The ai-blackteam batch command

ai-blackteam batch runs multiple attacks against a model in one go. By default, it runs them in parallel across 5 workers.
That fires every registered attack (1,000+) at the target. Each attack runs independently, and you get a summary at the end.

Selecting attacks

All attacks:
Specific attacks (comma-separated):
Unknown attack names get skipped with a warning. The rest keep running.

Parallelism

By default, batch runs 5 attacks at the same time. Increase or decrease with -w:
For true sequential execution, use --sequential:
This runs attacks one at a time with no async overhead. Useful for debugging or when you need deterministic ordering.

All flags

Progress bar

A live progress bar tracks how many attacks have completed:
Each line prints as an attack completes, showing its verdict and a preview of the prompt used.

Summary table

When the batch finishes, you get a one-line summary:
This tells you at a glance how many attacks got through, how many were blocked, and how many landed in the gray zone.

Exit codes

Same as ai-blackteam run:

Sensitive category warnings

When your batch includes attacks from sensitive categories (CBRN, weapons, infrastructure), ai-blackteam prints a warning:
This is a heads-up, not a blocker. The attacks still run. Make sure you have proper authorization before testing sensitive categories against production APIs.

The ai-blackteam sweep command

ai-blackteam sweep runs all attacks against all configured providers in sequence. It’s a full cross-provider comparison in one command.

How it works

  1. ai-blackteam checks your config for providers with API keys set
  2. For each provider, it runs every registered attack sequentially
  3. At the end, you get a summary table comparing all providers

Sweep summary table

Sweep flags

Configuring providers for sweep

Sweep uses whatever providers have API keys configured. Set them up first:
Ollama always runs (no API key needed). Providers without keys are skipped. If no providers are configured, sweep tells you: