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Trust & integrity
Full report- Maintenance
- Active (10d since push)
- As of today · Source: github_public_v1
- Provenance
- Not a fork · Organization account
- As of today · Source: github_public_v1
- Security (OSV)
- No lockfile
- As of today · Source: none
Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.
Overview
Set of tools to assess and improve LLM security.
Capability facts
- Languages
- python
Source: github.language · Jul 11, 2026
Categories
Tags
README
License
Components within the Purple Llama project will be licensed permissively enabling both research and commercial usage. We believe this is a major step towards enabling community collaboration and standardizing the development and usage of trust and safety tools for generative AI development. More concretely evals and benchmarks are licensed under the MIT license while any models use the corresponding Llama Community license. See the table below:
| Component Type | Components | License |
|---|---|---|
| Evals/Benchmarks | Cyber Security Eval (others to come) | MIT |
| Safeguard | Llama Guard | Llama 2 Community License |
| Safeguard | Llama Guard 2 | Llama 3 Community License |
| Safeguard | Llama Guard 3-8B | Llama 3.2 Community License |
| Safeguard | Llama Guard 3-1B | Llama 3.2 Community License |
| Safeguard | Llama Guard 3-11B-vision | Llama 3.2 Community License |
| Safeguard | Prompt Guard | Llama 3.2 Community License |
| Safeguard | Code Shield | MIT |
Getting Started
As part of the Llama reference system, we’re integrating a safety layer to facilitate adoption and deployment of these safeguards. Resources to get started with the safeguards are available in the Llama-recipe GitHub repository.