{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:24S7H46Q6QGB5WJR3ILAEZ63UP","short_pith_number":"pith:24S7H46Q","schema_version":"1.0","canonical_sha256":"d725f3f3d0f40c1ed931da160267dba3f2f5416a56492b3e461763fbf8d0ca69","source":{"kind":"arxiv","id":"2606.25189","version":1},"attestation_state":"computed","paper":{"title":"ActPlane: Programmable OS-Level Policy Enforcement for Agent Harnesses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.OS","authors_text":"Andi Quinn, Dan Williams, Quanzhi Fu, Tianyuan Wu, Tong Yu, Wei Wang, Wenan Mao, Yusheng Zheng","submitted_at":"2026-06-23T21:33:13Z","abstract_excerpt":"AI agents increasingly run in production through harnesses, the software around the LLM, including an engine that enforces safety and effectiveness policies, e.g., 'run tests before committing.' Enforcing these policies requires bridging a semantic gap: policy intent is expressed in underspecified natural language, while enforcement must act on concrete system actions, e.g., which test to run. Many policies also define event ordering or data flow actions. Yet existing approaches fall short. Tool-call guardrails miss system actions that bypass the tool layer, while OS sandboxes control resource"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.25189","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.OS","submitted_at":"2026-06-23T21:33:13Z","cross_cats_sorted":[],"title_canon_sha256":"7192bfb9d930d92a2a6900c9376c02b38fee905855b502c08631b0f937c830c0","abstract_canon_sha256":"4645801cfba3be14b5b7a9e3ec5c492ddf7217f68eeea0c8e772ec1601c573ab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T00:18:20.413665Z","signature_b64":"dkNn/RImwNquab9Dchry9hKIlEHnWDVU84l2JQ2mfK1Idc8xgbiLWRkvKChq6bJlAHbwVXrak0CrWQUNOnlCAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d725f3f3d0f40c1ed931da160267dba3f2f5416a56492b3e461763fbf8d0ca69","last_reissued_at":"2026-06-25T00:18:20.413258Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T00:18:20.413258Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ActPlane: Programmable OS-Level Policy Enforcement for Agent Harnesses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.OS","authors_text":"Andi Quinn, Dan Williams, Quanzhi Fu, Tianyuan Wu, Tong Yu, Wei Wang, Wenan Mao, Yusheng Zheng","submitted_at":"2026-06-23T21:33:13Z","abstract_excerpt":"AI agents increasingly run in production through harnesses, the software around the LLM, including an engine that enforces safety and effectiveness policies, e.g., 'run tests before committing.' Enforcing these policies requires bridging a semantic gap: policy intent is expressed in underspecified natural language, while enforcement must act on concrete system actions, e.g., which test to run. Many policies also define event ordering or data flow actions. Yet existing approaches fall short. Tool-call guardrails miss system actions that bypass the tool layer, while OS sandboxes control resource"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25189","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/2606.25189/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.25189","created_at":"2026-06-25T00:18:20.413327+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.25189v1","created_at":"2026-06-25T00:18:20.413327+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25189","created_at":"2026-06-25T00:18:20.413327+00:00"},{"alias_kind":"pith_short_12","alias_value":"24S7H46Q6QGB","created_at":"2026-06-25T00:18:20.413327+00:00"},{"alias_kind":"pith_short_16","alias_value":"24S7H46Q6QGB5WJR","created_at":"2026-06-25T00:18:20.413327+00:00"},{"alias_kind":"pith_short_8","alias_value":"24S7H46Q","created_at":"2026-06-25T00:18:20.413327+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP","json":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP.json","graph_json":"https://pith.science/api/pith-number/24S7H46Q6QGB5WJR3ILAEZ63UP/graph.json","events_json":"https://pith.science/api/pith-number/24S7H46Q6QGB5WJR3ILAEZ63UP/events.json","paper":"https://pith.science/paper/24S7H46Q"},"agent_actions":{"view_html":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP","download_json":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP.json","view_paper":"https://pith.science/paper/24S7H46Q","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.25189&json=true","fetch_graph":"https://pith.science/api/pith-number/24S7H46Q6QGB5WJR3ILAEZ63UP/graph.json","fetch_events":"https://pith.science/api/pith-number/24S7H46Q6QGB5WJR3ILAEZ63UP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP/action/storage_attestation","attest_author":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP/action/author_attestation","sign_citation":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP/action/citation_signature","submit_replication":"https://pith.science/pith/24S7H46Q6QGB5WJR3ILAEZ63UP/action/replication_record"}},"created_at":"2026-06-25T00:18:20.413327+00:00","updated_at":"2026-06-25T00:18:20.413327+00:00"}