{"as_of":"2026-08-20T18:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1fde7e6775b031a1c453b6d1b9b78efa905edcfbfd930faff0b5b3607a605e07","coverage":[{"denominator":73,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":73,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T20:34:32.366757Z","state":"measured"},{"denominator":73,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":73,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.19023/citation-record","integrity":"/paper/2606.19023/integrity","json":"/paper/2606.19023/citation-record.json","paper":"/paper/2606.19023"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:d6491d7d7ec6d89f8ee4443ac5a0b9aa8ac0f15f0e0f5da6ebcaece8ceadb3e2","observation_id":"8cacceb5-b55f-4a08-a6de-75a50f79fac6","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Malware Dynamic Analysis Eva- sion Techniques: A Survey.ACM Comput","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:3fc48d801d22f57bc6175ab292b43de5ea7ee42dca7654290f5c67de56acb0a1","observation_id":"37414afd-3b3e-4ce2-af7f-6206fa566bd3","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"A Comprehen- sive Review on Malware Detection Approaches.IEEE Access, 8:6249–6271, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:db4d49887c00dc1938016cddbb9415dd0cbedfb831864ecf6b973095483a6455","observation_id":"5cf55514-66e5-4c11-b851-6b447b65d25a","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Wild patterns: Ten years after the rise of adversarial machine learning.Pattern Recognition, 84:317–331, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:c05256b88a480c759ddf75c06079a92bc88ca3d7945ccc5a1d914a75fc69b1f0","observation_id":"c3b04fb5-6c50-4e01-8275-5efc64778036","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Bridges, Tarrah R","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:5cad3fb5dcb569610529dd3e79bf4fcb05587e5fe66af5d3774f346fdf648195","observation_id":"d4ce41e4-b6d0-406e-a5a8-f37befc3159b","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Hugging face and virustotal collaborate to strengthen ai security","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:9878675e43dffbe676b0a8bbca9bc205b343dc645749c9b0e89a5bf15696e134","observation_id":"ffef0d9d-127c-4af7-8227-ff8430ce96cd","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04490","last_updated":"2024-10-06T14:09:54Z","snapshot_observed_at":"2026-08-19T03:09:42.075176Z","submitted_at":"2024-10-06T14:09:54Z","title":"A Large-Scale Exploit Instrumentation Study of AI/ML Supply Chain Attacks in Hugging Face Models","version":1},"cited_work":{"arxiv_id":"2410.04490","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04490","snapshot_observed_at":"2026-07-04T01:09:19.761353Z","title":null,"venue":null,"work_id":"612004e2-0985-4f65-a3ce-4e6e1d808707","year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"cited_paper":"/paper/2410.04490","citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:6cb239e19fb8e2b785e6d9cf955d76e79b3d781575891e86c490b4c94f3b3a04","observation_id":"cda18d74-c60a-4626-a026-cbadd7fbbe15","resolution":{"observed_at":"2026-07-04T01:09:19.763275Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Towards an understanding of anti- virtualization and anti-debugging behavior in modern malware","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:16e49b83e49bd52d7f6ddf462005ddba4fff020c30571f6559bad33e162d3398","observation_id":"29b7f0ca-ed13-4aa4-bdf1-508f3ceed67f","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Keras, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:e031b50de2d403366f2fe159a99c232fd5598adcb16dca705146dab28517c8d9","observation_id":"5a28fe2d-9c13-4a1a-9aa7-f0ccbccfec96","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"ClamA V: Open-Source Antivirus Toolkit","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b2e0faafe0666030b4fc5ac6699e34bfd3abab6c574daddb05a9655020250c3c","observation_id":"00f9e727-5619-423d-8efd-71b8d4f0047f","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2024-3660","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:33e1fe1a95b718112d23a58a726c8b52d18877f1abde6599d3a127bdddc9472a","observation_id":"b47735ac-413d-4857-93f2-28bd883af92b","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-12058","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:804e3c29396c55740ea7396bbb1eed6247dddad45ec9a3b322e45f6225d89b75","observation_id":"9e7dc78a-3554-42b1-953b-a6ed6420db0f","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-1550","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:7ace079a26d4b86b2c9dcf2734376072777d0bc5f3f41ad9f5c70442f297e714","observation_id":"81865d36-b195-4759-bc1c-82284b1cc8d6","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-32434","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:ab92a1f03124a38d08a2d312935b4befa7ed4ac21b623ac55803244667f80779","observation_id":"475aa3ec-2451-4700-85c3-5b1bfb805271","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-49655","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:3b2a7522ad2d189e38e6aefdd075ecac308485e53e98f796b135d6113f166c01","observation_id":"de7cd025-a66f-4ead-9fdc-be72ba7e637c","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-8747","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:0d68739724317117aa8b003a4f1fda1545dcd9eb69371155c91f5a0a0e317442","observation_id":"033b2247-0923-427f-aec8-796241ad715c","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-9905","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:941e7215578a7866f807481e2f8c55a2c9386fb04ab65b3ae8cd0f77c0298088","observation_id":"8e8024b4-98c7-4bf2-b226-d29f1438c61c","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-9906","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:42f0c276551cd02f9f10192f8b712f080b60ef6276f8b69a551c72d2a863b357","observation_id":"626f7f0e-45b7-4cd5-a6fb-ed449be41a69","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"CVE-2025-1550 - Bypassing Keras safe_mode for Arbitrary Code Execution","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:11c9d1cf298ea1eef9843f66200ce9f1860d92f47cd1b61ef97b63563eeb09a1","observation_id":"ab053ef2-5f8e-4d5d-8c5b-0fc97235c8f6","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:ace324be61f3595228e510e9c6351cc378dae30709e27467517161b9e54fa964","observation_id":"ecbea3b8-95a9-44a1-ab35-d20dda9d3cc4","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"parse_uncertain"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"libdebug: Build Your Own Debugger","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:0becb16588827638bc1111d51c4e72d7bc4c5c05e997016d9d96ffade3ee2abf","observation_id":"acb2d743-463d-4172-ac61-1c824a68bd55","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Poster: lib- debug, Build Your Own Debugger for a Better (Hello) World","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:26a986d7784c12e58667f96d31ba78da162eec19c025fd976656f4bfcd5a3255","observation_id":"ce81add5-ba0b-4d1f-a497-bb1b2123602c","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"On the (In)Security of Loading Machine Learning Models","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:575534756dc44ce1509df4fd500323fa7ff1b27d26287297802fd2177f021aef","observation_id":"d4a05547-0bbb-412d-9521-76a4125ef0e7","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Towards Measuring Supply Chain Attacks on Package Managers for Interpreted Languages","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:d78250e3cba820195e3f3b2320ebd9fc2c3469304f2ce432d52be5d2a6f8f562","observation_id":"38f6d2ad-e57d-459f-811f-edd439d76ff8","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"A survey on automated dynamic malware-analysis techniques and tools.ACM Comput","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:d3145060814fbdef86bd1701ec12bc156654f66a46b4bfbd6900b2fa84aaf644","observation_id":"1cd695c0-5496-4759-ae84-bcf3ae3393b0","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Falco: Cloud Native Runtime Security","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:7c61c8a47e54a9805a5ed9af33055a065508751f7f96d492ca72e61989dfdc27","observation_id":"ba0e6679-3834-4719-8f51-f5a85d3f1423","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Forrest, S.A","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:ea039c8d2ad1c4ff728d0be48dbbf79f137d344e7fbe5c8f0f32767ff9cd0ebd","observation_id":"2b4d2afb-da9e-4a5b-8c77-6a57d573456e","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b8447522d488a3e08eb8c49d1e6a5d42a14aa5905696a4f856c333b25b2160ef","observation_id":"4e76b563-698a-403b-9377-86b823b25735","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Install TensorFlow with pip","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:a250cce0741e2c36759a228ea49c04f4c8ae8b5c25c604ce8f82da0a2282e356","observation_id":"8c2cef53-3875-4334-a539-a8c6311e090f","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"TensorFlow Hub: Reusable Machine Learning Modules","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:12da8c28df97df0d0dd4be1083157dbab3249e3aa96ec5fdab582a65a3cdaec4","observation_id":"5c3b6e21-cb1c-47f0-97cf-657a66c5bbb1","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Security and Pickle Files — Hug- ging Face Hub Documentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:6ca9914bce736ff5a4ade67d7b83846dbfca5014002e3663dd469b6009dea2d9","observation_id":"42091141-3836-419c-b33a-8398459ec9ca","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Hugging Face Hub Documentation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:73e05552daafb9388761e3bb6783a007c5606bae47aa8d47a6f02537a994043a","observation_id":"bfca1424-8021-45cc-8c1a-432e78d52619","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Python Developers Survey 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:2fd5f6c54eb731fe1985bb77327c995af49157e6ab2ff996525e4492085576a1","observation_id":"58f72924-fc19-4b50-b3e0-5cbf89a7cd99","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Software Supply Chain Solutions for DevOps and Security — JFrog","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:f7f1f12fe3f40e7a4b82f93b273a446382f5388aeb5286b8df90349744045950","observation_id":"ac8a7318-343c-4e2b-ba69-a14b2eec5c74","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b4ec17c90a665d3d787041728d3c4bb150ac1e22ba91dcbbbd264c479d72c58b","observation_id":"bf54ef54-4e3e-4d0b-a979-ea680ac1de4f","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Schorlemmer, George K","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:61e9e252dbfb8d2e9efac493b0f12d395187cf48b3b72d101b6f44c0b8babc3b","observation_id":"2de3cee8-40ba-41da-9dd3-e004dbe696c8","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Safe Harbor or Hostile Waters: Unveiling the Hidden Perils of the TorchScript Engine in PyTorch","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:0920ca5d8e609b952d250e82d1a338f8e67f8cda0276de8e46f8657b567d9425","observation_id":"b61ed9c5-d29f-4989-8482-9a68691f983e","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Kaggle Models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:733c6076c51a70cc6376a9e1af4f66430dd14e1992c62c3a3e9aa9e34d1f5bb2","observation_id":"4d135df3-dca6-4b6a-916c-ef2494c1c8cd","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Kellas, Neophytos Christou, Wenxin Jiang, Penghui Li, Laurent Simon, Yaniv David, Vasileios P","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b8b4c02204be0445706e537b1deee997a362de9636fcf12ef486544a4a1e0275","observation_id":"1568e44c-6cef-46d3-b4f7-5562e61982d8","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Serialization and Saving — Keras Documentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:f698642611ccf2cc040daffe16dc95deed25a172d6fd59924abb0e24dea4860a","observation_id":"c937c41a-3ed3-4439-b7e4-5dba0dbfab38","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Model Training APIs — Keras Doc- umentation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:ea7eca4d8f1b1e8b6a1709a2e3697416a1b1a6dab3712a9d24f45356cb0b7734","observation_id":"c82a5fa6-024d-4484-bde9-ccb2dc082076","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Whole model saving & loading - Keras","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:5b41b4b6ac78486e995d08367f6fbe847af52a3f817a4ffc25aecfe4e155fca6","observation_id":"fe8fdf1f-e98f-4d17-8493-6fec1915f535","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"SoK: Taxonomy of Attacks on Open- Source Software Supply Chains","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:84e2e681da61a56a015911d55b576a49c4cbfe0b1a903533822aa6a5fa215011","observation_id":"e99f2b27-fe2e-4af7-b768-5c6f7522d3c8","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"ptrace(2) — Linux manual page","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:34928af85bbdc97087c0381b0091289a621ec5c64a581bfb6fe273e217b1ba83","observation_id":"21d68e5c-54f6-41b7-8310-26ae45f1b254","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"seccomp(2) — Linux manual page","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:1c8eb0beddbc0419176ce476bd381a3c67e39435ad08cc6fe44dbb0f366c83a8","observation_id":"8e74e780-9788-443f-b2a3-740e95e6330a","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"The art of hide and seek: Making pickle-based model supply chain poisoning stealthy again, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:45d42a44b94f47f4b9d7ed04ed8be6a670d5bf7e692ccc7c3e3d6e9745c08f71","observation_id":"4469d9ae-d5ae-4587-af57-f969edcb2fec","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Position: Machine Learning Models Have a Supply Chain Problem","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:cd413f95f1cb65dcab164788a0f0a90f25ae53561348ebebd819545981ebc78b","observation_id":"10c50a6d-a0b1-47cf-a2ed-2cc10a279941","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Sysmon for Linux","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:dcb8e9e42758a84fcad2bb0a7fe897abd3f0de464559509c71fac9c56f050ea5","observation_id":"ded1f9ca-eb33-4907-9777-8d23ff35670e","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Sysmon v15.15","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b84f4205dbb6b6c6c35ec1f1027c866e29e232939ef3c26400befa412f31d91a","observation_id":"f1660560-b77e-483e-a4db-6de109854abc","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"2022 Kaggle Machine Learning & Data Science Survey","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:85c78366c02a3b6ec7b8075860c744f50542a0b29d17aa3e728c16a91a0c10c3","observation_id":"280c8e89-0083-461d-bd04-402877f3dd7b","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"4M Models Scanned: Protect AI + Hug- ging Face 6 Months In","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:9f923e6c719fc059c019967453016fc72fde106b9523c4a03e2f864d10506d1c","observation_id":"c88ec31e-8faa-4c39-a225-b26ebca2cdf4","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Backstabber’s Knife Collection: A Review of Open Source Software Supply Chain Attacks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:1902f7c879d4a2ea8f439c282ef682b09d78e766ae1f6c061583205ebf1fef15","observation_id":"86a9bd5c-06fd-4268-a552-7a6cd6630530","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Loading Models, Launching Shells: Abusing AI File Formats for Code Execution","venue":null,"work_id":null,"year":2033},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:3255ce9ee3e57bcaf11fdd1e8c8937a488d2bddf15d3e49613477450f66350a1","observation_id":"bc2972c3-dfd8-4bda-872a-0cc35f677194","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"TESSERACT: Eliminating Experimental Bias in Malware Classifica- tion across Space and Time","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:54d194bdfdaaead620641d4f06893a1bdb3e90bf04130b56e53fc839b04de0af","observation_id":"287b4b1a-af68-408c-8904-8e94f9505dee","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"ModelScan: Open source protection against model serialization attacks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:4a348a6de1c0b7f4849e5b0e6fa1f1a37ba778d416325b93a99f6c973c3c8cd5","observation_id":"a75de857-0f22-4b66-9128-e2ad2698e003","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Protect AI — The Platform for AI Security","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:41cb4f2342d51bfaae7aa5fefd62cd3c615c033d173a3ed572fe80be39bc7260","observation_id":"a97f6be1-c09b-4dea-9fde-bcf5cae1a6eb","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"pickle — Python object serialization","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:931960581d0e1993c1f9923322dcceaef012a264b7744033b7bdb6b4b4f04f4d","observation_id":"aecfa8cb-7958-440c-b8bc-e183f08ef532","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Serialization semantics — Py- Torch Documentation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:0a03b61165ac9b545da1e07bd437e4d6dc3fa5d3a6fdb74d0922b2545af636a3","observation_id":"3db25ef3-7d4d-49d4-bf9b-d820efbd9879","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Save and Load the Model — Py- Torch Tutorials 2.7.0+cu126 documentation","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:dac152cb6af746d8896afe1449090dd5ce1a67b7e8e165192d49fcb96ada6ade","observation_id":"538215c3-e8f8-4eeb-b15b-2b4f3bb046fb","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"PyTorch Hub","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:f966718f6f8a3f36d73d3d2cf7c96e06675a12ac7a5415a328c5ee25a355d5ac","observation_id":"bf994565-1a3b-4e10-abf2-76bda9711680","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"A systematic literature review on host-based intrusion de- tection systems.IEEE Access, 12:27237–27266, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:ca0e994e8443478b55ede4980e52bc6bbf2a7bb1f71d834847754b32911e1d73","observation_id":"3f993145-4148-4c2c-9270-3c202aaddfe3","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Extended berkeley packet filter: An application perspec- tive.IEEE Access, 10:126370–126393, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:9ccc8ec0f0f1712545d735379b6c13af09039f9f80e43b5ed9255965533a25db","observation_id":"18f53721-5850-457b-9818-326c52ae3987","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Sysdig: Cloud Security Starts at Runtime","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:0f4ef1a20ddefbed70459353cebab32be37731081358c9653f261952e1426475","observation_id":"ec730e5d-e9cc-461c-a336-9fb0011a9a38","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"SavedModel format guide — TensorFlow Documentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:5e34dfe9e04fee25a69e0b96979d347f1c8511e69d68fa920699487787575ada","observation_id":"b30abfce-a6fd-4fff-aa3f-ae6f72712b8a","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Training checkpoints — Ten- sorFlow Documentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:d21cb95b66250fd605ab6ff45819d834151d7c1297ad092b28096102281de384","observation_id":"12d08203-bd91-45b2-bea6-3939de02550c","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"tf.keras.models.load_model — TensorFlow API Documentation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:9debe225e4d705d9adf1f6db8d6a23c3620e5e1ea459c6d24fbdbde4449f6578","observation_id":"4f54f239-4af3-4842-9de8-3599d8f73d2e","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"TensorFlow I/O: Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:9bfb33ed1f73ddd7338e802c4a4edc11e475f558ca911ddd5000cc4ce8224311","observation_id":"4c7b2adf-425a-429d-a9e5-6c82b08210bf","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"TensorFlow Security Policy","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:d62c4d39f941edb084477dc251554a5e0b031f76b680354e0fe5615f8fa62faf","observation_id":"109132fa-c5ce-41a1-8bb1-aa4f67140249","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Fickling: A Tool for Manipulating and Analyzing Python Pickle Programs","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:b14f7c88e6abc3a65f7105417e40bf7a088e1308a56c3133df6bf6110f127d05","observation_id":"eaff2b94-f885-4351-b09b-6569c9e429c5","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"VirusTotal","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:5e17e0b2b396e3a72aa62eb75ad18afd33aa676efd0b5e6c3d76a00764d94e2c","observation_id":"f5dbc45d-2006-408b-8b2f-86580f48b739","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Linux Security Mod- ules: General Security Support for the Linux Kernel","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:95b7d98d07e19f76d58483f1e09a9d444912ae7cfb8cfacf9cfaf56b33b941a9","observation_id":"2a490bf5-5e2a-4a2b-b1fb-7a2e2e3ee671","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"Models Are Codes: Towards Measur- ing Malicious Code Poisoning Attacks on Pre-trained Model Hubs","venue":null,"work_id":null,"year":2087},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:a2a7d8f256350fa06c2beb2fa74c7d7db14e015a4341f123c3c6b38d7d10d363","observation_id":"7d5905ec-106e-4183-af0e-a61f7f407c2e","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-26T20:34:32.366757Z","title":"outside the standard library","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-06-26T20:34:32.366757Z"},"links":{"citing_paper":"/paper/2606.19023"},"observation_digest":"sha256:423d428788603fa4393b274fafabfd47773fa28c554687eb0e5d48d75dea6533","observation_id":"1d6b9020-a078-447c-a493-5ef4ecd6fc50","resolution":{"observed_at":"2026-06-26T20:34:32.366757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.19023","last_updated":"2026-06-17T12:49:22Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-09T19:44:12.563481Z","submitted_at":"2026-06-17T12:49:22Z","title":"Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution"},"reference_resolution":{"displayed":73,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":71,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":73},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2606.19023."}