Find weaknesses in your AI agents before your users and attackers do
Noma AI Red Teaming uses an adversarial LLM to run automated multi-turn attacks against your agents and applications, finding vulnerabilities, weaknesses, and compliance violations before they can be exploited.
the Challenge
AI systems evolve constantly, agents gain access to critical business tools, and traditional security testing struggles to keep pace. Organizations need a way to continuously understand how their AI can fail before attackers do.
Noma Solution
Noma AI Red Teaming continuously tests AI agents and applications using adaptive attack simulations tailored to each environment. Security teams gain ongoing visibility into real-world AI risk and can identify vulnerabilities before they become incidents.
Automated testing that discovers AI risk
Noma enables organizations to discover, govern, test, and protect AI and agents across the enterprise.
Attack like a real adversary
Real attackers chain their attacks instead of running one at a time. Noma simulates this by compounding multiple techniques into one attack sequence, raising attack success rate until your application's real weaknesses surface. Techniques include prompt injection, jailbreak, data leakage, denial-of-wallet, harmful content generation, and more.
Escalate the attack across turns
Most attacks don't land in one prompt. Noma runs multi-turn attack sequences with escalating pressure at each step, the way a patient attacker works a target.
Prove compliance with presets
Automatically map findings to compliance presets including OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act, and ISO 42001 for audit ready reporting.
Turn findings into runtime policy
Noma AI Red Team findings feed into AI-DR, so weaknesses that are exposed harden the policies protecting applications at runtime.
Use cases
Part of the Noma platform
When red teaming finds a vulnerability, it doesn't stay in a report. Findings feed directly into AI-DR detection policies, so every vulnerability discovered in testing becomes an enforced pattern in production. Posture management updates the agent's risk score. The loop between testing and protection is closed automatically.
Surface all AI assets and their risks
Noma finds every agent, model, MCP server and tool across your cloud, SaaS, and developer environments - often discovering 10 to 100x more agents than teams expect - and surfaces universal risks in your AI estate.
Set and enforce the rules
Define which agents are approved, what data they can access, and what actions they can take - enforcing policies in real time, before actions are carried out.
Test AI apps & agents continuously
Noma’s agents probe your AI apps and agents for prompt injection, jailbreak, data leakage, and goal drift - using sophisticated multi-turn attacks that uncover agent and model weaknesses.
See and stop threats in context
Every agent action looks normal on its own. The threat only appears in context. Noma monitors the full behavioral chain of every agent session (prompts, tool calls, data access, actions) and detects prompt injection, data exfiltration, and scope violations in real time.
