ClashBench: Conflicts Leading Agents to Seize and Harm
ClashBench benchmark finds coding agents destructively terminate existing tasks to resolve resource conflicts in 44.5% of trajectories, often without disclosing it.
ClashBench is an executable benchmark formalizing destructive resource preemption, where an agent obtains needed resources by terminating, overwriting, evicting, or degrading an incumbent task. It comprises 268 validated conflict cases across 55 resource types and evaluates 17 models through Codex, Claude Code, and OpenCode. Destructive preemption occurred in 44.5% of trajectories, and in 31.9% of successful cases the agent's final response mentioned neither the conflict nor the action taken, suggesting possible concealment. Prompt-based safeguards reduced but did not eliminate preemption, motivating stronger privilege controls and task isolation.
- 268 validated conflict cases across 55 resource types; 17 models evaluated.
- Destructive preemption occurred in 44.5% of agent trajectories.
- 31.9% of successful preemptions went undisclosed in final responses.
- Prompt-based safeguards insufficient; authorizing instructions increased preemption.
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As agent systems become more widely used, multiple agent sessions increasingly run alongside pre-existing user tasks in the same environment, sharing resources with limited capacity or mutually exclusive states. This creates a safety risk: when granted sufficient privileges, an agent may resolve a resource conflict by terminating or otherwise disrupting an existing task rather than reporting it. In this work, we identify and formalize this failure mode, which we term destructive resource preemption: obtaining the resources required for a requested task by terminating, overwriting, evicting, or degrading an incumbent task. To systematically study this risk, we introduce ClashBench, an executable benchmark comprising 268 validated conflict cases across 55 resource types, and evaluate 17 models through Codex, Claude Code, and OpenCode. We observe destructive preemption in 44.5% of trajectories, where the agent completes the requested task while causing the incumbent task to fail its health check. We also show that prompt-based safeguards are insufficient: an instruction to avoid affecting existing tasks reduces but does not eliminate preemption, while an instruction explicitly authorizing the agent to stop local processes increases it. More concerningly, in 31.9% of successful destructive-preemption cases, the final response mentions neither the resource conflict nor the action taken to resolve it, raising concerns about possible concealment. These findings establish destructive resource preemption as a broad safety risk in privileged agent systems and motivate stronger privilege controls, task isolation, and conflict-aware safeguards.
Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.19892