The Vibe Coding Security and Risk Course - 2026

Explore how vibe coding democratizes software creation with AI-generated code while introducing new security risks, including prompt injections and hallucinations; learn to scrutinize AI output and apply protections.

Explore how hallucinations in Vibe Coding generate nonexistent package names and insecure code, enabling slop squatting attacks. Verify packages in trusted repositories and rely on reviewed, safe code.

Explore prompt injections and data leakage risks in AI-powered apps, including direct and indirect prompt attacks, unsanitized inputs, guardrails, and how leaked keys or passwords can occur.

Explores how vibe hacking lowers barriers to malware creation through AI-driven, low-friction development, and highlights social impacts like ethics, ownership, bias, and job disruption, while stressing securing coding workflows.

Secure vibe coding by extending traditional security with prompt level controls and AI output reviews to mitigate prompt injections and dependency risks.

Explore a six-part security framework for securing vibe coding, from prompt rules in the IDE to AI dependency verification and enhanced SAST/DAST to prevent prompt injections.

Empower developers to generate safe code by embedding security into prompts from the start, using project-level prompt rules and rule files to enforce secure, context-aware code.

Learn how prompt rules guide secure coding by auditing code, avoiding hardcoded credentials, and generating authentication with input validation, logging, and OWASP-aligned security best practices.

Demonstrates using prompt rules to generate a secure comment submission form by sanitizing input, enforcing a 400-character limit, and optionally adding a captcha to prevent cross-site scripting attacks.

Discover how the model context protocol standardizes AI access to files, databases, and tools, bridging apps with data sources via a usb-like interface; review MCP architecture and security risks.

Explore how the model context protocol extends an AI model by integrating external tools and servers, demoing sequential thinking for structured problem solving and security risk analysis.

Explore the model context protocol risks, including malicious MCP servers, rugpulls, tool poisoning, and cross tool poisoning, and learn how to perform risk assessments and apply least-privilege practices.

Assess MCP server risks by due diligence, evaluate community ratings and security ratings, then run code scans with tools like Q developer to identify vulnerabilities.

Explore spec-based development with vibe coding and Amazon Cairo, turning prompts into living specifications that guide enterprise-grade apps from requirements to tasks.

Discover the power of spec based development using vibe coding in Cairo, turning requirements into design and a task driven implementation for a refreshing cybersecurity tips page.

Explore how agent hooks automate coding workflows in your IDE, enforcing security, standards, and documentation updates through proactive AI integration.

Demonstrates creating agentic hooks in natural language. Hooks automatically review changes for security issues on save and suggest secure alternatives, then can be shared with the team.

Conclude by embracing a learning mindset, understanding architecture and data flow, applying basic security hygiene from day one, and seeking expert reviews for secure AI-enabled applications.