L'IA peut écrire du code, mais ce sont les compétences qui le sécurisent.

Notre plateforme de codage sécurisé pour les entreprises permet de développer les compétences nécessaires pour sécuriser à la fois le code humain et celui généré par l'IA sans ralentir la livraison.

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De la première entreprise de formation en codage sécurisé
Le déficit de compétences

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.

Les développeurs sont désormais tenus de :
Identify vulnerabilities in AI-generated code
Identifier les modèles non sécurisés introduits par les LLM
Appliquez des normes de codage sécurisées dans tous les langages.
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.

Présentation du produit

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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Compétences clés

Comprehensive AI security training for modern development

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AI security challenges for developers

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

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

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

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

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).

Gouvernance des logiciels d'intelligence artificielle

Le plan de contrôle pour le développement basé sur l'IA

Rendez le développement basé sur l'IA visible, sécurisé et résilient, en prévenant les vulnérabilités avant la mise en production afin que les équipes puissent avancer rapidement en toute confiance.

Quêtes
Guided, role-based learning paths.
Laboratoires de codage
Remediation in live environments.
Les défis de l'IA
Secure code in AI workflows.
Missions
Immersive AI security simulations.

Quêtes

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
Modélisation des menaces à l'aide de l'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

Laboratoires de codage

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.
Injection directe immédiate
Injection directe immédiate
Injection directe immédiate

Les défis de l'IA

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
Injection directe immédiate
Agence excessive
Traitement incorrect des sorties
Injection indirecte immédiate
LLM Awareness
Divulgation d'informations sensibles
Vector & Embedding Weaknesses
Résultats et impact

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.

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En cours
Réduction des vulnérabilités introduites
53%
Réduction du délai moyen d'
ation pour remédier aux problèmes
3x+
AI/LLM learning
activities
1k+
Comprehensive secure coding languages covered
75+
Comment cela fonctionne-t-il ?

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:

Injection directe immédiate
Agence excessive
Traitement incorrect des sorties
Injection indirecte immédiate
Divulgation d'informations sensibles
Supply ChainMCP, Agents, and AI Infrastructure Security
Fuite de l'invite du système
Faiblesses des vecteurs et des intégrations
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
Modélisation des menaces à l'aide de l'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

Injection directe immédiate
Agence excessive
Insuffisance de la journalisation et de la surveillance
Divulgation d'informations sensibles
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
Injection directe immédiate
Injection indirecte immédiate
Information Exposure: Sensitive Data Exposure
Insuffisance de la journalisation et de la surveillance
Insufficient Transport Layer Protection: Unprotected Transport of Sensitive Information
Server-Side Request Forgery: Server-Side Request Forgery
Vulnerable Components: Using Known Vulnerable Components
À qui s'adresse ce produit ?

Security, engineering, and learning leaders responsible for secure development

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

À l'attention des responsables de la sécurité et de la gouvernance de l'IA

Démontrez les compétences mesurables des développeurs et réduisez les risques logiciels dans le cadre du développement humain et assisté par l'IA.

Pour les responsables de la formation et du développement

Mettez en place des programmes de codage sécurisé structurés et mesurables qui favorisent l'adoption, démontrent leur impact et s'alignent sur les exigences de conformité de l'entreprise.

À l'attention des responsables techniques

Permettre aux développeurs de créer un code résilient et sécurisé tout en maintenant la cadence et en réduisant les retouches.

À l'attention des responsables de la sécurité des applications

Renforcez la sécurité axée sur les développeurs et réduisez les vulnérabilités introduites sans augmenter les effectifs chargés de la révision.

Secure AI-generated code starts with trained developers

Renforcez les compétences en matière de codage sécurisé, réduisez les vulnérabilités introduites et instaurez une confiance mesurable envers les développeurs au sein de votre organisation.

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indice de confiance
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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Détails de l'assistance pour attirer les clients qui pourraient être indécis.

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