8 Best agentic-radar Alternatives in 2026 (Open Source)

agentic-radar — A security scanner for your LLM agentic workflows. The first dedicated security scanner specifically designed for agentic AI workflows, combining static analysis with runtime adversarial testing and automatic prompt hardening — no other tool maps agent vulnerabilities to OWASP AI security frameworks

These 8 open-source tools do the same job. They are ordered by how closely they match agentic-radar, with live GitHub data so you can see which projects are actively maintained.

1. 1. Promptfoo

   Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and

   What sets it apart: Unlike LangSmith (production observability) or Langfuse (logging), promptfoo is the only open-source tool combining eval + red teaming + CI/CD code scanning — now backed by OpenAI while remaining fully MIT-licensed

   Best for: Teams hardening LLM apps against prompt injection and jailbreaks with automated red teaming; Engineering teams adding LLM eval regression tests to CI/CD pipelines

   ⭐ 25.6kagentic-radar vs Promptfoo →Full profile →

2. 2. Superagent

   Superagent protects your AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers.

   What sets it apart: YC-backed AI safety SDK that pivoted from general agent building to focused safety tooling — provides guard, redact, and scan capabilities with open-weight models for self-hosting, filling the gap between building agents and securing them

   Best for: Teams adding safety layers to production AI agents; Enterprises requiring PII redaction and prompt injection protection; Security-focused AI deployments with compliance requirements

   ⭐ 6.8kagentic-radar vs Superagent →Full profile →

3. 3. LLM Guard

   The Security Toolkit for LLM Interactions

   Best for: Enterprise teams deploying LLMs in production needing security guardrails; Organizations with strict data leakage prevention requirements; Applications handling sensitive user data through LLM interfaces

   ⭐ 3.2kagentic-radar vs LLM Guard →Full profile →

4. 4. LangKit

   🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance m

   What sets it apart: Open-source text metrics toolkit for LLM monitoring with built-in security detection (jailbreaks, prompt injection), quality scoring, and whylogs integration

   Best for: llm-output-monitoring; detecting-prompt-injection; text-quality-observability

   ⭐ 997agentic-radar vs LangKit →Full profile →

5. 5. UpTrain

   UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform ro

   What sets it apart: vs generic eval tools: 20+ preconfigured evaluations with customizable prompts, few-shot examples, and scenario descriptions — all running locally for data privacy with root cause analysis on failures

   Best for: RAG system evaluation and quality assurance; LLM application testing before production deployment; Safety and security testing for prompt injection vulnerabilities

   ⭐ 2.4kagentic-radar vs UpTrain →Full profile →

6. 6. DeepEval

   The LLM Evaluation Framework

   What sets it apart: Most comprehensive open-source LLM eval framework with 30+ research-backed metrics including agentic, RAG, multi-turn, MCP, and multimodal — vs Ragas (RAG-only) or custom eval scripts

   Best for: Teams needing comprehensive LLM/agent evaluation pipelines; CI/CD integration for LLM app quality gates; RAG pipeline evaluation and optimization

   ⭐ 18.5kagentic-radar vs DeepEval →Full profile →

7. 7. langwatch

   The platform for LLM evaluations and AI agent testing

   What sets it apart: Unified platform combining agent simulation, evaluation, observability, and prompt optimization with OpenTelemetry-native design — vs separate tools for tracing (Langfuse), eval (DeepEval), and prompt management

   Best for: Teams wanting eval + observability + prompt management in one tool; Agent simulation testing before production deployment; Organizations needing OpenTelemetry-native LLM observability

   ⭐ 4.9kagentic-radar vs langwatch →Full profile →

8. 8. Langfuse

   🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

   What sets it apart: Unlike LangSmith (LangChain-specific) or Helicone (proxy-based), Langfuse is fully open-source, framework-agnostic, and self-hostable, combining tracing, prompt management, evaluations, and datasets in a single platform built on ClickHouse for scalable production use.

   Best for: Teams operating production LLM applications who need tracing, prompt management, and evaluation in one platform; Organizations requiring self-hosted LLM observability for data privacy compliance

   ⭐ 35.2kagentic-radar vs Langfuse →Full profile →