AI-generated code is often insecure by default. Learn how to use AI as a security force-multiplier to audit, harden, and verify your applications.
LLMs prioritize functional code over secure code. Without senior-level security judgment, AI is simply the fastest way to build a vulnerability.
Stop worrying about what AI missed. Learn to use it to double-check your own work and its own output.
Learn why AI often defaults to insecure code (hallucinated libs, outdated practices) and how to fix the starting point.
Turn feature descriptions into detailed threat models using AI to identify potential attack vectors before writing code.
Set up a repeatable process for AI-driven code reviews that focus specifically on the OWASP Top 10.
Use AI to audit JWT implementations, session management, and multi-factor auth flows for subtle logic flaws.
AI excels at syntax, but humans excel at logic. Learn to steer AI to find business logic errors that tools miss.
Prompting patterns to audit third-party packages and identify potential supply chain risks in your repo.
Rarely. But it is incredible at finding common mistakes (OWASP Top 10) and logic flaws that human developers miss when they're in a rush to ship. We focus on the 95% of common vulnerabilities.
Absolutely. We teach mental models and prompting frameworks that work across any AI tool, including IDE-integrated ones.
Yes. This is designed for developers who want to take their security seriously without becoming full-time security researchers. It provides a pragmatic, engineer-first approach.
Join the course and learn to ship code that doesn't keep you up at night.
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