head to head · open source

giskard-oss vs FuzzyAI

giskard-oss has 5,830 GitHub stars, 537 forks, 64 open issues and last shipped 2 days ago. FuzzyAI has 1,576 stars, 217 forks, 7 open issues and last shipped 8 months ago. giskard-oss leads on adoption by 270% (5,830 vs 1,576 stars). giskard-oss is written in Python under Apache-2.0; FuzzyAI is written in Jupyter Notebook under Apache-2.0. giskard-oss has attracted 9% as many forks as stars, FuzzyAI 14%. giskard-oss was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 4 topic tags (ai-red-team, llm, llm-evaluation, llm-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.

giskard-oss ★ 5.8K FuzzyAI ★ 1.6K category AI & Machine Learning

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Side by side

giskard-oss FuzzyAI
GitHub stars ★ 5.8K ★ 1.6K
License Apache-2.0 Apache-2.0
Written in Python Jupyter Notebook
Last push 2026-09-18 2026-02-06
Forks ⑂ 537 ⑂ 217
Self-hosting Yes Yes
Data ownership Your server Your server

pick giskard-oss if

  • You weight community size — 5.8K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full giskard-oss profile →

pick FuzzyAI if

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

full FuzzyAI profile →

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 →

About FuzzyAI

FuzzyAI is an open source fuzzer for large language model APIs. It lives in the AI security and red teaming ecosystem. It uses automated prompt mutation to test whether a model or API accepts jailbreak attempts. The project helps developers and security researchers find, evaluate, and reduce exposure to harmful or unwanted model behavior.

read the full FuzzyAI overview →

More in AI & Machine Learning

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More AI Security & Privacy projects

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

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

Frequently asked questions

Is giskard-oss or FuzzyAI more popular?

giskard-oss has 5,830 GitHub stars and FuzzyAI has 1,576. giskard-oss has the larger community by that measure.

Are giskard-oss and FuzzyAI free?

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

What is the difference between giskard-oss and FuzzyAI?

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

Which should I choose, giskard-oss or FuzzyAI?

Choose giskard-oss if you want the larger community (5,830 stars) or its Apache-2.0 licence terms. Choose FuzzyAI if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.