ActionBench: discovering hidden failure modes of agents
Evaluating how agents decide, use tools, and cross boundaries.
“AI agents are moving beyond assistance and into action. Instead of generating content, they invoke tools, modify data, trigger workflows, and operate across systems with increasing autonomy. This shift changes the security problem fundamentally.”
AI control plane for engineering teams to make every agent action visible, governable, secure and safe.
Task context
Cybersecurity evaluation
OpenAI × Hugging Face Space
14:01:58
Eval workspace attached
Isolated container runtime
14:02:03
Harness loaded benchmark tasks
[…]
11 steps omitted
14:02:16
Goal misalignment
Agent is trying to escape the sandbox
unshare --mount /
14:02:16
Session terminated
Alert sent to #sec-agents
Enforce boundaries
Block dangerous, unauthorized, or out-of-policy actions before execution.
Works with the models you already use
OpenAIAnthropicxAIGeminiMetaMistral
Hugging FaceAzureBedrock
Hugging FaceAzureBedrockOpenAIAnthropicxAIGeminiMetaMistralHugging FaceAzureBedrock
Hugging FaceAzureBedrockOpenAIAnthropicxAIGeminiMetaMistralHugging FaceAzureBedrock
Hugging FaceAzureBedrockOpenAIAnthropicxAIGeminiMetaMistralHugging FaceAzureBedrock
Hugging FaceAzureBedrockControl every agent action
Monitor behavior, protect against attacks and apply custom policies in real time.
input
LLM Provider
action
output
>/Detecting attempts to override system instructions and safety controls
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Research
The systems, methods, and experiments that shape how we build and safeguard AI products.
Read
PolicyGuard: evaluating runtime control for AI actions
Measuring the real-world performance of action-level guardrails.
Preprint · Security
Coming soon
Tool authorization failure modes
Where permissioning breaks down when models try to act.
Infrastructure
Coming soon
Policy enforcement under pressure
Keeping control decisions fast when agents run at production scale.
Training
Coming soon
Designing human approval loops
Making reinforcement from review practical for production agents.