benchmark 2026

Analysing the Safety Pitfalls of Steering Vectors

Yuxiao Li , Alina Fastowski , Efstratios Zaradoukas , Bardh Prenkaj , Gjergji Kasneci

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Published on arXiv

2603.24543

Prompt Injection

OWASP LLM Top 10 — LLM01

Key Finding

Steering vectors systematically alter jailbreak attack success rates, with increases up to 57% and decreases up to 50% depending on targeted behavior, attributed to overlap with refusal behavior latent directions

Contrastive Activation Addition

Novel technique introduced


Activation steering has emerged as a powerful tool to shape LLM behavior without the need for weight updates. While its inherent brittleness and unreliability are well-documented, its safety implications remain underexplored. In this work, we present a systematic safety audit of steering vectors obtained with Contrastive Activation Addition (CAA), a widely used steering approach, under a unified evaluation protocol. Using JailbreakBench as benchmark, we show that steering vectors consistently influence the success rate of jailbreak attacks, with stronger amplification under simple template-based attacks. Across LLM families and sizes, steering the model in specific directions can drastically increase (up to 57%) or decrease (up to 50%) its attack success rate (ASR), depending on the targeted behavior. We attribute this phenomenon to the overlap between the steering vectors and the latent directions of refusal behavior. Thus, we offer a traceable explanation for this discovery. Together, our findings reveal the previously unobserved origin of this safety gap in LLMs, highlighting a trade-off between controllability and safety.


Key Contributions

  • Systematic safety audit of Contrastive Activation Addition (CAA) steering vectors across 6 LLMs (3B-32B) showing steering can increase ASR by up to 57% or decrease by up to 50%
  • Mechanistic analysis tracing safety erosion to geometric overlap between steering vectors and refusal behavior directions
  • Causal validation via ablation of refusal-aligned components from steering vectors as a mitigation strategy

🛡️ Threat Analysis


Details

Domains
nlp
Model Types
llmtransformer
Threat Tags
inference_time
Datasets
JailbreakBench
Applications
llm safety alignmentactivation steering