arXiv:2606.02540v1 Announce Type: new Abstract: Agent skills occupy a privileged position in the agent workflow, as agents are expected to implicitly follow and execute them, rendering third-party skills a vulnerable attack surface. Existing studies have revealed unsafe agent behaviors induced by skill-based attacks, but they primarily evaluate poisoned skills within a single task execution and enumerate harms through ad-hoc risk lists. To bridge these gaps, we introduce SkillHarm, a benchmark of skill-based attacks across the skill-use lifecycle, paired with a systematic taxonomy of skill-rel
As AI agents become more sophisticated and integrated into workflows, the attack surface created by third-party skills is expanding rapidly, necessitating immediate attention to security vulnerabilities.
This benchmark highlights a critical and under-addressed security flaw in autonomous AI systems, which could lead to significant financial, reputational, or operational damage for organizations relying on agentic AI.
The focus shifts from ad-hoc risk assessments to a systematic, lifecycle-aware approach for identifying and mitigating skill-based attacks on AI agents, making the development and deployment of secure AI agents more complex but essential.
- · AI security firms
- · Developers of secure agent architectures
- · Ethical hackers
- · Organizations with unhardened AI agent deployments
- · Developers of insecure third-party AI skills
- · Bad actors exploiting unpatched vulnerabilities
Companies will need to invest more in AI security research and implement stricter vetting processes for agent skills.
A new industry for AI agent security audits and 'skill hardening' services will emerge to address these vulnerabilities.
Regulatory bodies may begin to mandate security standards for AI agent deployment, similar to cybersecurity regulations for other software.
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