FREEDOM251

Freedom251 › AI Red Teaming Tools

Prompt Fuzzer

Paid LinuxMacSelf-hostedWindows

Visit Prompt Fuzzer Alternatives

Prompt Fuzzer's own site

What Prompt Fuzzer is

Prompt Fuzzer is a free, open-source tool for developers who want to assess and improve the resilience of AI application system prompts. It creates varied test scenarios and uses malicious prompt variations as targets for dynamic LLM-based attacks. Its approach centers on prompts and how they interact with the target program rather than analyzing code paths. Developers can run campaigns in an interactive chat, from the command line, or through multithreaded testing. In the Playground, they can adjust settings through chat iterations, with each iteration starting a new fuzzing campaign. The repository lists 16 attack types, including jailbreak, prompt injection, RAG poisoning, and system prompt extraction, plus support for 16 LLM providers such as OpenAI, Anthropic, Azure OpenAI, Cohere, Google PaLM, and Ollama. Custom and self-hosted endpoints are supported, including Ollama and OpenAI-compatible endpoints. Prompt Fuzzer is self-hosted and available from GitHub; installation uses pip and requires Python 3.10 or newer. Tests consume tokens. RAG testing needs an embedding provider and model, and ChromaDB is installed by default with the package. Developers can also contribute attack tests through GitHub.

Who it suits

Prompt Fuzzer suits developers building generative AI, LLM-based, or RAG applications who want to evaluate system prompt resilience. Its chat, command-line, and multithreaded modes provide options for running campaigns, while custom and self-hosted endpoints support different target setups.

What it does well

  • Free and open source.
  • Offers interactive chat, command-line, and multithreaded testing.
  • Repository lists 16 attack types and 16 LLM providers.
  • Supports custom and self-hosted LLM endpoints.
  • Playground iterations start new fuzzing campaigns.

What to know first

  • Tests consume tokens.
  • RAG testing requires an embedding provider and model.
  • Installation requires Python 3.10 or newer.

Limits

The tool consumes tokens during use. RAG tests require an embedding provider and embedding model; ChromaDB is installed by default with the package.

Getting started

  1. Open the Prompt Fuzzer page at https://prompt.security/fuzzer.
  2. Get the tool from GitHub.
  3. Install it with pip; Python 3.10 or newer is required.
  4. Choose interactive chat, command-line, or multithreaded testing.
  5. For RAG tests, provide an embedding provider and model.

Verdict

Choose Prompt Fuzzer if you build AI applications and need to probe system prompts with automated attacks across multiple testing modes. Look elsewhere if token-consuming tests or the embedding requirements for RAG testing do not suit your workflow.

Questions

How much does Prompt Fuzzer cost?

It is free and open source.

Where can I get Prompt Fuzzer?

The maker directs users to GitHub. Installation is through pip and requires Python 3.10 or newer.

Which testing modes does it offer?

It supports interactive chat, command-line, and multithreaded testing.

Which LLM providers and endpoints does it support?

The repository lists 16 providers, including OpenAI, Anthropic, Azure OpenAI, Cohere, Google PaLM, and Ollama. Custom and self-hosted endpoints, including OpenAI-compatible endpoints, are also supported.

What does RAG testing require?

RAG tests need an embedding provider and model. ChromaDB is installed by default with the package.

Facts from Prompt Fuzzer's own pages

Access
The maker directs users to GitHub to get the tool; the page does not state specific operating system support or integrations. · prompt.security, 5 Oct 2026
Approach
The maker says the tool focuses on prompt-based systems and their target program interactions, unlike symbolic execution methods that analyze code paths. · prompt.security, 5 Oct 2026
Attack coverage
The repository lists 16 attack types, including jailbreak, prompt injection, RAG poisoning, and system prompt extraction. · github.com, 5 Oct 2026
Attack testing
The fuzzing process uses dynamic LLM-based attacks. · prompt.security, 5 Oct 2026
Community contributions
The maker invites the community to contribute additional attack tests through the GitHub repository. · github.com, 5 Oct 2026
Custom endpoints
The tool supports custom and self-hosted LLM endpoints, including Ollama and OpenAI-compatible endpoints. · github.com, 5 Oct 2026
Fuzzing engine
The fuzzer generates diverse test scenarios and uses variations of malicious prompts as fuzz targets for an AI system. · prompt.security, 5 Oct 2026
Installation
The repository instructs users to install the tool with pip and requires Python 3.10 or newer. · github.com, 5 Oct 2026
Intended users
The page presents the tool for developers of AI applications seeking to evaluate and improve prompt resilience and safety. · prompt.security, 5 Oct 2026
Interactive playground
The maker says users can iterate on system prompt settings in a chat-format Playground, with each iteration representing a fuzzing campaign. · prompt.security, 5 Oct 2026
LLM providers
The repository lists support for 16 LLM providers, including OpenAI, Anthropic, Azure OpenAI, Cohere, Google PaLM, and Ollama. · github.com, 5 Oct 2026
Open source
The maker describes Prompt Fuzzer as an open-source fuzzing tool and directs users to get it from GitHub. · prompt.security, 5 Oct 2026
Playground
The Playground lets users iterate settings in a chat format, with each iteration representing a new fuzzing campaign. · prompt.security, 5 Oct 2026
Purpose
Prompt Fuzzer tests and hardens the system prompts of AI applications against vulnerabilities. · prompt.security, 5 Oct 2026
RAG testing requirement
RAG tests require an embedding provider and embedding model; the repository says ChromaDB is installed by default with the package. · github.com, 5 Oct 2026
Target users
The maker presents the tool for developers building AI applications who want to assess and improve system prompt resilience. · prompt.security, 5 Oct 2026
Testing modes
It supports interactive chat mode, command-line mode, and multithreaded testing. · github.com, 5 Oct 2026
Token usage
The maker warns that using Prompt Fuzzer consumes tokens. · github.com, 5 Oct 2026

Where Prompt Fuzzer stands on Freedom251

Look at these too