Estableciendo el estándar: SCW publica reglas de seguridad de codificación de IA gratuitas en GitHub
AI-assisted development is no longer on the horizon — it’s here, and it’s rapidly reshaping how software is written. Tools like GitHub Copilot, Cline, Roo, Cursor, Aider, and Windsurf are transforming developers into co-pilots of their own, enabling faster iteration and accelerating everything from prototyping to major refactoring projects.
But with this shift comes a familiar tension: speed vs. security.
At Secure Code Warrior, we’ve been thinking a lot about how to help developers stay secure while working with AI coding tools. That’s why we’re excited to launch something simple, powerful, and immediately useful: our AI Security Rules — a public, free-to-use resource available to everyone on GitHub. You don’t need to be a Secure Code Warrior customer to use them; we’re providing these rules as a free, community-driven foundation that anyone can adopt and extend into their own projects.
These rules are designed to act as guardrails, nudging AI tools toward safer coding practices, even when developers are moving at breakneck speed.
Summary for those in a hurry:
As AI coding tools like Copilot and Cursor become essential to modern development, security can't be an afterthought. That’s why we’ve built a set of lightweight, security-first rulesets designed to guide AI code generation toward safer defaults.
- Covers web frontend, backend, and mobile
- Easy to drop into AI tools
- Public, free-to-use, and ready to adopt into your own projects
Explore the rules → https://github.com/SecureCodeWarrior/ai-security-rules
Let’s make secure coding the default—even with AI at the keyboard.
1. Why rules matter in the age of AI-assisted coding
AI coding tools are incredibly helpful, but not infallible. While they can generate working code quickly, they often lack the nuance to understand the specific standards, conventions, and security policies of a given team or project.
This is where project-level rule files come into play.
Modern AI tools like Cursor and Copilot support configuration files that influence how code is generated. These rule files act like a whisper in the AI’s ear, telling it:
“In this project, we never concatenate SQL strings.”
“Prefer fetch with safe headers over insecure defaults.”
“Avoid using eval() unless you want a security audit.”
These rules aren’t a silver bullet, or a substitute for strong code review practices and security tooling, however they can help align AI-generated code with the practices that teams already follow or should follow for secure development.
2. What we built (and what we didn’t)
Our Starter Rules are available now in a public GitHub repository. They’re:
- Organized by domain – including web frontend, backend, and mobile
- Security-focused – covering recurring issues like injection flaws, unsafe handling, CSRF protection, weak auth flows, and more
- Lightweight by design – they’re meant to be a practical starting point, not an exhaustive rulebook
We know how valuable your AI context windows are and how quickly code consumes those tokens, so we’ve kept our rules clear, concise, and strictly focused on security. We made a deliberate decision to avoid language- or framework-specific guidance, opting instead for broadly applicable, high-impact security practices that work across a wide range of environments without becoming opinionated on architecture or design.
These rules are written to be easily dropped into the supported config formats of AI tools, with little to no refactoring. Think of them as a starting set of policies that nudge the AI toward secure defaults.
3. A new layer of defense
Here’s what this looks like in practice:
- When the AI suggests code that handles user input, it leans toward validation and encoding, not bare processing.
- When building database queries, it’s more likely to recommend parameterization, not string concatenation.
- When generating frontend auth flows, the AI will be more likely to promote token handling best practices, not insecure local storage hacks.
None of this replaces strategic developer risk management within a security program, including continuous security upskilling. It also doesn’t eliminate the need for security-proficient developers, especially as they increasingly prompt LLMs and review AI-generated code. These guardrails add a meaningful layer of defense—especially when developers are moving fast, multitasking, or just trusting the tool a little too much.
What’s next?
This isn’t a finished product—it’s a starting point.
As AI coding tools evolve, so must our approach to secure development. Our AI Security Rules are free to use, adaptable, and extendable to your projects. We’re committed to continuously evolving these rulesets, and we’d love your input — so try them out and let us know what you think.
Explore the rules on GitHub
Read the Using Rules guideline in SCW Explore
AI-assisted coding is already reshaping how we build software. Let’s make sure it’s secure from the start.
El desarrollo asistido por IA ya no está en el horizonte: ya está aquí y está cambiando rápidamente la forma en que se escribe el software. Herramientas como GitHub Copilot, Cline, Roo, Cursor, Aider y Windsurf están transformando a los desarrolladores en copilotos propios, lo que permite una iteración más rápida y acelera todo, desde la creación de prototipos hasta los principales proyectos de refactorización.
Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST.
Secure Code Warrior está aquí para que su organización le ayude a proteger el código durante todo el ciclo de vida del desarrollo de software y a crear una cultura en la que la ciberseguridad sea una prioridad. Ya sea administrador de AppSec, desarrollador, CISO o cualquier persona relacionada con la seguridad, podemos ayudar a su organización a reducir los riesgos asociados con el código inseguro.
Reserva una demostración
Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST.
Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST. She’s passionate about making secure development and compliance more practical and approachable for technical teams, bridging the gap between security expectations and the realities of modern software development.
AI-assisted development is no longer on the horizon — it’s here, and it’s rapidly reshaping how software is written. Tools like GitHub Copilot, Cline, Roo, Cursor, Aider, and Windsurf are transforming developers into co-pilots of their own, enabling faster iteration and accelerating everything from prototyping to major refactoring projects.
But with this shift comes a familiar tension: speed vs. security.
At Secure Code Warrior, we’ve been thinking a lot about how to help developers stay secure while working with AI coding tools. That’s why we’re excited to launch something simple, powerful, and immediately useful: our AI Security Rules — a public, free-to-use resource available to everyone on GitHub. You don’t need to be a Secure Code Warrior customer to use them; we’re providing these rules as a free, community-driven foundation that anyone can adopt and extend into their own projects.
These rules are designed to act as guardrails, nudging AI tools toward safer coding practices, even when developers are moving at breakneck speed.
Summary for those in a hurry:
As AI coding tools like Copilot and Cursor become essential to modern development, security can't be an afterthought. That’s why we’ve built a set of lightweight, security-first rulesets designed to guide AI code generation toward safer defaults.
- Covers web frontend, backend, and mobile
- Easy to drop into AI tools
- Public, free-to-use, and ready to adopt into your own projects
Explore the rules → https://github.com/SecureCodeWarrior/ai-security-rules
Let’s make secure coding the default—even with AI at the keyboard.
1. Why rules matter in the age of AI-assisted coding
AI coding tools are incredibly helpful, but not infallible. While they can generate working code quickly, they often lack the nuance to understand the specific standards, conventions, and security policies of a given team or project.
This is where project-level rule files come into play.
Modern AI tools like Cursor and Copilot support configuration files that influence how code is generated. These rule files act like a whisper in the AI’s ear, telling it:
“In this project, we never concatenate SQL strings.”
“Prefer fetch with safe headers over insecure defaults.”
“Avoid using eval() unless you want a security audit.”
These rules aren’t a silver bullet, or a substitute for strong code review practices and security tooling, however they can help align AI-generated code with the practices that teams already follow or should follow for secure development.
2. What we built (and what we didn’t)
Our Starter Rules are available now in a public GitHub repository. They’re:
- Organized by domain – including web frontend, backend, and mobile
- Security-focused – covering recurring issues like injection flaws, unsafe handling, CSRF protection, weak auth flows, and more
- Lightweight by design – they’re meant to be a practical starting point, not an exhaustive rulebook
We know how valuable your AI context windows are and how quickly code consumes those tokens, so we’ve kept our rules clear, concise, and strictly focused on security. We made a deliberate decision to avoid language- or framework-specific guidance, opting instead for broadly applicable, high-impact security practices that work across a wide range of environments without becoming opinionated on architecture or design.
These rules are written to be easily dropped into the supported config formats of AI tools, with little to no refactoring. Think of them as a starting set of policies that nudge the AI toward secure defaults.
3. A new layer of defense
Here’s what this looks like in practice:
- When the AI suggests code that handles user input, it leans toward validation and encoding, not bare processing.
- When building database queries, it’s more likely to recommend parameterization, not string concatenation.
- When generating frontend auth flows, the AI will be more likely to promote token handling best practices, not insecure local storage hacks.
None of this replaces strategic developer risk management within a security program, including continuous security upskilling. It also doesn’t eliminate the need for security-proficient developers, especially as they increasingly prompt LLMs and review AI-generated code. These guardrails add a meaningful layer of defense—especially when developers are moving fast, multitasking, or just trusting the tool a little too much.
What’s next?
This isn’t a finished product—it’s a starting point.
As AI coding tools evolve, so must our approach to secure development. Our AI Security Rules are free to use, adaptable, and extendable to your projects. We’re committed to continuously evolving these rulesets, and we’d love your input — so try them out and let us know what you think.
Explore the rules on GitHub
Read the Using Rules guideline in SCW Explore
AI-assisted coding is already reshaping how we build software. Let’s make sure it’s secure from the start.
AI-assisted development is no longer on the horizon — it’s here, and it’s rapidly reshaping how software is written. Tools like GitHub Copilot, Cline, Roo, Cursor, Aider, and Windsurf are transforming developers into co-pilots of their own, enabling faster iteration and accelerating everything from prototyping to major refactoring projects.
But with this shift comes a familiar tension: speed vs. security.
At Secure Code Warrior, we’ve been thinking a lot about how to help developers stay secure while working with AI coding tools. That’s why we’re excited to launch something simple, powerful, and immediately useful: our AI Security Rules — a public, free-to-use resource available to everyone on GitHub. You don’t need to be a Secure Code Warrior customer to use them; we’re providing these rules as a free, community-driven foundation that anyone can adopt and extend into their own projects.
These rules are designed to act as guardrails, nudging AI tools toward safer coding practices, even when developers are moving at breakneck speed.
Summary for those in a hurry:
As AI coding tools like Copilot and Cursor become essential to modern development, security can't be an afterthought. That’s why we’ve built a set of lightweight, security-first rulesets designed to guide AI code generation toward safer defaults.
- Covers web frontend, backend, and mobile
- Easy to drop into AI tools
- Public, free-to-use, and ready to adopt into your own projects
Explore the rules → https://github.com/SecureCodeWarrior/ai-security-rules
Let’s make secure coding the default—even with AI at the keyboard.
1. Why rules matter in the age of AI-assisted coding
AI coding tools are incredibly helpful, but not infallible. While they can generate working code quickly, they often lack the nuance to understand the specific standards, conventions, and security policies of a given team or project.
This is where project-level rule files come into play.
Modern AI tools like Cursor and Copilot support configuration files that influence how code is generated. These rule files act like a whisper in the AI’s ear, telling it:
“In this project, we never concatenate SQL strings.”
“Prefer fetch with safe headers over insecure defaults.”
“Avoid using eval() unless you want a security audit.”
These rules aren’t a silver bullet, or a substitute for strong code review practices and security tooling, however they can help align AI-generated code with the practices that teams already follow or should follow for secure development.
2. What we built (and what we didn’t)
Our Starter Rules are available now in a public GitHub repository. They’re:
- Organized by domain – including web frontend, backend, and mobile
- Security-focused – covering recurring issues like injection flaws, unsafe handling, CSRF protection, weak auth flows, and more
- Lightweight by design – they’re meant to be a practical starting point, not an exhaustive rulebook
We know how valuable your AI context windows are and how quickly code consumes those tokens, so we’ve kept our rules clear, concise, and strictly focused on security. We made a deliberate decision to avoid language- or framework-specific guidance, opting instead for broadly applicable, high-impact security practices that work across a wide range of environments without becoming opinionated on architecture or design.
These rules are written to be easily dropped into the supported config formats of AI tools, with little to no refactoring. Think of them as a starting set of policies that nudge the AI toward secure defaults.
3. A new layer of defense
Here’s what this looks like in practice:
- When the AI suggests code that handles user input, it leans toward validation and encoding, not bare processing.
- When building database queries, it’s more likely to recommend parameterization, not string concatenation.
- When generating frontend auth flows, the AI will be more likely to promote token handling best practices, not insecure local storage hacks.
None of this replaces strategic developer risk management within a security program, including continuous security upskilling. It also doesn’t eliminate the need for security-proficient developers, especially as they increasingly prompt LLMs and review AI-generated code. These guardrails add a meaningful layer of defense—especially when developers are moving fast, multitasking, or just trusting the tool a little too much.
What’s next?
This isn’t a finished product—it’s a starting point.
As AI coding tools evolve, so must our approach to secure development. Our AI Security Rules are free to use, adaptable, and extendable to your projects. We’re committed to continuously evolving these rulesets, and we’d love your input — so try them out and let us know what you think.
Explore the rules on GitHub
Read the Using Rules guideline in SCW Explore
AI-assisted coding is already reshaping how we build software. Let’s make sure it’s secure from the start.
Haga clic en el enlace de abajo y descargue el PDF de este recurso.
Secure Code Warrior está aquí para que su organización le ayude a proteger el código durante todo el ciclo de vida del desarrollo de software y a crear una cultura en la que la ciberseguridad sea una prioridad. Ya sea administrador de AppSec, desarrollador, CISO o cualquier persona relacionada con la seguridad, podemos ayudar a su organización a reducir los riesgos asociados con el código inseguro.
Ver informeReserva una demostración
Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST.
Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST. She’s passionate about making secure development and compliance more practical and approachable for technical teams, bridging the gap between security expectations and the realities of modern software development.
AI-assisted development is no longer on the horizon — it’s here, and it’s rapidly reshaping how software is written. Tools like GitHub Copilot, Cline, Roo, Cursor, Aider, and Windsurf are transforming developers into co-pilots of their own, enabling faster iteration and accelerating everything from prototyping to major refactoring projects.
But with this shift comes a familiar tension: speed vs. security.
At Secure Code Warrior, we’ve been thinking a lot about how to help developers stay secure while working with AI coding tools. That’s why we’re excited to launch something simple, powerful, and immediately useful: our AI Security Rules — a public, free-to-use resource available to everyone on GitHub. You don’t need to be a Secure Code Warrior customer to use them; we’re providing these rules as a free, community-driven foundation that anyone can adopt and extend into their own projects.
These rules are designed to act as guardrails, nudging AI tools toward safer coding practices, even when developers are moving at breakneck speed.
Summary for those in a hurry:
As AI coding tools like Copilot and Cursor become essential to modern development, security can't be an afterthought. That’s why we’ve built a set of lightweight, security-first rulesets designed to guide AI code generation toward safer defaults.
- Covers web frontend, backend, and mobile
- Easy to drop into AI tools
- Public, free-to-use, and ready to adopt into your own projects
Explore the rules → https://github.com/SecureCodeWarrior/ai-security-rules
Let’s make secure coding the default—even with AI at the keyboard.
1. Why rules matter in the age of AI-assisted coding
AI coding tools are incredibly helpful, but not infallible. While they can generate working code quickly, they often lack the nuance to understand the specific standards, conventions, and security policies of a given team or project.
This is where project-level rule files come into play.
Modern AI tools like Cursor and Copilot support configuration files that influence how code is generated. These rule files act like a whisper in the AI’s ear, telling it:
“In this project, we never concatenate SQL strings.”
“Prefer fetch with safe headers over insecure defaults.”
“Avoid using eval() unless you want a security audit.”
These rules aren’t a silver bullet, or a substitute for strong code review practices and security tooling, however they can help align AI-generated code with the practices that teams already follow or should follow for secure development.
2. What we built (and what we didn’t)
Our Starter Rules are available now in a public GitHub repository. They’re:
- Organized by domain – including web frontend, backend, and mobile
- Security-focused – covering recurring issues like injection flaws, unsafe handling, CSRF protection, weak auth flows, and more
- Lightweight by design – they’re meant to be a practical starting point, not an exhaustive rulebook
We know how valuable your AI context windows are and how quickly code consumes those tokens, so we’ve kept our rules clear, concise, and strictly focused on security. We made a deliberate decision to avoid language- or framework-specific guidance, opting instead for broadly applicable, high-impact security practices that work across a wide range of environments without becoming opinionated on architecture or design.
These rules are written to be easily dropped into the supported config formats of AI tools, with little to no refactoring. Think of them as a starting set of policies that nudge the AI toward secure defaults.
3. A new layer of defense
Here’s what this looks like in practice:
- When the AI suggests code that handles user input, it leans toward validation and encoding, not bare processing.
- When building database queries, it’s more likely to recommend parameterization, not string concatenation.
- When generating frontend auth flows, the AI will be more likely to promote token handling best practices, not insecure local storage hacks.
None of this replaces strategic developer risk management within a security program, including continuous security upskilling. It also doesn’t eliminate the need for security-proficient developers, especially as they increasingly prompt LLMs and review AI-generated code. These guardrails add a meaningful layer of defense—especially when developers are moving fast, multitasking, or just trusting the tool a little too much.
What’s next?
This isn’t a finished product—it’s a starting point.
As AI coding tools evolve, so must our approach to secure development. Our AI Security Rules are free to use, adaptable, and extendable to your projects. We’re committed to continuously evolving these rulesets, and we’d love your input — so try them out and let us know what you think.
Explore the rules on GitHub
Read the Using Rules guideline in SCW Explore
AI-assisted coding is already reshaping how we build software. Let’s make sure it’s secure from the start.
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Shannon Holt is a cybersecurity product marketer with a background in application security, cloud security services, and compliance standards like PCI-DSS and HITRUST.
Secure Code Warrior está aquí para que su organización le ayude a proteger el código durante todo el ciclo de vida del desarrollo de software y a crear una cultura en la que la ciberseguridad sea una prioridad. Ya sea administrador de AppSec, desarrollador, CISO o cualquier persona relacionada con la seguridad, podemos ayudar a su organización a reducir los riesgos asociados con el código inseguro.
Reserva una demostraciónDescargarRecursos para empezar
Temas y contenido de formación sobre código seguro
Nuestro contenido líder en la industria siempre está evolucionando para adaptarse al cambiante panorama del desarrollo de software teniendo en cuenta su función. Se ofrecen temas que abarcan desde la IA hasta la inyección de XQuery para distintos puestos, desde arquitectos e ingenieros hasta directores de productos y control de calidad. Obtenga un adelanto de lo que ofrece nuestro catálogo de contenido por tema y función.
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