Meetanshi AI
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AI Code VulnerabilityExplainer

Plain-English explanations of the 10 most common security vulnerabilities in AI-generated code. What they are, why AI produces them, and how to fix them.

SQL Injection

CRITICAL

What It Is

SQL injection happens when user input gets directly inserted into a database query without being cleaned first. If someone types malicious code into a search box, it can read, delete, or modify your entire database.

Why AI Code Produces This

AI tools write queries by concatenating strings — the fastest way to prototype, but the most dangerous way to query a database.

What It Looks Like

// ❌ BAD — AI-generated string concatenation
const query = "SELECT * FROM users WHERE email = '" + req.body.email + "'";
db.query(query);
// ✅ GOOD — Parameterized query
const query = "SELECT * FROM users WHERE email = $1";
db.query(query, [req.body.email]);

What Happens If Exploited

An attacker can read all your users' data, emails, passwords. In the worst case: delete your entire database.

How To Fix It

Use parameterized queries or an ORM. Never concatenate user input directly into SQL strings.

Not sure if your code has these issues? Our AI Code Security Audit ($299) checks your entire codebase.

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How to Understand Security Vulnerabilities in Your AI-Generated Code

  1. 1Describe the vulnerability — paste the exact error message from your terminal, browser console, or security scanner, or describe the concerning behavior in plain English (e.g., "my API returns data for other users" or "I found my database password in the GitHub commit history"). The more specific you are, the more precise the explanation.
  2. 2Select the type of security issue — choose from common vulnerability categories: authentication bypass, SQL/NoSQL injection, secret/API key exposure, CORS misconfiguration, insecure direct object reference (IDOR), XSS (cross-site scripting), missing rate limiting, or broken access control.
  3. 3Get a plain English explanation — receive a clear explanation of what the vulnerability is, why AI coding tools (Cursor, Bolt, v0) commonly produce it (training data patterns, defaults they rely on), and what a malicious actor could actually do if they exploited it in your specific context.
  4. 4Review risk level and impact — see the severity rating (Critical/High/Medium/Low based on CVSS scoring), which types of data or users are at risk, whether the vulnerability is exploitable remotely or requires local access, and how urgently it needs to be fixed before launch.
  5. 5Copy the fix recommendation — get a specific code-level fix recommendation or secure code example you can apply directly. For example: replace raw SQL string concatenation with parameterized queries, move the API key from the source file to an environment variable, or add the missing authorization check to the route handler.