
Manicode
Manicode Security · Coding
Manicode Forge is a library of 328 system prompts from Manicode Security that make AI coding assistants write secure-by-default code across 30+ frameworks.

About Manicode
What Is Manicode
Manicode is a secure coding company founded by Jim Manico, a longtime application security trainer and OWASP volunteer. Its flagship product, Manicode Forge, ships a catalog of 328 system prompts that change how AI coding assistants generate code.
The problem it targets is straightforward. Frontier models are trained to produce working code, not safe code. Ask an assistant for a login endpoint and you often get a version that builds, passes its tests, and still ships an SQL injection, a plaintext password comparison, and no rate limiting. Manicode's own testing found that even when models are told to write secure code, they still introduce vulnerabilities 23% of the time.
Each prompt is a system instruction tuned to one framework. You set it as the system message in your IDE, coding agent, or API call, and the model's output shifts toward parameterized queries, password hashing, validation, and access control. The prompts are plain markdown files, so there's no plugin to install and no vendor to lock into.
The main limits are the pricing model and the fact that prompts are guidance, not enforcement. Plans start at $1,000 per prompt with a five-prompt minimum, and Teams pricing begins at $10,000, which keeps the tool aimed at engineering teams and companies rather than solo hobbyists. A prompt steers the model but can't guarantee it follows every rule, so review still matters.
Getting Started
- Book a call with Manicode and pick the frameworks your team actually ships.
- Receive the prompt files for those frameworks in the model variant you use, such as Claude, Codex, Gemini, or Copilot.
- Set the prompt as the system instruction in your tool, whether that's Cursor, Claude Code, GitHub Copilot, or a direct API call.
- Ask for code the way you normally would, then test it with a security-sensitive request to confirm the controls show up.
- Roll the prompts out to the rest of the team and revisit them as the catalog updates.
Product Information
A quick look at Manicode's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Engineering teams shipping AI-generated code
- Security engineers who review AI output
- Web, API, and mobile developers
- Companies with compliance requirements
Tasks
- Generating secure authentication code
- Preventing injection in generated queries
- Securing REST and gRPC APIs
- Hardening agentic AI and RAG pipelines
Scenarios
- A fintech team using Claude Code for backend work
- A startup prototyping fast with Cursor
- A platform team standardizing tools across squads
- An enterprise preparing for a security audit
Key features
Framework-specific security prompts
Every prompt targets one framework and encodes the rules that matter for its APIs. A Django prompt covers ORM usage and template escaping; a React prompt covers XSS and CSP. That specificity is the core difference from a generic "write secure code" instruction.
Broad language and framework coverage
The catalog spans 15 languages and 30+ frameworks, including Python, JavaScript, TypeScript, Java, C#, Go, Rust, PHP, C++, Kotlin, Swift, Ruby, C, Scala, and Elixir. Teams working across a mixed stack can secure each part without buying separate tools.
Model variant support
Each prompt ships in variants tuned for different models, including Claude Opus 4.6, GPT 5.3 Codex, Gemini 3.1 Pro, Grok 4.1, and GitHub Copilot. Prompts differ from 800 to 2,000 tokens and lean toward dense, opinionated rules over vague guidance.
Standards-aligned coverage
The library maps its rules to OWASP ASVS 5.0, OWASP AISVS 1.0, the OWASP Agentic Top 10, CWE mitigations, and NIST SP 800-218. For teams facing audits, that mapping turns prompt selection into documented security work. For teams comparing this against generic AI secure code generation tools, the difference is the framework-level detail.
AI security category
Beyond classic app security, 41 prompts address agentic AI: agent frameworks, RAG security, agent IAM, AI supply chain risk, and governance. They point at failure modes that ordinary coding rules don't touch.
Drop-in deployment
Prompts are plain markdown files that work anywhere a system instruction is accepted, from GitHub Copilot, Cursor, and Windsurf to Claude Code, Codex, and direct Anthropic, OpenAI, or Gemini API calls. There's no SDK or wrapper in the loop.
Pros and cons
Pros
- Prompts plug into tools teams already use, so there's no new platform to adopt.
- Framework-specific rules produce more relevant code than a generic security instruction.
- Coverage across 30+ frameworks and 15 languages fits mixed-stack teams.
- Standards mapping to ASVS, AISVS, and NIST SSDF helps with audits and compliance work.
- Author Jim Manico brings deep OWASP experience, and the rules encode that expertise directly.
Cons
- Pricing starts at $1,000 per prompt with a five-prompt minimum, so it's out of reach for solo developers and small hobby projects.
- Prompts are guidance, not enforcement, so a model can still deviate and code review stays necessary.
- No free tier is published, which makes trying before buying harder.
- Enterprise features like SSO, SCIM, and SOC 2 reporting sit behind the top plan.
Frequently asked questions
Manicode is a secure coding company founded by Jim Manico. Its Manicode Forge product sells a library of 328 system prompts that configure AI coding assistants to generate secure-by-default code.
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