DeepTeam is a framework to red team LLMs and AI agents.

llm-guardrails 开源项目推荐(332 个)
llm-guardrails 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 332 个仓库Agentic LLM Vulnerability Scanner / AI red teaming kit 🧪
A curated, source-backed list of projects built with Jev, TypeSafe AI's System One model for typed decisions.
The Open Source Firewall for LLMs. A self-hosted gateway to secure and control AI applications with powerful guardrails.
The fastest Trust Layer for AI Agents
Open Source policy enforcement proxy: Make your agents follow rules.
Real-time decision features without streaming infra. Turn live events into product reflexes — no Kafka, no Flink, no feature store.
Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️
Prompt-injection guardrail for LLM applications. Compact model that outperforms larger open-source guards. No regex, no signatures. Demo: anton.securelayer7.net
A production-grade control layer that sits between your application logic and any LLM — input validation, schema enforcement, circuit breaking, targeted retry, and audit logging in one composable pipeline.
A TypeScript library providing a set of guards for LLM (Large Language Model) applications
A modular threat detection library for AI and LLM pipelines. It provides language-agnostic guardrails through a configurable pipeline of loaders, multi-layer de-obfuscation, specialized scanners, and automatic enforcement.
Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell
A curated list of LLM/MLLM guardrails, safety benchmarks, guard models, jailbreak attacks, moderation datasets, and evaluation tools.
LMAP (large language model mapper) is like NMAP for LLM, is an LLM Vulnerability Scanner and Zero-day Vulnerability Fuzzer.
Checks AI-generated code changes before merge: scope, validation, risk, review evidence, and optional Verity receipts.
Real-time guardrail runtime for AI agents.
Explainable security gate for LLM apps — blocks prompt injection with an auditable reason for every decision.
LLM prompt injection detection for Go applications
Official Python SDK for RAIL Score. LLM evaluation across 8 dimensions, guardrails, safe regeneration, agent tool-call eval, and compliance (GDPR, HIPAA, EU AI Act, India DPDP).
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/llm-guardrails。
- 该话题在 GitHub 上共有 332 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 6942 Star,覆盖 5 种主要语言,数据更新于 2026-11-10。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。