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Integrity report for Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2607.06963 · pith:2026:Y5HDU2XSHLBXBNOMCGWPFLI2R5

1Critical
0Advisory
5Detectors run
2026-07-09Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

cited_work_retraction completed v1.0.0 · findings 0 · 2026-07-09 19:19:11.092463+00:00
ai_meta_artifact completed v1.0.0 · findings 0 · 2026-07-09 08:49:17.643888+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-07-09 08:21:48.558002+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-07-09 07:30:57.197991+00:00
doi_compliance completed v1.0.0 · findings 1 · 2026-07-09 07:18:04.888225+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/Y5HDU2XS/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.