La IA puede escribir código, pero la habilidad lo asegura.

Nuestra plataforma de codificación segura para empresas desarrolla las habilidades necesarias para proteger tanto el código generado por humanos como por IA sin ralentizar la entrega.

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De la empresa líder en formación en programación segura

La brecha de habilidades

AI accelerates code. AI security skills must keep pace.

AI coding assistants can generate production-ready code in seconds. But speed does not equal security. AI security training helps developers identify vulnerabilities in AI-generated code, prevent prompt injection, and apply secure coding practices across modern AI workflows.

Ahora se espera que los desarrolladores:

Identify vulnerabilities in AI-generated code

Reconocer los patrones inseguros introducidos por los LLM.

Aplicar estándares de codificación segura en todos los lenguajes.

Prevent new risks like prompt injection

Nearly 45% of AI-generated code contains known security vulnerabilities. Securing AI-generated code starts with developer capability to identify and fix risks before code reaches production.

Descripción general del producto

Build developer capability for secure AI development

Secure Code Warrior Learning provides AI security training that builds the skills behind every commit. Developers learn to secure AI-generated code through hands-on practice across real-world AI workflows, reducing risk at the source.

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Capacidades básicas

Comprehensive AI security training for modern development

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AI security challenges for developers

Simulated AI-assisted development workflows

Developers learn to secure AI-generated code through interactive challenges that simulate real-world AI workflows. Learn to detect insecure patterns, validate outputs, and prevent vulnerabilities in a safe, controlled environment.

AI and LLM vulnerability training

Learn to identify real AI risk patterns

Learning covers emerging AI vulnerabilities including prompt injection, excessive agency, system prompt leakage, sensitive data exposure, and vector and embedding weaknesses.

Modern AI frameworks and environments

Secure real-world AI stacks

Developers train across production AI technologies including Python (LangChain, MCP), Terraform (AWS Bedrock), and modern backend frameworks powering AI applications.

LLM missions and coding labs

Apply AI security skills in real scenarios

Developers build capability through immersive Missions and hands-on Coding Labs that simulate real-world AI security scenarios and vulnerability exploitation patterns.

AI security concepts and design patterns

Build foundational AI security knowledge

Developers learn how to securely use AI through topics like AI risk and security, threat modeling with AI, OWASP Top 10 for LLMs, and AI agent protocols (MCP, A2A, ACP).

Gobernanza del software de IA

El plano de control para el desarrollo impulsado por la IA

Haga que el desarrollo impulsado por la IA sea visible, seguro y resistente, previniendo vulnerabilidades antes de la producción para que los equipos puedan avanzar rápidamente con confianza.

Misiones

Guided, role-based learning paths.

Laboratorios de codificación

Remediation in live environments.

AI Challenges

Secure code in AI workflows.

Missions

Immersive AI security simulations.

Misiones

Discover Quests

Quests combine AI Challenges, labs, and missions into guided programs aligned to real-world AI risks and concepts

AI/LLM SECURITY

AI Agents and their Protocols (MCP, A2A and ACP)

Coding With AI

Introduction to AI Risk & Security

LLM Security Design Patterns

OWASP Top 10 for LLM Applications

Modelado de amenazas con IA

Vibe Coding: Risk Management Framework

CYBERMON 2025 BEAT THE BOSS

Bypassaur: Direct Prompt Injection

Keykraken: Indirect Prompt Injection

Promptgeist: Vector and Embedding Weaknesses

Proxysurfa: Excessive Agency

Laboratorios de codificación

Discover Coding Labs

Practice real-world AI and application security scenarios in live coding environments. Fix vulnerabilities as they would appear in actual development work — not just theory.

Inyección directa inmediata

AI Challenges

Discover AI Challenges

Over 800 challenges that simulate real AI-assisted development workflows. Build the ability to detect insecure patterns, validate AI outputs, and prevent vulnerabilities before they reach production.

800+ AI security challenges

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Missions

Discover missions

Apply skills across complex, multi-step scenarios that simulate authentic AI risks. Missions build the muscle memory to recognise and respond to real threats in context.

AI/LLM SECURITY

Inyección directa inmediata

Agencia excesiva

Manejo inadecuado de la salida

Inyección indirecta de comandos

LLM Awareness

Divulgación de información confidencial

Vector & Embedding Weaknesses

Resultados e impacto

Reduce AI-driven risk at the source of code creation through developer training

Secure Code Warrior delivers AI security training that builds developer capability to identify and prevent vulnerabilities in both human-written and AI-generated code. Through hands-on learning and real-world AI security scenarios, organizations reduce recurring vulnerabilities, strengthen secure coding behavior, and demonstrate measurable improvement across modern development workflows.

*En curso

Reducción de las vulnerabilidades introducidas

53%+

Más rápido significa un tiempo de reparación más rápido (
).

3x+

AI/LLM learning
activities

1k+

Comprehensive secure coding languages covered

75+

Cómo funciona

What developers learn in AI security training

Coverage spans LLM vulnerabilities, agent protocols, infrastructure security, and foundational AI security design — mapped to real developer workflows.

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LLM Vulnerability Coverage

Practice real-world AI and LLM security risks.

AI security training teaches developers how to identify, prevent, and remediate vulnerabilities in AI-generated code and modern AI systems, including:

Inyección directa inmediata

Agencia excesiva

Manejo inadecuado de la salida

Inyección indirecta de comandos

Divulgación de información confidencial

Supply ChainMCP, Agents, and AI Infrastructure Security

Fuga de indicaciones del sistema

Debilidades de los vectores y las incrustaciones

AI Security Concepts and Design

Build foundational AI security knowledge

Developers learn how to securely design and review AI systems through:

AI Agents and their Protocols (MCP, A2A and ACP)

Coding With AI

Introduction to AI Risk & Security

LLM Security Design Patterns

OWASP Top 10 for LLM Applications

Modelado de amenazas con IA

Vibe Coding: Risk Management Framework

MCP, Agents & AI Infrastructure

Secure AI agents, protocols, and cloud AI environments

Understand and mitigate risks across agent-based systems and AI infrastructure, including MCP and cloud AI services:

Bedrock (Cloud AI Infrastructure)

Secure AI services and model integrations

Inyección directa inmediata

Agencia excesiva

Registro y supervisión insuficientes

Divulgación de información confidencial

MCP (Model Context Protocol)

Model Context Protocol — Secure AI agents and protocol interactions

Access Control: Missing Function Level Access Control

Authentication: Improper Authentication

Authentication: Insufficiently Protected Credentials

Inyección directa inmediata

Inyección indirecta de comandos

Information Exposure: Sensitive Data Exposure

Registro y supervisión insuficientes

Insufficient Transport Layer Protection: Unprotected Transport of Sensitive Information

Server-Side Request Forgery: Server-Side Request Forgery

Vulnerable Components: Using Known Vulnerable Components

Para quién es

Security, engineering, and learning leaders responsible for secure development

Support secure AI development with role-specific capabilities tailored to your organization’s needs.

Para los responsables de seguridad y gobernanza de la IA

Demuestre una competencia cuantificable como desarrollador y reduzca los riesgos del software en el desarrollo asistido por personas y por IA.

Para líderes en aprendizaje y desarrollo

Ofrece programas de codificación segura estructurados y cuantificables que impulsen la adopción, demuestren su impacto y se ajusten a los requisitos de cumplimiento normativo de la empresa.

Para líderes de ingeniería

Permite a los desarrolladores escribir código resistente y seguro, al tiempo que se mantiene la velocidad y se reduce la necesidad de volver a trabajar.

Para los líderes de AppSec

Amplíe la seguridad impulsada por los desarrolladores y reduzca las vulnerabilidades introducidas sin aumentar el número de revisores.

Secure AI-generated code starts with trained developers

Fortalezca las habilidades de codificación segura, reduzca las vulnerabilidades introducidas y genere confianza medible en los desarrolladores de toda su organización.

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AI security training for developers FAQs

Secure AI-assisted development starts with developer capability

Learn how Secure Code Warrior helps teams adopt AI safely, reduce risk, and build measurable developer capability.

How do developers learn to secure AI-generated code?

Developers learn to secure AI-generated code through hands-on AI security training in simulated AI workflows.

Secure Code Warrior provides Quests, AI Challenges, Coding Labs, and Missions that teach developers how to identify insecure patterns, validate outputs, and prevent vulnerabilities before code reaches production.

What security risks does AI-generated code introduce?

AI-generated code can introduce vulnerabilities such as prompt injection, excessive agency, sensitive data exposure, and insecure output handling.

These risks often appear in otherwise functional code, making them difficult to detect without developer awareness and training.

How is AI security training different from traditional secure coding training?

Secure Code Warrior delivers interactive, AI security training that focuses on how developers interact with AI systems, not just how they write code.

It teaches developers how to validate AI outputs, recognize insecure patterns introduced by LLMs, and apply secure coding practices across AI-assisted workflows.

Traditional training focuses on known vulnerabilities, while AI security training prepares developers for emerging, dynamic risks.

How does Secure Code Warrior support AI security training?

Secure Code Warrior builds developer capability through hands-on learning across AI Challenges, Missions, Coding Labs, and Quests.

Developers practice securing AI-generated code in real-world scenarios, helping reduce vulnerabilities at the source and support AI Software Governance.

What AI technologies and frameworks are covered?

Secure Code Warrior provides learning across modern AI technologies and frameworks, including:

AI agents and protocols (MCP, A2A, ACP)
Python LangChain
Python MCP
Terraform AWS (Bedrock)
Typescript LangChain
LLM security concepts and design patterns

This ensures developers are prepared to secure real-world AI systems and workflows.

How can organizations govern AI-assisted development and reduce risk?

Organizations govern AI-assisted development by gaining visibility into how AI is used, applying governance policies within development workflows, and strengthening developer capability.

Secure Code Warrior supports this through Trust Agent AI, which provides visibility into AI usage across development workflows, correlates risk at the commit level, and enforces security policies. Combined with hands-on learning, this helps organizations reduce risk before vulnerabilities reach production.

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