CVE-2010-1709 in Auto-Img-Gallery
Summary
by MITRE
Multiple cross-site scripting (XSS) vulnerabilities in upload.cgi in G5-Scripts Auto-Img-Gallery 1.1 allow remote attackers to inject arbitrary web script or HTML via the (1) user and (2) pass parameters.
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Analysis
by VulDB Data Team • 01/30/2019
The vulnerability identified as CVE-2010-1709 represents a critical cross-site scripting flaw within the G5-Scripts Auto-Img-Gallery version 1.1 web application. This vulnerability specifically affects the upload.cgi script which serves as a core component for handling image uploads and user authentication within the gallery system. The flaw stems from inadequate input validation and sanitization mechanisms that fail to properly process user-supplied data before incorporating it into dynamic web content. The vulnerability impacts two distinct parameters within the upload.cgi script, namely the user and pass parameters, which are typically used for user authentication and access control purposes. Attackers can exploit this weakness by crafting malicious payloads that contain embedded script code within these parameters during the upload process.
The technical implementation of this vulnerability aligns with CWE-79, which specifically addresses cross-site scripting vulnerabilities where web applications fail to properly validate or sanitize user input before incorporating it into web pages served to other users. This weakness creates a persistent security risk where malicious actors can inject arbitrary HTML and JavaScript code into the application's response, potentially compromising user sessions and executing unauthorized actions. The vulnerability operates at the application layer and can be classified under the ATT&CK technique T1059.007 for Command and Scripting Interpreter, specifically focusing on JavaScript execution within web browsers. The flaw demonstrates a classic example of insufficient output encoding and input validation, where the application fails to properly escape special characters in user-supplied data before rendering it in HTML contexts.
The operational impact of this vulnerability extends beyond simple data corruption or display issues, as it enables attackers to perform session hijacking, steal sensitive user credentials, and potentially gain unauthorized administrative access to the gallery system. When users authenticate through the vulnerable upload.cgi script, the injected malicious code executes within their browser context, allowing attackers to capture session cookies, redirect users to malicious sites, or modify gallery content. The vulnerability affects the entire user base of the Auto-Img-Gallery application, making it particularly dangerous for public-facing websites that rely on user uploads and authentication. Attackers can leverage this weakness to establish persistent backdoors within the gallery system, potentially leading to complete compromise of the web server hosting the application.
Mitigation strategies for this vulnerability must address both immediate remediation and long-term security hardening measures. The primary fix involves implementing comprehensive input validation and output encoding mechanisms that sanitize all user-supplied data before processing or displaying it within the web application. Security professionals should implement proper parameter validation for both the user and pass parameters, ensuring that special characters are properly escaped or removed from input data. Organizations should also consider implementing Content Security Policy (CSP) headers to prevent execution of unauthorized scripts within the application context. Additionally, regular security audits and code reviews should be conducted to identify similar vulnerabilities in other application components, particularly focusing on areas where user input is processed and rendered. The vulnerability highlights the importance of secure coding practices and proper input sanitization as fundamental requirements for web application security, aligning with industry best practices outlined in OWASP Top Ten and NIST cybersecurity guidelines.