AI red teaming & LLM evaluation

DeepTeam: open-source LLM red teaming framework

DeepTeam is an open-source LLM red teaming framework from Confident AI. It is released under the Apache-2.0 license and is offered as: Library, CLI, Self-hosted.

  • Last reviewed
Open sourceApache-2.0 Layer 4: Testing and red teaming

Best for

Python teams that want a free framework to run single-turn and multi-turn attacks against an LLM app or agent from code or a YAML config

Consider instead if

  • You want a command-line scanner with a fixed probe library instead of a framework you configure. See garak.
  • You need an inline filter that screens live traffic instead of a testing framework. See NeMo Guardrails.

What DeepTeam does

DeepTeam is an open-source Python framework for red teaming LLM applications and agents, made by Confident AI and built on the DeepEval project. You install it with pip, then run it from Python or from a YAML config with the deepteam run command. Its README lists more than 50 vulnerabilities, such as PII leakage and bias, and more than 20 attacks, including single-turn prompt injection and multi-turn jailbreaks such as Crescendo. The README says it can red team against frameworks including OWASP Top 10 for LLMs 2025, NIST AI RMF and MITRE ATLAS. The code is Apache-2.0 licensed and free to run. DeepTeam is a testing framework, not an inline filter for live traffic.

This summary is our own wording of the sourced facts on this page.

Key facts

Each value links to the page that states it, with the date we checked it.

Pricing model
Free: The framework is free. On the vendor's pricing page, the Enterprise plan (custom pricing) lists an AI red teaming module. (as listed on October 21, 2026; check the vendor for current pricing) Source, checked October 21, 2026: confident-ai.com (opens in a new tab)
API reference
Not documented in the sources we checked
Security page
Not documented in the sources we checked
Attestations or disclosure
Not documented in the sources we checked

Capabilities

As documented by the vendor or project. The tag is our label from a controlled vocabulary.

Integrations

Where DeepTeam fits in our AI security layers

Our analysis

Our editorial model, not a standard. The primary layer follows the category, except for tools whose main documented job is detection and response; other layers rest on a capability the sources document. How the model works.

AI security layers that DeepTeam covers, with the role, how each applies and what it rests on
LayerRoleHow it appliesBased on
L4 Testing Testing and red teaming Primary Attack and evaluate models, apps and agents on purpose, before release and after every change, to find what the other layers miss. Follows its category, AI red teaming & LLM evaluation

OWASP LLM Top 10 mapping

Our analysis

The risk list is OWASP's (Top 10 for LLM Applications, 2025). The mapping is our analysis, and each row rests on a capability the sources document.

OWASP LLM risks mapped to DeepTeam, with the capabilities each mapping rests on
RiskHow it appliesBased on
LLM01 Prompt Injection Runs prompt injection and jailbreak attacks, single-turn and multi-turn, against a target. Runs single-turn prompt injection attacks; Runs jailbreaking attacks, including linear, tree and Crescendo jailbreaking; Runs multi-turn attacks such as Sequential Jailbreak and Bad Likert Judge
LLM02 Sensitive Information Disclosure Tests a target for PII leakage. Tests for PII leakage among its data privacy vulnerabilities
LLM09 Misinformation Tests a target for misinformation. Tests for misinformation among its vulnerability types

Alternatives and related tools

More in AI red teaming & LLM evaluation, ranked within the category by Coverage Score.

garak

NVIDIA

Open sourceApache-2.0
  • CLI
  • Library
  • Self-hosted

Probes language models and LLM apps for prompt injection, jailbreaks, data leakage and more.

Best for: Teams that want a free command-line scanner they can point at any model or LLM endpoint before release

Coverage Score 82 out of 100
  • LLM01 Prompt Injection
  • LLM02 Sensitive Information Disclosure
  • LLM09 Misinformation

Reviewed

Giskard

Giskard AI

Open sourceApache-2.0 Freemium
  • Library
  • Self-hosted
  • SaaS
  • On-prem

Generates adversarial test suites for LLM agents and RAG apps, runs them and reports failures by threat type.

Best for: Python teams that want a free library to scan an LLM agent or RAG app for prompt injection and harmful output, and to write pass or fail checks for it

Coverage Score 81 out of 100
  • LLM01 Prompt Injection
  • LLM02 Sensitive Information Disclosure
  • LLM09 Misinformation

Reviewed

Promptfoo

OpenAI (Promptfoo)

Open sourceMIT Freemium
  • CLI
  • Library
  • Self-hosted
  • SaaS
  • On-prem

Runs evals and red team scans against LLM apps from a CLI or CI pipeline and writes a vulnerability report.

Best for: Developer teams that want one open-source CLI for both prompt evals and red teaming, run locally and in CI

Coverage Score 80 out of 100
  • LLM01 Prompt Injection
  • LLM02 Sensitive Information Disclosure
  • LLM09 Misinformation

Reviewed

Head-to-head comparisons

DeepTeam FAQ

Is DeepTeam open source?

Yes. DeepTeam is released under the Apache-2.0 license, and the code is on GitHub at confident-ai/deepteam.

How do you run DeepTeam?

The README says to install it with pip install -U deepteam, then run red teaming from Python or from the CLI with a YAML config.

What does DeepTeam cost?

The framework is free under Apache-2.0. Confident AI's pricing page lists an AI red teaming module only under its Enterprise plan, which has custom pricing.

Key facts you can cite

We have no commercial relationship with Confident AI.

Sources & last reviewed

Last reviewed . We compile from the vendors' own public pages and repositories and we do not run the products. Source links open in a new tab. Found a mistake? Report a correction.