Back to content
    CybersecurityDeveloperTechnical analysis

    CodeQL 2.26.0: What Does the System Prompt Injection Query Catch in AI Applications?

    An analysis of the js/system-prompt-injection query introduced in CodeQL 2.26.0 and the JavaScript/TypeScript data flows it detects in AI applications.

    Published: July 23, 2026Updated: July 23, 2026InoviqLab
    Detecting system prompt injection vulnerabilities in AI applications with CodeQL 2.26.0.
    Audience
    Developer
    Content type
    Technical analysis
    Source verification date
    2026-07-22
    Verified version or policy
    CodeQL 2.26.0 js/system-prompt-injection query
    This article contains time-sensitive technical information; version and policy details should be rechecked before implementation.
    CodeQLPrompt InjectionJavaScriptTypeScriptAI SecurityStatic Analysis

    Short answer

    System Prompt Injection occurs when untrusted user inputs alter or override the system instructions guiding an AI model's behavior, leading to unauthorized tool execution or sensitive data disclosure.

    Static analysis tools like **CodeQL** incorporate security rules (e.g., CodeQL 2260 query patterns) to detect un-sanitized user inputs concatenated directly into system prompt instructions.

    Defensive Pattern:

    // VULNERABLE: Direct string concatenation into system prompt
    const prompt = `System: You are an assistant. User query: ${userInput}`;
    
    // SECURE: Separating system instructions from user messages
    const messages = [
      { role: 'system', content: 'You are an assistant. Do not execute system commands.' },
      { role: 'user', content: userInput }
    ];

    Prompt Injection Checklist

    • [ ] Separate system instructions from user input in message arrays
    • [ ] Run CodeQL static analysis to detect prompt injection vectors
    • [ ] Validate and sanitize all external user inputs before LLM invocation

    Sources

    • CodeQL Documentation — Static Analysis Rules for Artificial Intelligence Systems
    • OWASP Top 10 for LLM Applications — Prompt Injection Risks

    Share