arXiv:2608.29942cs.CRcs.AI2026-08

现有工具调用防护机制无法区分合法与恶意操作,易误判。

Influence Is Not Authority: When Causal Guardrail Signals Make Legitimate Tool Use Look Like an Attack in Tool-Using LLM Agents

  • 通过24个基例的授权等价测试,发现仅因数据来源不同就触发攻击信号
  • 同一操作在用户输入与工具输出间切换时,评分平均上升16%以上
  • 需重构参考信息构建与路由逻辑,才能实现准确安全判断

当前最先进的基于影响的防护机制无法可靠区分依赖外部工具信息的合法用户操作与恶意未经授权操作。这种模糊性导致良性行为被错误触发验证与干预,降低可用性并引入延迟。我们通过96种条件的授权等价审计揭示此问题:在24个基础案例中,保持授权状态、具体执行动作及预期效果不变,仅改变所需值来自用户还是合法工具结果。尽管动作未变,这一无害的数据源迁移使所有24例在Llama与Gemma评分器下均将因果信号推向攻击区域。匹配的未经授权对照组显示信号仍敏感于攻击,但无害迁移产生的评分变化大于实际授权变更。架构级评估表明该错配在防护设计中持续放大。引入语义监控后,攻击成功率降至0%,可用性为28%;而无监控时分别为16%和60%。基于影子的防护机制可让所有测试的无害运行通过,但对未授权操作的拒绝率并未显著提升:57.5%的未授权运行在后续安全检查前自动通过,而授权运行仅为29.2%。结果表明,所研究的因果信号反映的是行为成因,而非授权状态,且参考构建与路由是有效安全决策的关键。

原文摘要 · Abstract (English)

The key limitation of current state-of-the-art influence-based guardrails is that they do not reliably distinguish a legitimate, user-authorized action from a malicious, unauthorized action when both rely on external tool information. This ambiguity can cause benign actions to trigger unnecessary verification and intervention, reducing utility and adding latency. We expose this limitation through an authorization-equivalence audit of 96 conditions derived from 24 base cases. Within matched source comparisons, we hold authorization, the exact committed action, and its intended effect fixed, changing only whether a required value comes from the user or a legitimate tool result. Although the action remains unchanged, this harmless relocation shifts the causal signal toward the attack region in all 24 cases under both Llama and Gemma scorers. Matched unauthorized controls show that the signal remains attack-sensitive, yet the benign relocation produces a larger average score shift than the actual change in authorization. Architecture-level evaluation shows how this mismatch propagates through guardrail designs. With a semantic monitor, attack success is 0% and utility is 28%, compared with 16% and 60% without it. A shadow-based guardrail allows every tested harmless run, yet does not reject matched unauthorized actions more often overall: 57.5% of unauthorized runs pass automatically before reaching the later security check, compared with 29.2% of authorized runs. These results show that the studied causal signal reveals what shaped an action without reliably encoding whether the action was authorized, and that reference construction and routing are integral to the effective security decision.

大模型安全工具调用因果防护

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