{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:MS46RE6H4LYBPOHMUJ4A55SL2O","short_pith_number":"pith:MS46RE6H","schema_version":"1.0","canonical_sha256":"64b9e893c7e2f017b8eca2780ef64bd3bb9952edca623d8c7f08c1b62e4eee27","source":{"kind":"arxiv","id":"2410.02828","version":1},"attestation_state":"computed","paper":{"title":"PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CR","authors_text":"Amanda J. Minnich, Blake Bullwinkel, Bolor-Erdene Jagdagdorj, Chang Kawaguchi, Charlotte Siska, Christian Seifert, Gary D. Lopez Munoz, Joris de Gruyter, Katherine Pratt, Martin Pouliot, Nina Chikanov, Pete Bryan, Raja Sekhar Rao Dheekonda, Ram Shankar Siva Kumar, Richard Lundeen, Roman Lutz, Shiven Chawla, Tori Westerhoff, Whitney Maxwell, Yonatan Zunger","submitted_at":"2024-10-01T17:00:59Z","abstract_excerpt":"Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both single- and multi-modal models. As the GenAI ecosystem matures, the need for extensible and model-agnostic risk identification frameworks is growing. To meet this need, we introduce the Python Risk Identification Toolkit (PyRIT), an open-source framework designed to enhance red teaming efforts in GenAI systems. PyRIT is a model- and platform-agnostic tool that enables red teamers to probe for and identify novel harms,"},"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":"2410.02828","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-10-01T17:00:59Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"4e25dcf5c531c73528363ad77971eb4f2cd0bf427a6aecd8e555dcec06153400","abstract_canon_sha256":"c75e10865513e7619b31a7c28e46f3295415082f6124e1398f10413770ef4ddb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:15:40.458986Z","signature_b64":"JLor0jvUeyohitrsQ8vYhIWxzV1LMoFYPbcKY21ulQdPEBunJ1UblvTN1RoFe2GugvOtCXoQn6dhMoO9QpqFAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64b9e893c7e2f017b8eca2780ef64bd3bb9952edca623d8c7f08c1b62e4eee27","last_reissued_at":"2026-07-05T09:15:40.458548Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:15:40.458548Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CR","authors_text":"Amanda J. Minnich, Blake Bullwinkel, Bolor-Erdene Jagdagdorj, Chang Kawaguchi, Charlotte Siska, Christian Seifert, Gary D. Lopez Munoz, Joris de Gruyter, Katherine Pratt, Martin Pouliot, Nina Chikanov, Pete Bryan, Raja Sekhar Rao Dheekonda, Ram Shankar Siva Kumar, Richard Lundeen, Roman Lutz, Shiven Chawla, Tori Westerhoff, Whitney Maxwell, Yonatan Zunger","submitted_at":"2024-10-01T17:00:59Z","abstract_excerpt":"Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both single- and multi-modal models. As the GenAI ecosystem matures, the need for extensible and model-agnostic risk identification frameworks is growing. To meet this need, we introduce the Python Risk Identification Toolkit (PyRIT), an open-source framework designed to enhance red teaming efforts in GenAI systems. PyRIT is a model- and platform-agnostic tool that enables red teamers to probe for and identify novel harms,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02828","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/2410.02828/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":"2410.02828","created_at":"2026-07-05T09:15:40.458608+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.02828v1","created_at":"2026-07-05T09:15:40.458608+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02828","created_at":"2026-07-05T09:15:40.458608+00:00"},{"alias_kind":"pith_short_12","alias_value":"MS46RE6H4LYB","created_at":"2026-07-05T09:15:40.458608+00:00"},{"alias_kind":"pith_short_16","alias_value":"MS46RE6H4LYBPOHM","created_at":"2026-07-05T09:15:40.458608+00:00"},{"alias_kind":"pith_short_8","alias_value":"MS46RE6H","created_at":"2026-07-05T09:15:40.458608+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":9,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.03136","citing_title":"PsychoPass: Geometric Profiling of Multi-Turn Adversarial LLM Conversations","ref_index":19,"is_internal_anchor":false},{"citing_arxiv_id":"2606.31227","citing_title":"Securing the AI Agent: A Unified Framework for Multi-Layer Agent Red Teaming","ref_index":21,"is_internal_anchor":false},{"citing_arxiv_id":"2510.09093","citing_title":"Exploiting Web Search Tools of AI Agents for Data Exfiltration","ref_index":22,"is_internal_anchor":false},{"citing_arxiv_id":"2605.12702","citing_title":"DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2605.12869","citing_title":"Quantifying LLM Safety Degradation Under Repeated Attacks Using Survival Analysis","ref_index":10,"is_internal_anchor":false},{"citing_arxiv_id":"2604.27997","citing_title":"When and How AI Should Assist Brainstorming for AI Impact Assessment","ref_index":76,"is_internal_anchor":false},{"citing_arxiv_id":"2605.04019","citing_title":"Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours","ref_index":3,"is_internal_anchor":false},{"citing_arxiv_id":"2605.05058","citing_title":"SoK: Robustness in Large Language Models against Jailbreak Attacks","ref_index":56,"is_internal_anchor":false},{"citing_arxiv_id":"2604.20833","citing_title":"AVISE: Framework for Evaluating the Security of AI Systems","ref_index":3,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O","json":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O.json","graph_json":"https://pith.science/api/pith-number/MS46RE6H4LYBPOHMUJ4A55SL2O/graph.json","events_json":"https://pith.science/api/pith-number/MS46RE6H4LYBPOHMUJ4A55SL2O/events.json","paper":"https://pith.science/paper/MS46RE6H"},"agent_actions":{"view_html":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O","download_json":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O.json","view_paper":"https://pith.science/paper/MS46RE6H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.02828&json=true","fetch_graph":"https://pith.science/api/pith-number/MS46RE6H4LYBPOHMUJ4A55SL2O/graph.json","fetch_events":"https://pith.science/api/pith-number/MS46RE6H4LYBPOHMUJ4A55SL2O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O/action/storage_attestation","attest_author":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O/action/author_attestation","sign_citation":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O/action/citation_signature","submit_replication":"https://pith.science/pith/MS46RE6H4LYBPOHMUJ4A55SL2O/action/replication_record"}},"created_at":"2026-07-05T09:15:40.458608+00:00","updated_at":"2026-07-05T09:15:40.458608+00:00"}