AI Red Team
What is AI Red Team?
AI Red TeamA specialised team that simulates adversaries against AI systems to uncover safety, security, and misuse risks before real attackers do.
AI red teaming extends traditional red teaming to AI-specific failure modes: prompt injection, jailbreaks, harmful content generation, hallucinated authority, model theft, data exfiltration via tools, agentic abuse, and emergent dual-use risks. It blends adversarial ML expertise with policy, sociotechnical, and offensive-security skills. Microsoft, Anthropic, OpenAI, Google DeepMind, and NIST (via the AI Safety Institute and AI 600-1 profile) all run or recommend structured red-team programs, often combining manual probing, automated attack suites, and crowdsourced bug-bounty events. Outputs feed model alignment, evaluation harnesses, guardrails, governance controls, and incident-response playbooks. AI red teams are an explicit requirement under the EU AI Act for high-risk and general-purpose AI models.
● Examples
- 01
A pre-launch red team probing a chatbot for jailbreaks, data leakage, and harmful-output failure modes.
- 02
A government-sponsored exercise testing whether an open-weights model can be coaxed into producing biothreat instructions.
● Frequently asked questions
What is AI Red Team?
A specialised team that simulates adversaries against AI systems to uncover safety, security, and misuse risks before real attackers do. It belongs to the AI & ML Security category of cybersecurity.
What does AI Red Team mean?
A specialised team that simulates adversaries against AI systems to uncover safety, security, and misuse risks before real attackers do.
How does AI Red Team work?
AI red teaming extends traditional red teaming to AI-specific failure modes: prompt injection, jailbreaks, harmful content generation, hallucinated authority, model theft, data exfiltration via tools, agentic abuse, and emergent dual-use risks. It blends adversarial ML expertise with policy, sociotechnical, and offensive-security skills. Microsoft, Anthropic, OpenAI, Google DeepMind, and NIST (via the AI Safety Institute and AI 600-1 profile) all run or recommend structured red-team programs, often combining manual probing, automated attack suites, and crowdsourced bug-bounty events. Outputs feed model alignment, evaluation harnesses, guardrails, governance controls, and incident-response playbooks. AI red teams are an explicit requirement under the EU AI Act for high-risk and general-purpose AI models.
How do you defend against AI Red Team?
Defences for AI Red Team typically combine technical controls and operational practices, as detailed in the full definition above.
What are other names for AI Red Team?
Common alternative names include: AI red teaming, Generative AI red team.
● Related terms
- ai-security№ 030
AI Jailbreak
A technique that causes an aligned AI model to bypass its safety policies and produce content or behaviour the operator intended to forbid.
- ai-security№ 866
Prompt Injection
An attack that overrides an LLM's original instructions by smuggling adversarial text into the prompt, causing the model to ignore safeguards or execute attacker-chosen actions.
- ai-security№ 777
OWASP LLM Top 10
An OWASP-maintained list of the ten most critical security risks affecting applications that build on large language models.
- ai-security№ 691
MLSecOps
The discipline of integrating security and risk controls across the entire machine-learning lifecycle, from data sourcing through training, deployment, monitoring, and retirement.
- ai-security№ 033
AI Safety
The discipline that aims to prevent AI systems from causing unintended harm to users, operators, and society — covering technical, operational, and societal dimensions.
- ai-security№ 027
AI Governance
The policies, processes, roles, and controls organisations and regulators use to ensure AI systems are developed, deployed, and operated responsibly and lawfully.
● See also
- № 018Adversarial Example
- № 393Evasion Attack (ML)
- № 024AI Alignment
- № 1163Token Smuggling
- № 1168Transferable Adversarial Attack
- № 014Adaptive Attack
- № 619LLM System Prompt Leak