Harmless Yet Harmful: Neutral Prompting Attacks for Stealthy Hallucination Steering in Agent Skills
arXiv:2605.29354v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly participate in software development workflows by generating code, selecting dependencies, and producing package installation commands. This creates a new software supply chain risk: when an agent hallucinates a non-existent package, an attacker may register the hallucinated name and later compromise users who install it. Existing package hallucination attacks and defenses primarily focus on naturally occurring hallucinations, targeted dependency steering, or post-hoc package validation. In this paper, we i
The increasing integration of LLM-powered agents into critical software development workflows makes this vulnerability immediately relevant.
This research highlights a novel and stealthy attack vector leveraging AI hallucinations, posing a significant supply chain risk for any organization using AI agents in code generation.
The understanding of AI agent security shifts to include active manipulation of hallucinations as a threat, beyond passive or naturally occurring errors.
- · Cybersecurity firms developing AI security solutions
- · Security researchers focusing on AI agent vulnerabilities
- · Organizations with robust software supply chain security practices
- · Organizations relying heavily on unsupervised AI agents for coding
- · Developers with inadequate package validation processes
- · End-users of compromised software
Increased focus on hardening AI agent-generated code and dependencies through better validation.
Development of new AI trust and verification layers specifically designed to detect and mitigate hallucination steering attacks.
Broader regulatory push for 'AI safety by design' in software development, potentially leading to new compliance standards.
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