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Prior mitigations, including developer training, static analysis tools, and domain-specific template languages, each face diminishing returns; AI code generation inherits these limitations and introduces new ones, reproducing insecure patterns from training data and lacking reliable context for self-correction.\n  This paper introduces a general framework for secure content composition that extends across content languages and integrates directly into general-pur"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"This paper introduces a general framework for secure content composition that extends across content languages and integrates directly into general-purpose programming languages via additive changes to string expression syntax.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That practical compilation strategies exist which achieve static analyses specified in terms of dynamic semantics while delivering runtime performance approaching naive string concatenation and useful developer diagnostics.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A language-integrated framework for compile-time analysis of sensitive string producers that minimizes lexical distance between secure and insecure idioms.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A general framework for secure content composition integrates into general-purpose languages through small changes to string syntax.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"55c4f77edb6ae1881c48c341a560792136be40ea14e7f5848e4a9b732c7c20d1"},"source":{"id":"2605.16561","kind":"arxiv","version":1},"verdict":{"id":"65961ecb-fc69-4ba0-9241-271bca1e0b3f","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T21:19:17.117335Z","strongest_claim":"This paper introduces a general framework for secure content composition that extends across content languages and integrates directly into general-purpose programming languages via additive changes to string expression syntax.","one_line_summary":"A language-integrated framework for compile-time analysis of sensitive string producers that minimizes lexical distance between secure and insecure idioms.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That practical compilation strategies exist which achieve static analyses specified in terms of dynamic semantics while delivering runtime performance approaching naive string concatenation and useful developer diagnostics.","pith_extraction_headline":"A general framework for secure content composition integrates into general-purpose languages through small changes to string syntax."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.16561/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T21:31:19.467773Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T21:31:17.432288Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T19:21:56.882822Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.626643Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"d4249c36c336526aadb23df025c1e6aed8f7761bc32d4f4e28dd294f4d1bfc01"},"references":{"count":24,"sample":[{"doi":"","year":2011,"title":"Anonymous Authors. 2011. 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