pith:BV5INSAK
Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale
More than one in four AI agent skills contain at least one security vulnerability.
arxiv:2601.10338 v1 · 2026-01-15 · cs.CR · cs.AI · cs.CL · cs.SE
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Claims
26.1% of skills contain at least one vulnerability, spanning 14 distinct patterns across four categories: prompt injection, data exfiltration, privilege escalation, and supply chain risks. Data exfiltration (13.3%) and privilege escalation (11.8%) are most prevalent, while 5.2% of skills exhibit high-severity patterns strongly suggesting malicious intent.
That SkillScan's static analysis plus LLM semantic classification accurately flags real vulnerabilities at the stated precision and recall without significant selection bias in the 31,132 analyzed skills or over-representation of risky marketplaces.
26.1% of analyzed AI agent skills contain vulnerabilities across 14 patterns, with executable scripts raising risk 2.12x, based on static and LLM analysis of 31k skills.
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| First computed | 2026-05-17T23:39:19.831777Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BV5INSAKZCOC4HDWOVTUZ35OJ2 \
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# expect: 0d7a86c80ac89c2e1c7675674cefae4e8e32bd4585ec730df12ea994b8af1ff5
Canonical record JSON
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