head to head · open source

shannon vs giskard-oss

shannon has 48,105 GitHub stars, 5,515 forks, 18 open issues and last shipped 10 days ago. giskard-oss has 5,823 stars, 537 forks, 64 open issues and last shipped 2 days ago. shannon leads on adoption by 726% (48,105 vs 5,823 stars). shannon is written in TypeScript under AGPL-3.0; giskard-oss is written in Python under Apache-2.0. shannon has attracted 11% as many forks as stars, giskard-oss 9%. giskard-oss was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-security), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

shannon ★ 48K giskard-oss ★ 5.8K category AI & Machine Learning

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Side by side

shannon giskard-oss
GitHub stars ★ 48K ★ 5.8K
License AGPL-3.0 Apache-2.0
Written in TypeScript Python
Last push 2026-09-08 2026-09-16
Forks ⑂ 5.5K ⑂ 537
Self-hosting Yes Yes
Data ownership Your server Your server

pick shannon if

  • You weight community size — 48K stars and counting
  • You want the AGPL-3.0 license terms
  • Your stack matches TypeScript
  • You value the larger contributor base for long-term maintenance

full shannon profile →

pick giskard-oss if

  • You want the giskard-oss feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and giskard-oss fits your workflow better

full giskard-oss profile →

About shannon

Shannon is an autonomous AI pentester for web applications and APIs that reads an application's source code, identifies attack paths, and executes real exploits so that only vulnerabilities with a working proof of concept are reported, built for AppSec, DevSecOps, and security engineering teams that ship code continuously.

read the full shannon overview →

About giskard-oss

Giskard OSS is an open source Python library for evaluating, red teaming and testing LLM agents and RAG pipelines, built for developers, ML engineers and AI security teams that need reproducible checks on non deterministic systems.

read the full giskard-oss overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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strix vs shannon strix vs giskard-oss strix vs skillspector strix vs ifixai strix vs codex-security strix vs garak strix vs ai-infra-guard strix vs agentic-bug-hunter openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse

More AI Security & Privacy projects

Compare either of these against the rest of the AI Security & Privacy field.

shannon vs strix shannon vs SkillSpector shannon vs iFixAi shannon vs codex-security shannon vs garak shannon vs AI-Infra-Guard shannon vs Agentic-Bug-Hunter shannon vs nono shannon vs CyberStrike shannon vs AiSOC shannon vs pentest-ai-agents shannon vs toolhive

Frequently asked questions

Is shannon or giskard-oss more popular?

shannon has 48,105 GitHub stars and giskard-oss has 5,823. shannon has the larger community by that measure.

Are shannon and giskard-oss free?

Both are open source. shannon is licensed under AGPL-3.0 and giskard-oss under Apache-2.0. Neither carries a licence fee.

What is the difference between shannon and giskard-oss?

shannon is written in TypeScript and giskard-oss in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, shannon or giskard-oss?

Choose shannon if you want the larger community (48,105 stars) or its AGPL-3.0 licence terms. Choose giskard-oss if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.