AI Red Teaming Services
Crescent AI actually tries to break your live agents and LLM applications — prompt injection, tool misuse, poisoned data — mapped to the OWASP GenAI Top 10, distinct from the identity, permission, and guardrail build-out this testing exists to validate.
We Try to Break It Before Someone Else Does
A guardrail nobody's tried to bypass is a guess dressed up as a control. We run real attacks against the real, live system — the same prompt injection, tool misuse, and jailbreak attempts an actual attacker would try — and hand you evidence, not an assumption.
What is AI red teaming?
AI red teaming is adversarial testing run against a live AI agent or LLM application — prompt injection, tool misuse, jailbreak attempts, and data extraction — to find how the system actually fails under attack, rather than assuming its guardrails hold.
AI Red Teaming vs AI Security Engineering
AI Red Teaming is the adversarial-testing slice: actually attacking the live system. AI Security Engineering is the broader discipline that builds what gets tested — identity checks, least-privilege permissions, guardrails, and threat modeling. Red teaming proves whether those controls actually hold under attack; it doesn't build them in the first place.
Recognize the symptoms
When You Need AI Red Teaming
If two or more of these are already true, this isn't a tuning problem.
- Guardrails were installed but never actually tested for whether they can be tricked
- Nobody's tried prompt injection against what the agent reads, only what a user types
- A security questionnaire from a customer or partner asks for AI-specific test evidence you don't have
- The agent has broad tool access and nobody's tried to misuse it on purpose
What We Test
The same attack surface an actual attacker would go after, not a fixed checklist run once and filed away.
Prompt Injection (Direct & Indirect)
Instructions typed straight at the model, and instructions hidden in content it reads elsewhere — a web page, a resume, a retrieved document.
Tool Misuse & Excessive Agency
Whether the agent can be talked into calling a tool it shouldn't, with arguments it shouldn't, or taking an action beyond what its job requires.
Guardrail Bypass Testing
Trying to talk safety filters into missing what they should catch, or blocking what they shouldn't, before an attacker finds the gap first.
Data & Credential Leakage
Attempts to extract system prompts, secrets, or one customer's data through the model's own responses.
Multi-Turn Jailbreak Attempts
Attacks built across several turns of conversation, not just a single malicious prompt, since that's how most real jailbreaks actually work.
When the system calls tools over MCP, that's its own attack surface — see MCP Security in Production: 8 Attack Classes and Required Mitigations.
Red Team Engagements We've Run
Organized around the real-world system under test, not the attack technique underneath it.
Customer-Facing Agent Adversarial Testing
Live testing against a support or sales agent with account access, where a successful trick has a real financial or privacy consequence.
RAG & Retrieval Injection Testing
Poisoned documents planted in a retrieval index to see whether the agent treats retrieved content as data or follows it as an instruction.
Multi-Tenant Isolation Testing
Deliberate attempts to make one customer's data or context leak into another's session, search results, or memory.
Pre-Launch Security Gate Testing
A red-team pass run before a new agent or feature ships, so the first attacker to try something isn't the first person to find the gap.
Post-Incident Re-Testing
After a fix ships for a confirmed issue, we retest the same attack path plus adjacent ones, instead of trusting the fix on paper.
What You Receive
From our experts.
Writing on agent risk, safe rollout, and production failure modes.
Related Engineering Services
Common questions.
Bring us the agent nobody's stress-tested yet.
Whether it's a prototype with broad access and no permission rules, or a production agent that's never been tested against someone trying to trick it, we'll walk through where it stands before we recommend anything.
No hype · No forced roadmap · Just a clear view of what the system needs next