When Words Are Safe But Actions Kill: Probing Physical Danger Beyond Text Safety in Hidden-State Risk Space

2026-07-16 · 17:20 UTC ·Weimeng Wang, Ziqiang Wang, Zihang Zhan... ·1 min read

Brief

When Words Are Safe But Actions Kill evaluates whether physical danger (PD) and content danger (CD) are distinct signals in LLM hidden states. Using hidden-state direction analysis and random-split null tests across Qwen2.5-3B/7B/14B/32B, Phi‑3.5, and SmolLM2, the authors introduce PRISM — a single‑layer L2‑regularized logistic probe — and demonstrate strong PD detection (SafeAgentBench: 86.2–87.7% accuracy; PSB‑1K: 99.6%).

Why it matters

Hidden-state analyses across Qwen2.5-3B/7B/14B/32B, Phi-3.5, and SmolLM2 show content danger (CD) and physical danger (PD) form separable signals; PRISM (single-layer L2-regularized logistic probe over full hidden states) achieves 86.2–87.7% accuracy with 11.7–13.7% FPR on SafeAgentBench, versus 24.7–39.0% FPR for same-scale LLM judges.

Key details

On the new PSB-1K contrastive benchmark (1,000 physical-risk pairs without explicit harm keywords), PRISM reaches 99.6% accuracy and 0.7% FPR, while a Qwen2.5-3B judge wrongly rejects 67.8% of safe tasks; PRISM’s findings also replicate on SafeText and EARBench.

Abstract

Large language models (LLMs) increasingly serve as high-level planners for embodied agents, where linguistically benign instructions can become unsafe once grounded in the physical world. We study whether this physically grounded danger is the same safety problem as ordinary text-level content danger. Through hidden-state direction analysis and random-split null tests, we show that content danger (CD) and physical danger (PD) form separable signals in LLM representations across Qwen2.5-3B/7B/14B/32B, Phi-3.5 and SmolLM2. Building on the CD/PD separability, we propose PRISM, a single-layer L2-regularized logistic probe over full hidden states. PRISM achieves 86.2--87.7\% accuracy on SafeAgentBench with 11.7--13.7\% FPR, while same-scale LLM judges over-block safe tasks at 24.7--39.0\% FPR. We further introduce PhysicalSafetyBench-1K (PSB-1K), a contrastive benchmark of 1{,}000 physical-risk pairs without direct harm keywords, to test whether methods detect physically grounded danger rather than explicit unsafe wording. On PSB-1K, PRISM reaches 99.6\% accuracy and 0.7\% FPR, whereas a Qwen2.5-3B judge rejects 67.8\% of safe tasks. PRISM also replicates on SafeText and EARBench, supporting hidden-state probing as a representation-level method for physical safety beyond text moderation.