DatasetPublic With Caveat
AI Security arXiv Corpus 2026
Canonical State 2026 AI-security-tagged arXiv corpus.
July 20, 2026Open
Start with the pressure: sales, launch, abuse, agents, data, or guardrails
Statistic
AI-security-tagged papers in the State 2026 research corpus.
Connected intelligence
Canonical State 2026 AI-security-tagged arXiv corpus.
2,730
Legacy AI-security paper count
Superseded by the canonical State 2026 research corpus.
3,411 of 10,152 unique arXiv papers in the current pull are strict AI-security papers, already naming concrete work in prompt/generation security, agentic action security, model and ML attack security, governance assurance, privacy protection, MCP/tool-use security, and red teaming.
Only 8 Wikimedia pages are narrowly tagged AI-security-specific against a field with 3,411 strict AI-security arXiv papers and 437 classified GitHub repos — there is no canonical public reference for AI security engineering as a practice.
Differential privacy and privacy-preserving ML remain active arXiv research terms (112 and 32 papers in the current pull), but privacy still appears in hiring language mainly as a GDPR/compliance checkbox rather than a named engineering capability.
What companies really mean by AI Security Engineer and why the operating model is lagging the technology.
arXiv puts only 1.99% of papers (202 of 10,152) in detection and runtime monitoring, and media coverage of AI cyber defense is just 0.9% of volume (486 of 53,865 items) — among the least-researched and least-covered AI security topics.