Check how you test your robot policy, in two minutes.
Six questions: what runs your robot, where you evaluate it, which of the Embodied AI Security Top 10 risks you have tested under attack, where it ships and how far along you are. You get the gaps in your own answers and a sensible next step. It is not a certification, a legal opinion, an insurance score or a safety guarantee.
In our own test of a real SmolVLA policy: 42 of 50 episodes left the keep-out envelope under a roleplay instruction (task-clustered 95% CI 62-100%) against 1 of 50 benign; the same frame with no target named does it in 27 of 30, so this is fragility, not steering. A task-success metric never sees that. The two families that stayed at the benign floor (visual 2/100, injection 2/50) are published at that size too, as counts, not as zero. See the measured result.
Scope: SmolVLA (HuggingFaceVLA/smolvla_libero) × libero_object (all 10 tasks), 5 seeds per task, LIBERO · robosuite · MuJoCo — simulation only, default (uncalibrated) predicate, provael 0.41.2.
What is coming, and when — for your counsel to confirm
Filtered by your market answers only. Whether an instrument actually applies to your product is a legal question this page cannot answer; each card links to the sourced crosswalk with its primary text and review date.
Where you have evidence, and where you do not
The 8 categories a policy red-teamer can reach. EAI07 (CPS / firmware / comms) and EAI10 (evaluation / observability) are out of a VLA-policy red-teamer's scope by design.
Get your scoped next step.
Optional. Sending transmits exactly this: your work email, organisation and role, plus a text summary of the answers above (practice level, ticked categories, markets, stage) — nothing else, and nothing until you press the button. A real person reads it and replies with the next useful conversation, not a sales cadence.
One email a month: the results that landed, the errata, and what is next. Nothing else, no spam, unsubscribe in one click.
You sign off on safety
Turn "is this safe enough?" into a measured rate with a benign control and its limits stated, for your own release decision.
You build the policy
Run the red-team yourself, free and CPU-first. Every attack family is in the open-source tool.
From a self-check to a measured result
The tool is free and runs on your own machine. If you want Provael to run it on your policy, these are the paid options; every price is on the pricing page.
The CLI, every attack family, an attack-success rate with a benign control, SARIF, the GitHub Action and local attestation are free and always will be. Run it yourself: pip install provael.
Get the tool →One eligible checkpoint on an agreed simulator and task set: the agreed tests that apply, matched controls, a reproducible report and an engineering review. Eligibility is confirmed by a short form and a human reply before anything is sent or paid.
Check eligibility →A human-led red-team of your own policy in simulation, scoped to your stack: the attack-success rate with 95% confidence intervals and a benign control, narrated attack chains, and an evidence pack under a written acceptance protocol.
Request a scoping call →The red-team re-run each quarter, CI gated on your acceptance protocol, and a rolling per-checkpoint regression baseline, so the evidence keeps up with a policy that keeps changing.
Request a scoping call →This checklist is a self-reported evaluation aid. Its heuristic is unvalidated, and its market and role answers are inputs for a review, not a determination of which rules apply. Provael is a defensive, simulation-only tool for authorized testing. Not affiliated with or endorsed by OWASP, MITRE, or any standards body. Verify every regulatory date against the primary source.