AI Made Development Faster. It Also Changed the Risk Model.

Security Journey transforms how developers use AI and LLMs—securely, effectively, and without compromise

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AI Security Gap Widens

AI is evolving faster than security skills are keeping up

Developer Adoption
Developers are increasingly using AI to ship code faster, but many lack guidance on secure practices, leaving gaps in protection.
Threat Sophistication
AI-driven attacks are evolving faster than traditional defenses. Security measures that once worked are no longer enough.
Security Visibility
Organizations have more AI-powered tools than ever, but limited insight into vulnerabilities. Without oversight, AI can unintentionally introduce risks.

Gain Visibility into How Developers Use AI and Where Risk Exists

Surface AI-assisted coding usage and tools via our Developer Profile to target training and manage risk.

Baseline AI/LLM knowledge of foundational risks and advanced attack vectors to measure growth and target training with our Developer Security Knowledge Assessments.

Learn what AI/LLM related CWEs are being committed to code through your scanning tool data via our GitHub Integration

Read more about understanding your developers through Developer Insights

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Build Proactive Guidance to keep you team moving and safe

Aspen: Guardian AI takes real findings from your CI scanners and converts them into small, tailored updates to your AI assistant’s existing rule file.

Aspen: Hints AI is available for developers to get assistance if they get stuck on a hands-on assignment.

Read more about Aspen: Guardian AI

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Engage Developers around AI/LLM & Secure Code

Create Tournaments/CTF to keep developers engaged and encourage friendly competition

Award developers with Certificates to share learner competency and achievements both internally and externally while simultaneously motivating learners to share their successes with others.

Read more about Engaging Your Developers

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Modern AI Development Learning Path

The Modern AI Development Path prepares developers for the evolving role of AI in modern software development.

Learners will understand how to use AI tools effectively by applying clear context, constraints, and oversight through hands-on lessons covering prompting best practices, rule-based workflows, AI agents, and scalable AI systems.

OWASP Top 10 for Large Language Model Applications Learning Paths

The OWASP Top 10 for LLM Applications Path equips developers and security-minded builders to recognize and mitigate the most common vulnerabilities in LLM-enabled systems.

Learners will explore real-world attack patterns and defenses—covering prompt injection, system prompt leakage, sensitive data exposure, supply chain risk, data and model poisoning, excessive agency, insecure plugins, unsafe output handling, RAG/vector weaknesses, misinformation, and cost-exhaustion threats—so they can design and operate safer AI applications.

AI Business Learner Learning Path

The AI Business Learner Path provides a clear, end-to-end understanding of how AI/LLM systems are built and governed—without requiring deep engineering specialization.

Learners will map the AI development lifecycle from data and model engineering through application integration, tooling, governance, and secure development practices, gaining the vocabulary and context needed to make informed decisions, manage risk, and align teams around responsible AI delivery.

The AI Challenges / Capture the Flag Learning Path

The AI Challenges / Capture The Flag Path builds real-world, hands-on skill by immersing learners in interactive challenges that mirror how LLM applications are attacked in practice.

Learners will work through progressively challenging, CTF-style exercises focused on extracting hidden instructions and manipulating retrieval-augmented systems, reinforcing how attackers think and how secure designs prevent compromise.