6ed89e0b8046bec7e6af23db2d2b299d03feb445","schema_version":"1.0","event_id":"sha256:b817e4fc638315c603b2b65f6ed89e0b8046bec7e6af23db2d2b299d03feb445"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J276MSRKZYZD4E7PELII3T7AEU/bundle.json","state_url":"https://pith.science/pith/J276MSRKZYZD4E7PELII3T7AEU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J276MSRKZYZD4E7PELII3T7AEU/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":"2026-06-02T06:13:07Z","links":{"resolver":"https://pith.science/pith/J276MSRKZYZD4E7PELII3T7AEU","bundle":"https://pith.science/pith/J276MSRKZYZD4E7PELII3T7AEU/bundle.json","state":"https://pith.science/pith/J276MSRKZYZD4E7PELII3T7AEU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J276MSRKZYZD4E7PELII3T7AEU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:J276MSRKZYZD4E7PELII3T7AEU","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":"98f1b1c82e3214113f2157c03416f5a2de529c2313ac5a3a7cfab68915a87ca1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-20T12:51:39Z","title_canon_sha256":"2682461e28eb2548ba4359aad730a8d194755abb6fe559087bb241894b3a8491"},"schema_version":"1.0","source":{"id":"2605.15204","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15204","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15204v1","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15204","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_12","alias_value":"J276MSRKZYZD","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_16","alias_value":"J276MSRKZYZD4E7P","created_at":"2026-05-20T00:00:45Z"},{"alias_kind":"pith_short_8","alias_value":"J276MSRK","created_at":"2026-05-20T00:00:45Z"}],"graph_snapshots":[{"event_id":"sha256:b817e4fc638315c603b2b65f6ed89e0b8046bec7e6af23db2d2b299d03feb445","target":"graph","created_at":"2026-05-20T00:00:45Z","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":"Our GSPO-aligned 7B Intent Router achieves higher joint accuracy than zero-shot GPT-4o on this FSM-constrained adversarial routing benchmark (80.9% versus 48.9%). In end-to-end execution, SDOF reaches 86.5% task completion and blocks all 22 operations in the injection, illegal HR subset."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"The expert-curated 185 scenarios and the Beisen iTalent platform data accurately represent general multi-agent orchestration challenges and that the GoalStage finite-automaton mapping faithfully captures real business process constraints without missing edge cases."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"SDOF combines an RLHF-trained intent router with a state-aware dispatcher using finite automata to constrain multi-agent orchestration, reporting 80.9% routing accuracy and 86.5% task completion on a recruitment platform while blocking unsafe actions."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations."}],"snapshot_sha256":"6f16b5d1760ea970fad60e1592e8eec4e8c7ca5c6a4ac62a99657f2f18d84bf0"},"formal_canon":{"evidence_count":2,"snapshot_sha256":"b759ef96b48494f90fc79883a1a71f2604110f2f4f552ba54e2056079b36fbc2"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.15204/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-agent orchestration frameworks such as LangChain, LangGraph, and CrewAI route tasks through graph-based pipelines but do not enforce the stage constraints that govern real business processes. We present SDOF, a framework that treats multi-agent execution as a constrained state machine. SDOF operates through two primary defensive layers, implemented by three components: (1) an Online-RLHF Specialized Intent Router trained via Generative Reward Modeling (GRPO) and (2) a StateAwareDispatcher with GoalStage finite-automaton checks and precondition/postcondition SkillRegistry validation for a","authors_text":"Zhantao Wang","cross_cats":[],"headline":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations.","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-20T12:51:39Z","title":"SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch"},"references":{"count":25,"internal_anchors":4,"resolved_work":25,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"AgentAuditor: Safety and security evaluation for large language model agents","work_id":"e527547e-ca92-4fe0-84cb-83fa78cac2f3","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Langchain: Building applications with LLMs through composability.https://github","work_id":"542b2884-59d3-4552-80b0-d5d52720aa7c","year":2023},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"AgentVerse: Facilitating multi-agent collaboration and exploring emergent be- haviors","work_id":"a1aba051-38f4-4c13-a2d0-a2adf31bdf01","year":2024},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Cooperative AI: machines must learn to find common ground","work_id":"fed3351c-df58-41d9-ac89-7b6480095e3b","year":2021},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Agentscope: A flexible yet robust multi-agent platform","work_id":"41f8fc1e-1e31-4adb-81fa-414f73b79d41","year":2024}],"snapshot_sha256":"edbdc84b7204a8e01f1134a9bc4c0af25b977323831bbec05cf8fb30f5bfaec1"},"source":{"id":"2605.15204","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T18:01:50.686244Z","id":"f53d7ca7-77c7-4b67-bec4-967edc16a39e","model_set":{"reader":"grok-4.3"},"one_line_summary":"SDOF combines an RLHF-trained intent router with a state-aware dispatcher using finite automata to constrain multi-agent orchestration, reporting 80.9% routing accuracy and 86.5% task completion on a recruitment platform while blocking unsafe actions.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"SDOF models multi-agent orchestration as a constrained state machine to let a 7B router beat zero-shot GPT-4o on adversarial routing while blocking all illegal operations.","strongest_claim":"Our GSPO-aligned 7B Intent Router achieves higher joint accuracy than zero-shot GPT-4o on this FSM-constrained adversarial routing benchmark (80.9% versus 48.9%). In end-to-end execution, SDOF reaches 86.5% task completion and blocks all 22 operations in the injection, illegal HR subset.","weakest_assumption":"The expert-curated 185 scenarios and the Beisen iTalent platform data accurately represent general multi-agent orchestration challenges and that the GoalStage finite-automaton mapping faithfully captures real business process constraints without missing edge cases."}},"verdict_id":"f53d7ca7-77c7-4b67-bec4-967edc16a39e"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:abd5190535d1d7d6ce3e6d4dba8b557b392c5f93a53ccfb616e8442b6da4d642","target":"record","created_at":"2026-05-20T00:00:45Z","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":"98f1b1c82e3214113f2157c03416f5a2de529c2313ac5a3a7cfab68915a87ca1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-04-20T12:51:39Z","title_canon_sha256":"2682461e28eb2548ba4359aad730a8d194755abb6fe559087bb241894b3a8491"},"schema_version":"1.0","source":{"id":"2605.15204","kind":"arxiv","version":1}},"canonical_sha256":"4ebfe64a2ace323e13ef22d08dcfe0253f2625ccb9655806abfe5d41eedbda61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4ebfe64a2ace323e13ef22d08dcfe0253f2625ccb9655806abfe5d41eedbda61","first_computed_at":"2026-05-20T00:00:45.900309Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:00:45.900309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cNzsizSoI0+181FU04xL19C8RDMNeWGkr+Mlfic3PLYrMuHPjgJPHSKkLv+aRKq6OSdQfQBdV8gj9VKc0tmnCg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:00:45.901271Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.15204","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:abd5190535d1d7d6ce3e6d4dba8b557b392c5f93a53ccfb616e8442b6da4d642","sha256:b817e4fc638315c603b2b65f6ed89e0b8046bec7e6af23db2d2b299d03feb445"],"state_sha256":"bd9830e451eeefd3f6471573a6e48674b1c4e7275fd86716d97a84b36d6f62b4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z4tEle00AlGOLJP1HjFUIJevQ/5z3JvEsGY1Sv+YoVwGLNuou1NogWSrwsvZyInPz8CgzKG6Km5RgPSBEuSQDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T06:13:07.679452Z","bundle_sha256":"142edae1b7181020fe064f98ee02474164a7726b2870d729fbd50223bd35f7e5"}}