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Paper finds trojan risk in LLM steering-vector plugins

Original title: Steering for Safety, Hijacking for Profit: Trojan Threats in the LLM Activation Steering Supply Chain

arXiv cs.CRby Yu Yan ()1 min read
AI summary · x-ai/grok-4.7Summaries by Vani AI

Authors say plugin IDH reached up to 97.8% attack success on five LLMs while keeping high refusal rates.

A paper audits eight open-source steering-vector plugin libraries and reports weak distribution checks, excessive privileges, and no runtime monitoring. The authors introduce IDH, a plugin that pairs safety-refusal steering with commercial recommendation manipulation through norm-gated routing and automatic layer selection. They also propose a runtime defense that suppresses anomalous activation changes and orthogonalizes inter-layer trajectories. Tests covered five LLMs and six brands in three commercial domains.

Unconfirmed: The 97.8% success rate and library weaknesses are author-reported findings, not confirmed real-world incidents.

Key facts
  • The audit covered eight mainstream open-source steering libraries.
  • IDH uses safety-refusal steering as its claimed legitimate function.
  • The hijack goal is commercial recommendation manipulation.
  • Reported peak attack success is 97.8% across the evaluated setup.
  • Experiments span six brands and three commercial domains.
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From the original article

1 min read at arxiv.org

As large language models (LLMs) are increasingly integrated into Web search, online recommendation, and intelligent decision-making, the third-party plugin ecosystem centered on model customization continues to grow. Among these, Steering Vectors guide model behavior by intervening in internal representations.

arXiv cs.CR

By Yu Yan · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.