Many people assume that if the AI-generated code they produce with prompts looks and works fine, there are no issues. However, that assumption is one of the biggest risks in vibe coding. AI tools are good at creating functional code, but that doesn’t always mean it’s secure.
That’s the reason SecureFlag has released Secure Vibe Coding, a new beginner-level Security Awareness learning path. It’s designed to help anyone using LLMs to develop applications understand the security risks involved.
A Quick Refresher
If you’re new to the term, vibe coding refers to using AI assistants to generate code from natural-language descriptions. Instead of manually writing every line, you describe the functionality you need, and the AI writes the code for you.
It’s popular because it’s fast and accessible, even for non-developers. The problem is that AI can introduce vulnerabilities and may not fully understand your security and compliance requirements.
Why a Security Awareness Path for Vibe Coding?
Conversations about AI-assisted development tend to focus on its productivity benefits. It’s true that features can be built quickly and prototypes can be generated in minutes. However, what often gets overlooked is what happens behind the scenes when AI is doing the coding.
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AI can generate vulnerable patterns at scale: All it takes is one small flaw in a prompt or model output to quickly spread across an entire project, creating risks you might not even notice.
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Coding agents can act autonomously: They might update multiple files, call APIs, or initiate workflows without you realizing the security implications.
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Prompts can expose sensitive information: Instructions or data that’s given to the AI could end up in logs, outputs, or shared repositories.
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Third-party dependencies can be added undetected: The AI could introduce libraries or packages without knowing the potential risks, leaving you with hidden vulnerabilities.
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Security reviews aren’t necessary because AI wrote it: The code works, so we think it’s safe, but functionality doesn’t equal security.
What Participants Learn
The learning path on Secure Vibe Coding is intentionally accessible to anyone who uses AI to produce code, even non-technical users.
It is designed to take you on a progressive journey from foundational awareness to practical risk reduction. Here’s an overview of what it covers:
1. The Dangers of Vibe Coding
The path begins by establishing context. What makes vibe coding different from traditional development? It looks at how the speed and accessibility of AI code generation create new security challenges.
2. Vibing Vulnerabilities
In this section, participants explore how AI introduces specific types of vulnerabilities. They learn why vulnerabilities can be surprisingly subtle, even when the code looks clean and polished.
3. OWASP and the Top 10
Security guidance still applies, even when AI writes the code. This section connects vibe coding risks to the OWASP Top 10, an established industry framework of proven security principles.
4. Agents in Your Machine
Learn all about AI agents and how they work. See how these agents differ from traditional tools and why handing off work to AI can expand the potential for risk if not managed carefully.
5. The Agentic Attack Surface
Agents can, for example, access data, call APIs, modify repositories, or initiate workflows, which increases the attack surface. This section explains what the expanded surface looks like in practice and why it’s important for security.
6. Hardening Your Vibe Coding
The path concludes with practical defenses, and participants learn strategies for reviewing AI-generated code with a security mindset.
7. Trivia Assessment
An interactive assessment reinforces key concepts and helps participants leave with clear takeaways, ensuring they understand how to apply what they’ve learned in real-world scenarios.
Optional Labs
There are also optional hands-on labs that let you experiment with AI-generated code and test defenses in a safe, guided environment.
The good news for developers and other technically minded users is that we’re also working on a new line of labs specifically for vibe coding in real-world scenarios. These labs will give participants even more opportunities to gain practical experience, so stay tuned for updates!
Why Organizations Should Take Note
Something to consider is that AI-assisted development is no longer only applicable to engineering teams. For example, product teams can use AI to quickly prototype features or generate example workflows, and marketing teams can work with AI to create scripts, automation, or even small apps for campaigns.
Non-technical staff can now generate code or scripts that interact with the company’s systems, and as a result, more people are creating executable code. Security ownership is spreading outside traditional engineering teams, which means the guardrails organizations usually have may not cover these AI-driven workflows.
Building Secure Practices in an AI-Assisted World
Vibe coding isn’t going anywhere any time soon, and, if anything, it’s becoming more popular. The question is no longer if teams should use AI to write code, but whether they understand the security implications of doing so.
The learning path on Secure Vibe Coding helps build that understanding in a clear, straightforward way, without requiring technical expertise.
For those teams ready to move past awareness and get hands-on, SecureFlag’s labs provide the experience needed to enhance skills in secure best practices, with more advanced vibe coding labs coming soon.
