{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:PQZOAYSPSJH22W7QEWYSKJQF5H","short_pith_number":"pith:PQZOAYSP","schema_version":"1.0","canonical_sha256":"7c32e0624f924fad5bf025b1252605e9c571fa3cb1d7a32dc0003adedf027606","source":{"kind":"arxiv","id":"2110.06253","version":2},"attestation_state":"computed","paper":{"title":"StateAFL: Greybox Fuzzing for Stateful Network Servers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.OS","cs.SE"],"primary_cat":"cs.CR","authors_text":"Roberto Natella","submitted_at":"2021-10-12T18:08:38Z","abstract_excerpt":"Fuzzing network servers is a technical challenge, since the behavior of the target server depends on its state over a sequence of multiple messages. Existing solutions are costly and difficult to use, as they rely on manually-customized artifacts such as protocol models, protocol parsers, and learning frameworks. The aim of this work is to develop a greybox fuzzer (StateaAFL) for network servers that only relies on lightweight analysis of the target program, with no manual customization, in a similar way to what the AFL fuzzer achieved for stateless programs. The proposed fuzzer instruments th"},"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":"2110.06253","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-10-12T18:08:38Z","cross_cats_sorted":["cs.OS","cs.SE"],"title_canon_sha256":"ff6ee5d0e7fc8a6f6d64e01d965d1faeb6ecaded505151f5b2b40ed9f233866d","abstract_canon_sha256":"71be25da8e7899c1915d3e8fe567dab9dbb794fa624a1c96ab2c2f59a94cdd9a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:02:55.123773Z","signature_b64":"sT85klIEbGNswE9LIzcVTn1fZyo8Ks8WHBvRoqvqXGsYDpsG1dlH2FdeqNEFZhajJ3DHbismiF2uBORRjWwYBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c32e0624f924fad5bf025b1252605e9c571fa3cb1d7a32dc0003adedf027606","last_reissued_at":"2026-07-05T05:02:55.123238Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:02:55.123238Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"StateAFL: Greybox Fuzzing for Stateful Network Servers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.OS","cs.SE"],"primary_cat":"cs.CR","authors_text":"Roberto Natella","submitted_at":"2021-10-12T18:08:38Z","abstract_excerpt":"Fuzzing network servers is a technical challenge, since the behavior of the target server depends on its state over a sequence of multiple messages. Existing solutions are costly and difficult to use, as they rely on manually-customized artifacts such as protocol models, protocol parsers, and learning frameworks. The aim of this work is to develop a greybox fuzzer (StateaAFL) for network servers that only relies on lightweight analysis of the target program, with no manual customization, in a similar way to what the AFL fuzzer achieved for stateless programs. The proposed fuzzer instruments th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.06253","kind":"arxiv","version":2},"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/2110.06253/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":"2110.06253","created_at":"2026-07-05T05:02:55.123333+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.06253v2","created_at":"2026-07-05T05:02:55.123333+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.06253","created_at":"2026-07-05T05:02:55.123333+00:00"},{"alias_kind":"pith_short_12","alias_value":"PQZOAYSPSJH2","created_at":"2026-07-05T05:02:55.123333+00:00"},{"alias_kind":"pith_short_16","alias_value":"PQZOAYSPSJH22W7Q","created_at":"2026-07-05T05:02:55.123333+00:00"},{"alias_kind":"pith_short_8","alias_value":"PQZOAYSP","created_at":"2026-07-05T05:02:55.123333+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/PQZOAYSPSJH22W7QEWYSKJQF5H","json":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H.json","graph_json":"https://pith.science/api/pith-number/PQZOAYSPSJH22W7QEWYSKJQF5H/graph.json","events_json":"https://pith.science/api/pith-number/PQZOAYSPSJH22W7QEWYSKJQF5H/events.json","paper":"https://pith.science/paper/PQZOAYSP"},"agent_actions":{"view_html":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H","download_json":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H.json","view_paper":"https://pith.science/paper/PQZOAYSP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.06253&json=true","fetch_graph":"https://pith.science/api/pith-number/PQZOAYSPSJH22W7QEWYSKJQF5H/graph.json","fetch_events":"https://pith.science/api/pith-number/PQZOAYSPSJH22W7QEWYSKJQF5H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H/action/storage_attestation","attest_author":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H/action/author_attestation","sign_citation":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H/action/citation_signature","submit_replication":"https://pith.science/pith/PQZOAYSPSJH22W7QEWYSKJQF5H/action/replication_record"}},"created_at":"2026-07-05T05:02:55.123333+00:00","updated_at":"2026-07-05T05:02:55.123333+00:00"}