AI Quality
AI Red Teaming
Adversarial testing of AI products: jailbreaks, prompt injection, data exfiltration, and policy bypass — so you learn how the system fails before an attacker or a bored user does.
The problem
Most AI QA is cooperative: you ask the product to do its job well. Red teaming is the opposite. Someone will try to make it leak data, ignore the system prompt, or perform an action it should refuse. If you only test polite users, you will ship a polite-looking hole.
AI red teaming is structured adversarial testing of your product. It is not a generic “jailbreak leaderboard” and not a penetration test of your entire company. Guardrail testing checks filters you already turned on. Red teaming tries to go around them.
What’s at risk
- System-prompt or tool-schema leakage
- Prompt injection via uploaded files, retrieved docs, or pasted pages
- Jailbreaks that disable safety copy
- An agent talked into a forbidden tool call
- Personal or tenant data pulled through a “helpful” answer
What we attempt (within an agreed brief)
- Direct jailbreaks and role-play that try to drop policy
- Indirect injection through RAG documents or user-generated content
- Social-engineering the bot into revealing other users’ data
- Tool abuse if an agent is in scope — pair with AI agent testing
- Repeated probing after you patch one phrase — attackers iterate too
We agree the rules of engagement first: in-scope surfaces, forbidden live side effects, and what “stop” looks like. We do not attack systems you do not own.
How a red-team pass runs
- Threat sketch: what would actually hurt this product
- Attack set: known patterns plus product-specific ideas
- Execution on staging (or a tightly controlled prod slice)
- Evidence: prompts, outputs, and whether a guardrail fired
- Retest after you change the filter or the prompt
Parent: AI testing services. This is not a SOC 2 or legal opinion.
Deliverables
- Attack list and results (reproducible steps)
- Severity notes tied to user or business impact
- Retest of the issues you choose to fix
Suitable for
Consumer or internal AI features that can talk, retrieve, or act — especially if they are public-facing.
FAQs
Is this a security penetration test?
It is adversarial QA of the AI surface. Network, IAM, and classic appsec are out of scope unless we explicitly add them — and we usually will not.
Will you publish our jailbreaks?
No. Findings stay with you. We do not invent a public hall of fame.
Talk to our QA team
Need this tested on a real product?
Tell us the AI surface, the next change you plan to ship, and what a bad answer would cost.