AI Red Teaming Tools (2026): 10 Platforms to Attack-Test Your AI

An AI agent that can read email, call tools and touch customer data has a far bigger attack surface than a chatbot. Prompt injection is the classic example: instructions hidden in a user message or an external document that push the model to leak sensitive data or take actions it shouldn't.

The ten tools below are listed alphabetically and in no particular order, and every description comes from each vendor's own website, read as of Oct 2026. If you're tracing and evaluating AI apps rather than attacking them, my guide to LLM observability tools covers that job.

AI red teaming platforms side by side

I checked the free plan column on each vendor's own website, as of Oct 2026. Yes means the page names a free plan, a free version or an open source edition. Trial only means the page names a time-limited free trial. Not stated means the page I read named neither, so check the vendor's own site before you sign up.

Tool	Type	Good for	Free plan
Giskard	AI red teaming and LLM security	Agent red teaming with a go/no-go report	Not stated
HiddenLayer	AI security platform	Supply chain, attack simulation and runtime security	Not stated
Lakera	AI-native security	Protecting GenAI apps, agents and MCP use	Not stated
Lasso Security	AI security platform	Discovery, red teaming and runtime protection	Not stated
Mindgard	AI red teaming	Autonomous, attack-led AI red teaming	Not stated
Pillar Security	AI security platform	Multi-turn attacks on whole agent systems	Not stated
Prisma AIRS (Protect AI)	AI security (Palo Alto Networks)	AI security inside the Palo Alto Networks platform	Not stated
Prompt Security	AI security (SentinelOne)	AI usage control plus open source testing tools	Not stated
Promptfoo	AI testing and red teaming	Open source red teaming in CI/CD	Yes
Repello AI	Red teaming and AI security	Red teaming for agents, MCP and chatbots	Not stated

Ten AI red teaming tools for apps and agents

Giskard

Best for: Teams that want AI security delivered as a service, ending in a go or no-go report that clears an agent for production.

HiddenLayer

Best for: Security teams covering the whole AI life cycle, from model supply chain checks before deployment to attack detection in production.

Lakera

Best for: Enterprises protecting GenAI apps, agents and MCP use, with risk-based red teaming and an expert-led adversarial testing service.

Lasso Security

Best for: Enterprises discovering and controlling AI use at scale, with red teaming, detection and response, and runtime protection for agents.

Mindgard

Best for: Companies without in-house AI security specialists, drawing on more than a decade of Lancaster University AI security research.

Pillar Security

Best for: Agentic systems, running multi-turn adversarial attacks that test tool orchestration, permission escalation and agent workflows end to end.

Prisma AIRS (Protect AI)

Best for: Palo Alto Networks customers who want to discover, assess, protect and govern their whole AI ecosystem from one platform.

Prompt Security

Best for: SentinelOne customers who want AI security from the same vendor, plus open source tools such as a prompt fuzzer for vulnerability checks.

Promptfoo

Best for: Developers who want red teaming in their pipeline, with tests configured in YAML, findings in pull requests and an open source version.

Repello AI

Best for: Teams securing agentic workflows, MCP connections and chatbots who want red teaming and runtime security from one specialist.

Two well-known AI security startups now belong to big security vendors

Here's what I noticed when I read every vendor page side by side. The Protect AI address now opens a page titled Prisma AIRS from Palo Alto Networks, and Prompt Security's page now reads From SentinelOne. Two of the best-known AI security names are now part of large security companies.

That cuts both ways. If you already buy from one of those vendors, the AI module may slot into tools your security team knows. If you want a specialist, the open source led names, Promptfoo and Giskard, are worth a look first.

Testing before launch versus guarding in production

Red teaming is testing: you attack the system before release, fix what breaks and repeat after every change. Runtime protection is a guard that sits in front of the live app and blocks attacks as they happen. Most vendors here now sell both, so ask which one you're seeing in the demo.

What a good AI red teaming test should cover

1. Prompt injection, including instructions hidden in documents and web pages your agent reads.
2. Jailbreaks and attempts to make the model ignore its rules.
3. Data leakage, such as revealing the system prompt or sensitive records.
4. Agent abuse: tool calls, permission escalation and multi-step workflows, not just single prompts.
5. Regression: tests that run again in your CI/CD pipeline after every model or prompt change.
6. Reporting: findings ranked by severity, with clear steps to fix them.

If you're building the agents themselves, my guide to AI agent frameworks covers the frameworks these tools test.

Do you make AI red teaming software? Tool makers can ask to be considered for a featured place on this list.

My plain advice on AI red teaming tools

Run an open source red teaming tool against your own app before you talk to any vendor. You'll learn which attacks land and what your team can fix alone. Then bring in a platform when you need continuous testing, runtime guardrails or a report your compliance team can sign off.

And don't forget the keys your agents hold. My guide to secrets management tools covers where those credentials should live.

Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.

Frequently asked questions

What is AI red teaming?

It's attacking your own AI system the way an adversary would, with prompt injection, jailbreaks and agent abuse, to find weaknesses before real attackers or users do.

What's prompt injection?

It's when attackers hide instructions in user input or external content, so the AI leaks data or takes actions it shouldn't.

Are there open source AI red teaming tools?

Yes. One tool here names an open source version on its own page, and another publishes open source testing tools. Check the free plan column.

Is red teaming the same as AI guardrails?

No. Red teaming tests the system before and between releases. Guardrails block attacks in production. Many vendors here sell both.

How often should you red team an AI app?

After every change to the model, prompts, tools or data sources, ideally automatically in your CI/CD pipeline, plus deeper tests before major launches.