Skip to content
aiqbench takeAI Safety

aiqbench analysis

This paper provides a rigorous formal analysis of supply chain security risks specific to agentic AI skills, correcting previous claims regarding malicious tool counts and vulnerability severity with verified experimental data. By offering an open-source verification harness alongside corrected theorems on information flow analysis, it establishes essential baselines for securing autonomous agent ecosystems against sophisticated attacks like token exfiltration.
Sources coveringarXiv, LessWrong, Analytics Vidhya, AI Alignment Forum
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Formal Analysis and Supply Chain Security for Agentic AI Skills

arXiv2 min read

arXiv:2603.00195v2 Announce Type: replace-cross Abstract: 32 pages, 5 theorems with full proofs, 68 references, open-source tool: https://github.com/qualixar/skillfortify. v2: corrects the bibliography (22 entries had author lists that did not match the papers at the cited arXiv identifiers; all verified against the arXiv API and corrected, and affected authors notified) and three external claims against primary sources: MalTool reports 1,300 standalone and 5,727 embedded malicious tools, not 6,487; CVE-2026-25253 is authentication-token exfiltration via an unvalidated gatewayUrl, credited to depthfirst and fixed in 2026.1.29, not remote code execution through a crafted skill package; ClawHavoc counts are 341, later 824, and 1,184 by source and date, not "over 1,200". All experiments re-measured against the released v0.6.0 implementation using harnesses now committed to the repository. E1/E2 unchanged (F1 96.15%). E3 reverses to a negative result: information flow analysis adds no detections over pattern matching on this corpus. The soundness theorem's scope is stated explicitly and no longer conflated with the zero false-positive rate.

Abstract:32 pages, 5 theorems with full proofs, 68 references, open-source tool: this https URL. v2: corrects the bibliography (22 entries had author lists that did not match the papers at the cited arXiv identifiers; all verified against the arXiv API and corrected, and affected authors notified) and three external claims against primary sources: MalTool reports 1,300 standalone and 5,727 embedded malicious tools, not 6,487; CVE-2026-25253 is authentication-token exfiltration via an unvalidated gatewayUrl, credited to depthfirst and fixed in 2026.1.29, not remote code execution through a crafted skill package; ClawHavoc counts are 341, later 824, and 1,184 by source and date, not "over 1,200". All experiments re-measured against the released v0.6.0 implementation using harnesses now committed to the repository. E1/E2 unchanged (F1 96.15%). E3 reverses to a negative result: information flow analysis adds no detections over pattern matching on this corpus. The soundness theorem's scope is stated explicitly and no longer conflated with the zero false-positive rate.

Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Software Engineering (cs.SE)

D.2.4; D.4.6; I.2.11; K.6.5

arXiv:2603.00195 [cs.CR]

(or arXiv:2603.00195v2 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2603.00195 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.5281/zenodo.18787662 Focus to learn more DOI(s) linking to related resources

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 269 words

Related coverage