Secure Coding & Reviewing AI-Written Code
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About this course
Secure Coding & Reviewing AI-Written Code teaches you to find and fix security bugs in Python code, whether a person or an AI assistant wrote it. The first lesson reviews a short AI-generated Flask login endpoint, finds the SQL injection in it and applies the parameterised-query fix. From there the course covers input validation and output encoding, SQL, command and template injection, XSS, CSRF and SSRF, broken access control and IDOR, sessions and JWTs, password hashing and secrets management, path traversal, unsafe uploads and deserialization, dependency and supply-chain risk including hallucinated packages, Bandit, Semgrep and pip-audit, secure error handling and logging, threat modelling with STRIDE, a review checklist for AI-written code, and the security of code that calls LLMs. The course has 185 lessons and about 1233 minutes of content. Each lesson is a short narrated reading card followed by MCQ practice with an explanation for every answer.
How the lessons work
Every lesson is built around a few lines of Python a reviewer might see in a pull request: a query built with an f-string, a file path joined from user input, a pickle.loads on request data, or a tool call an LLM can trigger. The bug is explained against that code and then fixed. MCQ practice then shows similar snippets and asks whether they are safe, which input breaks them, or which change fixes them, with an explanation for every answer. All examples use Python with Flask, FastAPI and SQLAlchemy, so you learn the bugs as they appear in that stack.
Who this course is for
Python developers, students and freshers who write or review backend code, and anyone who now accepts suggestions from an AI coding assistant. It suits engineers asked to do code review for the first time, QA engineers moving toward security testing, and developers preparing for roles that list secure coding or application security. If you want a broad view of security beyond code, including networks, incident response and compliance, Cybersecurity Interview Mastery covers that ground; this course goes deep on the code itself.
MCQ practice vs video courses
Security video courses often show an exploit being run against a deliberately broken demo app. In real code review the bug is rarely labelled: it is a missing ownership check in an otherwise tidy endpoint, a subprocess call with shell=True, or a package an assistant suggested that does not exist. This course gives you short, realistic snippets and asks you to decide, then explains the answer. That trains the habit of reading code for what an attacker controls.
Best way to learn secure coding
Keep a small Flask or FastAPI project open and, after each lesson, look for the same bug in your own code before moving on. Run Bandit and pip-audit on it when you reach the scanning topic. Answer each MCQ before reading its explanation, and pay extra attention to the snippets you marked safe that were not. By the AI code review topic, try reviewing one AI-generated change with the checklist from the course.