HouYi
HouYi: A focused local framework for developers testing prompt injection in LLM-integrated applications. Ranked #26 of 27 in AI Red Teaming Tools by our editors (6.7/10); pricing: Open source; best for developers testing prompt injection locally.
At a glance
- Editor score6.7 / 10
- PricingOpen source
- Best forDevelopers testing prompt injection locally
- Paid fromFree
- Automation levelAutomated
- Facts checked21 Sep 2026
Where it wins
- Automates prompt-injection generation and iterative optimization
- Supports custom application harnesses and attack intentions
- Includes a demo application and attack workflow
Where it doesn't
- Focused on prompt injection rather than multiple attack categories
- Uses OpenAI as its listed integration
- Requires local Python installation and self-hosted operation
Our verdict on HouYi
HouYi is an open-source framework for researchers and developers assessing applications that incorporate large language models. Its focus is prompt-injection testing: the project generates and injects prompts into LLM-integrated applications, helping teams examine how their own applications respond to a defined attack intention. A demo application and attack workflow provide a concrete starting point, while the harness abstraction connects testing to real-world applications.
The main strength is customization. HouYi supports custom application harnesses and custom attack intentions, so developers can adapt the testing workflow to their application rather than relying only on fixed examples. Iterative prompt optimization adds automation to the attack-generation process, making the tool a fit for development-stage security research and repeatable local experiments. Installation is Python-based and requires configuration of an OpenAI API key, which makes the setup suitable for teams comfortable managing local developer tooling and application-specific test harnesses.
HouYi remains deliberately narrow in scope. Its listed attack category is prompt injection, and OpenAI is the stated integration, so teams assessing a wider range of attack types or model providers may need additional tooling. The self-hosted deployment model suits developers who want local control, while the absence of continuous monitoring makes it less appropriate as an always-on operational security layer. Pick HouYi when the priority is automated, customizable prompt-injection testing during application development or research. Choose a broader approach when ongoing monitoring, multiple attack categories, or broader platform coverage is required.
Your product? Our editors can test HouYi in depth and publish a review, labelled as paid · from $149/mo →
HouYi pricing
HouYi fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Attack categories | prompt injection |
| Target systems | LLM-integrated applications |
| Automation level | Automated |
| Custom tests | Yes |
| Deployment | Self_hosted |
| Continuous monitoring | No |
| Report exports | Not verified |
| Deployment | Self-hosted |
| Support | Email, Docs |
| Built for | Solo, Small business (editorial estimate) |
| Integrations | 1 integrations: OpenAI |
| Pricing | Open source |
| Website | github.com |
| Facts checked | 21 Sep 2026 |
HouYi integrations
HouYi lists 1 integrations on its own site.
- OpenAI
Alternatives to HouYi
- AgentSealContinuous AI red teaming across agents, MCP, RAG, prompts, and multimodal systems.9.4
- PromptfooA broad open-source choice for evaluating and red-teaming AI applications.9.3
- ProofLayerA focused platform for automated, continuous testing of agents, MCP servers, and LLM applications.9.1
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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