8/12/2025

A Deep Dive into Finding Security Vulnerabilities in Claude Code

Hey everyone, let's talk about something that's been on my mind a lot lately: AI & cybersecurity. Specifically, I want to dive deep into the world of Anthropic's Claude & how it fits into the picture of finding security vulnerabilities. It's a fascinating topic with a couple of different angles, & honestly, it's something anyone in the dev world should be thinking about.

Turns out, when we talk about "vulnerabilities in Claude code," we're really talking about two distinct but connected things. First, how can we use Claude as a tool to find security holes in our own code? & second, how do we make sure that the code Claude generates for us isn't riddled with vulnerabilities itself? It's a classic two-sided coin, & we're going to break it all down.

So, grab a coffee, get comfortable, & let's get into the nitty-gritty of it.

Using Claude as Your Personal Security Analyst

This is where things get REALLY interesting. Anthropic has been making some serious moves to position Claude as a powerful ally for developers who care about security. They've developed tools specifically designed to help you sniff out weaknesses in your code, & it's pretty impressive stuff.

Meet Your New Security Tools: Claude.ai & Claude Code

Anthropic offers a one-two punch for security analysis with Claude.ai & Claude Code. Think of them as two different modes of operation for the same brilliant security mind.

Claude.ai: This is the browser-based version of Claude that you can chat with. It's perfect for high-level security thinking before you even get deep into the code. You can use it to:
- Explore threat models: Got a new feature idea? You can brainstorm with Claude about potential security risks & how to mitigate them from the get-go.
- Review insecure patterns: You can paste in code snippets & ask Claude to look for anti-patterns or common mistakes.
- Understand CVEs: If a new Common Vulnerabilities & Exposures (CVE) is announced, you can ask Claude to break it down for you & help you figure out if your projects are at risk.
- Generate security checklists: Need a quick audit plan or a hardening checklist for a specific service? Claude.ai is your go-to.
Claude Code: This is where the magic really happens for developers. It's an agentic coding tool that lives right in your terminal & integrates with your development environment. This isn't just a chatbot; it's a tool that can read your entire project, understand the context, & help you find & fix problems at the source.

The
`1/security-review`
Command: A Game Changer

Recently, Anthropic rolled out a new feature for Claude Code that's a total game-changer: the

/security-review

command. With just a simple command in your terminal before you commit your code, you can get a senior security engineer's eyes on your work.

Here's how it works: you type

/security-review

, & Claude Code gets to work, scanning your codebase for a whole host of common vulnerabilities, including:

SQL injection risks
Cross-site scripting (XSS) attacks
Authentication & authorization flaws
Insecure data handling
Dependency vulnerabilities

What's so powerful about this is that it's not just a simple linter or a static analysis (SAST) tool that matches patterns. Claude Code uses its reasoning capabilities to analyze the logic of your code in context. It can trace the flow of data, see how different parts of your application interact, & identify potential weaknesses that a traditional tool might miss.

For example, it can look at your token generation logic & flag predictable tokens or check your user onboarding flow to see if user roles can be bypassed. That's a level of analysis that usually takes a lot of manual effort.

Integrating Security into Your Workflow

The best part about these tools is that they're designed to fit seamlessly into your existing workflow. You can run ad-hoc security reviews from your terminal, which helps you catch issues early when they're easiest to fix.

Even better, you can integrate Claude Code into your Continuous Integration (CI) pipeline. Imagine automatically scanning every pull request for security vulnerabilities before it ever gets merged into the main branch. Claude Code can run in CI, evaluate the context of the changes, & provide structured output. You could even set it up to automatically block merges if high-severity issues are found or post summaries of its findings as comments on the pull request.

This is how you build a culture of security on your team. It's not about adding extra overhead; it's about making security an integral part of the development process.

The Other Side of the Coin: When AI Writes Insecure Code

Okay, so we've seen how Claude can be a powerful force for good in the world of cybersecurity. But what about the code that Claude itself writes? This is where things get a little more complicated.

A recent study by Backslash Security put a bunch of popular LLMs, including Claude, to the test to see how good they are at producing secure code. The results were...mixed.

"Vibe Coding" & Its Dangers

The study found that when developers use "naïve" prompts—basically just asking the AI to generate code for a specific task without mentioning security—the results are often not great. In fact, all the LLMs tested generated insecure code in response to these simple prompts, riddled with common vulnerabilities like command injection, XSS, & path traversal.

This has led to the rise of what some are calling "vibe coding," where developers rely heavily on AI-generated code without fully understanding its security implications. It's a scenario that can feel like a nightmare for security teams, as it creates a flood of new code that might be hiding serious risks.

How Did Claude Fare?

Now, for the good news. In the Backslash Security study, Claude 3.7-Sonnet actually had the best security performance of all the LLMs tested. It produced secure code in 60% of cases even with naïve prompts. And when the prompt was tweaked to include a generic security requirement like "make sure you are writing secure code," Claude achieved a perfect 100% score.

This suggests that while you can't blindly trust the code that any AI generates, some models are definitely better than others when it comes to security. & it highlights the importance of how you prompt the AI.

The Art of the Secure Prompt

The study made one thing abundantly clear: the way you ask the AI for code matters. A LOT.

Simply asking for a feature is a recipe for disaster. But if you're specific about your security requirements, you can get much better results. For example, instead of saying:

"Write a Python script that lets users upload files to a server."

You could say:

"Write a secure Python script that lets users upload files to a server. Make sure to follow OWASP secure coding best practices, validate file types, limit file sizes, & prevent path traversal vulnerabilities."

The more specific you are, the better the AI can understand your intent & generate code that's not only functional but also secure. The study showed that even a generic prompt to "make sure to follow OWASP secure coding best practices" significantly improved the security of the generated code for all LLMs.

The Human Element is Still CRUCIAL

Here's the bottom line: AI is a tool, not a replacement for a skilled developer with a security mindset. You should NEVER blindly copy & paste code from an AI into a production application without carefully reviewing it first.

Think of AI-generated code as a first draft. It can save you a ton of time & get you 80% of the way there, but it's your job to do that final 20% of due diligence. That means:

Reviewing every line of code: Understand what it does & how it works.
Testing it thoroughly: Don't just test the "happy path." Try to break it. Think like an attacker.
Using security tools: This is where tools like Claude Code's
1/security-review
come in handy. Use the AI to check the AI's work!

Building a Secure Future with AI

So, what's the takeaway from all of this?

AI is a double-edged sword when it comes to security. It can be an incredibly powerful tool for finding vulnerabilities, but it can also be a source of them if you're not careful. The key is to be smart about how you use it.

Embrace tools like Claude.ai & Claude Code to augment your security practices. Integrate them into your workflow to catch issues early & often. They can genuinely help you build more secure applications & save you a ton of time in the process.

But at the same time, maintain a healthy skepticism of AI-generated code. Always review it, always test it, & always remember that you are ultimately responsible for the security of your applications.

And hey, if you're building a business & thinking about how to engage with your customers in a more modern, efficient way, you might want to check out Arsturn. It's a no-code platform that lets you build custom AI chatbots trained on your own data. These chatbots can provide instant customer support, answer questions, & engage with your website visitors 24/7. It's a pretty cool way to leverage the power of AI to boost conversions & provide personalized customer experiences, all while you focus on building secure & robust applications.

Hope this deep dive was helpful! The world of AI & security is moving at a breakneck pace, & it's on all of us to keep up. Let me know what you think in the comments below.