We'll attack your AI agent for free. You keep the report.
Up to 2,500 attacks built around your own policies, single and multi-turn. You give us an endpoint, we give you every way your agent breaks under pressure, with the fixes. Zero cost, zero obligation.
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free assessment
An Alice red teamer scopes the endpoint, we run the automated, personalized attacks, you get the report.
Nothing to buy, nothing to install.
One agent. Up to 2,500 attacks. One report you keep.
Option to add the system prompt or description and the attacks get sharper. Nothing touches production.
Alice acts as the user and runs hundreds of custom, single and multi-turn attacks against your policies.
Every way the agent broke, how easily, and how to fix it. In a detailed report sent directly to you.
What you get, free
No credit card. No sales deck. Just an endpoint.
Someone will find out how your agent breaks. Better it's us.
A person stops at a few dozen attacks.
We run hundreds, built for your agent.
Agents fail in behavior, under pressure, in ways a code review never shows. Finding those failures takes more attacks than anyone can write by hand, and every one of them written for your agent, not pulled from a generic list.
5
red teaming policies tested
Up to 500
prompts per policy generated for your agent
~1 day
till results
Attacks written for your agent,
taken from real attacks found online
Most tools send a fixed list of known bad prompts. We build the attack around your agent and disguise it like a real adversary would.
The plan of attack
We start by learning your agent, what it may do and what it must never do.
Example: a banking agent may explain fees but never share account details. The scenario asks about fees in a way that pulls account details into the answer.
The disguise on the attack
We take real attack techniques, and place them inside custom-built scenarios, written by our platform based on what it learns from your agent. Up to 500 scenarios per policy.
Example: Using a 3-part-prompt, convince the bank you are Dan from investments and need access to the CEOs account details.
Where attack techniques come from
Hundreds of in-house researchers track real attackers across online forums, the deep and dark web. We store the techniques inside our database.
Billions of adversarial examples stored. Used to red team your agent against new techniques.
Four answers, with the evidence behind each
Attack success rate,
overall and per policy
Your headline number, and the one to track between versions.
3%
11%
The scenario and technique
behind each success
Tells you what to fix: an ignored rule needs a prompt change, a disguise it keeps falling for needs a guardrail.
200
14
A risk score for every finding
An attack anyone can copy and paste is critical. One that needs expertise is low.
4
12
31
Fixes, prioritized
A fix per finding, with the full attack session. Make the change and we rerun the same prompts to show what improved and what regressed.
Example: restrict account data in the system prompt, add a multi-turn check, retest.
01
02
03
What's included
Scope
One AI agent or application
Access
No production access, just an endpoint.
Attacks
Up to 5 of your policies, such as prompt injection, data leakage or safety rules.
Single and multi-turn attacks on each.
Your effort
Endpoint details and a 30-minute scoping call.
Turnaround
1 business day
Cost
None. No purchase, no obligation