LlamaFirewall
A guardrail framework that combines prompt-injection detection, agent-alignment checks and generated-code scanning for LLM applications.
About LlamaFirewall
Agent applications need configurable checks on untrusted inputs, intermediate decisions and generated code.
Who it’s for
- Developers adding security checks to AI agents
- Security engineers composing scanners for LLM application workflows
When to consider it
Consider LlamaFirewall when you want to attach different security scanners to message roles and inspect conversation traces.
Tradeoffs & limitations
- The LlamaFirewall code is MIT licensed; its setup guide requires Python 3.10 or later and access to the referenced Meta models. The surrounding PurpleLlama repository includes components with other licenses.
SOTA overview · Documentation-based assessment · Sources & review method
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Sources & review method
Documentation-based assessment · Oct 30, 2026 · Prepared with AI assistance; not a hands-on benchmark.
- LlamaFirewall official documentation
- LlamaFirewall architecture, scanners and setup requirements
- LlamaFirewall component MIT license
- PurpleLlama component and model license distinctions
- LlamaFirewall-specific commit history
- Official maintainer organization and Meta domain
Checked by SOTA · AI-assisted documentation review. Selection advice is our assessment; verify current requirements for your deployment.
Import history & original evidence
LlamaFirewall official repository
A guardrail framework that combines prompt-injection detection, agent-alignment checks and generated-code scanning for LLM applications.
Based on official pages and announcements checked on 2026-10-29. No hands-on test, performance benchmark or popularity ranking is claimed.