AI Red Team Tools: Open Source Options Compared

The tooling for AI red teaming has matured significantly. Several open-source options are available, each with different design philosophies and strengths.

Chainbreaker

Developer: 15 Research Lab Approach: Multi-turn adversarial evaluation with naturalistic framing. Chainbreaker does not tell the model it is being tested. It uses realistic conversation patterns that mirror how real attackers operate.

Key capabilities:

• 15-turn escalation sequences that test gradual compliance erosion
• Presentation-decision coupling analysis (does the model stop reasoning about safety when warnings are absent?)
• Trajectory blindness testing (does the model catch the pattern across turns or evaluate each turn independently?)
• Scoring against the ASB Benchmark framework

Best for: Evaluating model behavior under realistic adversarial conditions. Finding the gap between benchmark performance and real-world resilience.

Garak

Developer: NVIDIA Approach: Probe-based vulnerability scanning. Garak runs a large set of probes against the model and reports which ones succeed.

Key capabilities:

• Extensive probe library covering prompt injection, jailbreaking, data leakage, and more
• Plugin architecture for custom probes
• Multiple detector types for classifying model responses
• Support for various LLM API backends

Best for: Broad vulnerability scanning. Running a wide sweep of known attack types against a model to establish a baseline security posture.

PyRIT (Python Risk Identification Tool)

Developer: Microsoft Approach: Multi-turn orchestration with automated scoring. PyRIT automates the attacker side of the conversation and uses a judge model to score outcomes.

Key capabilities:

• Orchestrators that manage multi-turn attack sequences
• Automated objective scoring using judge models
• Memory management for tracking attack progress
• Support for multi-modal attacks (text, image)

Best for: Automated multi-turn red teaming at scale. When you need to run thousands of adversarial conversations without manual effort.

Comparison Matrix

| Feature | Chainbreaker | Garak | PyRIT | |---------|-------------|-------|-------| | Multi-turn attacks | Primary focus | Limited | Yes | | Naturalistic framing | Yes | No | Partial | | Breadth of probes | Focused | Extensive | Moderate | | Automated scoring | ASB Benchmark | Detector-based | Judge model | | Custom payloads | Yes | Plugin system | Orchestrator | | MCP-specific testing | Yes | No | No | | Compliance mapping | OWASP, EU AI Act | OWASP | OWASP |

Using Them Together

These tools are complementary. A thorough red team exercise might:

1. Run Garak for broad vulnerability scanning (find the obvious holes)
2. Run Chainbreaker for deep multi-turn evaluation (find the behavioral vulnerabilities)
3. Use PyRIT for scaled automated testing of specific scenarios identified in steps 1 and 2

No single tool covers the entire attack surface. Layer them for coverage.