Red Teaming
Red teaming is the authorised practice of attacking your own AI system to expose weaknesses before a hostile actor does: a dedicated team fires adversarial prompts, jailbreak attempts and abuse scenarios at it, records what gets through, and feeds every finding back into a fix.
No jargon, no math
In plain words, what is it?
You give a team written permission to attack your own AI system, with a scope: the chatbot, its tools, its data, its permissions. The team works like a hostile user with a deadline. It writes adversarial prompts, jailbreak attempts, crafted inputs and abuse scenarios, then fires them at the system while the logs record everything. Every attack that lands (the agent leaks its system prompt, runs an unfiltered query, approves a fake request) is reproduced, logged and ranked by damage. A fix goes in, the same attack runs again to prove the patch holds, and the attack joins your permanent test set. The boundary: red teaming is a snapshot. Models, tools and prompts all change, so a clean report from last quarter says little about this quarter's build. That is why it runs on a schedule, not once, and why its real output is not the pass but the library of attacks you now run against every release.
- 01
Scope. You define the target and the rules of engagement: what may be attacked, what must not be touched.
- 02
Generate attacks. Adversarial prompts, jailbreaks and abuse scenarios are produced, including ones nobody wrote before.
- 03
Run them. Every attack fires at the live system while logs capture input, output and tool calls.
- 04
Triage. Whatever gets through is reproduced, logged and ranked by damage.
- 05
Fix and retest. The patch must survive the exact attack that broke it, and the attack joins the permanent test set.
Terms that live nearby.
Guardrails
Guardrails are the checks and limits wrapped around an AI model so its behaviour stays inside your rules: they screen what goes in, constrain what the model can do, and verify what comes out before it reaches a person or a system.
ReadPrompt Injection
Prompt injection is an attack where hidden instructions are planted inside content an AI reads (an email, a web page, a document), so the model executes a stranger's commands as if they were yours.
ReadJailbreak
A jailbreak is an attempt to make an AI model ignore its safety training through a cleverly disguised prompt, so it produces content it was built and tuned to refuse.
Read§ 04
Want this running in your stack?
We design and ship AI systems with permissions, logs and human approval. It starts with a 30-minute scoping call.