CVE-2026-4849
CVE-2026-4849: Cross-Site Scripting in Simple Laundry System
Executive Summary
CVE-2026-4849 is a medium severity vulnerability affecting software systems. It is classified as Cross-Site Scripting (XSS). Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"Precogs AI detected this vulnerability pattern in Cross-Site Scripting (XSS) implementations. The pattern deviates from documented secure coding standards, suggesting a high likelihood of exploitation if unpatched."
Summary
A medium-severity Cross-Site Scripting vulnerability (CVE-2026-4849) has been identified in code-projects Simple Laundry System 1.0. User-submitted form data is reflected into HTML pages without proper output encoding (CWE-79).
Technical Details
The issue is classified under CWE-79 (Improper Neutralization of Input During Web Page Generation). The PHP application uses raw echo or print statements to render user-submitted form data directly into HTML templates without applying htmlspecialchars() or equivalent encoding functions.
This creates multiple reflected XSS vectors across form input fields throughout the application.
Exploitation Context
- Vector: Remote / Network-based
- Authentication: Not required
- Complexity: Low
- Impact: Medium (Confidentiality and Integrity)
Combined with the SQL Injection in CVE-2026-4850, this application demonstrates multiple OWASP Top 10 violations, indicating systemic security issues in the codebase.
Remediation
Developers should immediately:
- Apply
htmlspecialchars($input, ENT_QUOTES, 'UTF-8')to every instance where user input is rendered into HTML output. - Implement a templating engine (such as Twig or Blade) that auto-encodes output by default, preventing raw HTML injection.
- Add Content Security Policy headers to all responses to restrict inline script execution.
Precogs AI Integration
The Precogs AI Code Security Platform detects XSS by tracing form input data from submission handlers through to PHP echo and template rendering sinks, verifying that context-appropriate output encoding is applied at each injection point.