CVE-2007-2847 in hlstats
Summary
by MITRE
Multiple cross-site scripting (XSS) vulnerabilities in hlstats.php in HLstats 1.35, and possibly earlier, allow remote attackers to inject arbitrary web script or HTML via the (1) authusername or (2) authpassword parameter, different vectors than CVE-2007-0840 and CVE-2007-2812.
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Analysis
by VulDB Data Team • 09/03/2018
The vulnerability identified as CVE-2007-2847 represents a critical cross-site scripting weakness affecting HLstats 1.35 and potentially earlier versions of the HLstats web application. This flaw resides within the hlstats.php script and demonstrates the persistent challenge of input validation in web applications that process user-supplied data for authentication purposes. The vulnerability specifically targets the authusername and authpassword parameters, which are utilized during the authentication process of the HLstats monitoring system for game servers. These parameters are processed without adequate sanitization or output encoding, creating opportunities for malicious actors to inject arbitrary web scripts or HTML content that can be executed in the context of other users' browsers.
The technical nature of this vulnerability aligns with CWE-79 which describes improper neutralization of input during web page generation, commonly known as cross-site scripting. This particular implementation flaw allows attackers to exploit the authentication parameters by crafting malicious input that gets stored or reflected in the application's response. The vulnerability operates through different attack vectors compared to related issues CVE-2007-0840 and CVE-2007-2812, indicating that the security weaknesses are not isolated to a single input point but rather represent a broader class of input validation failures within the application's authentication handling mechanisms. The fact that these parameters are used for authentication purposes makes the impact particularly severe as attackers could potentially manipulate the authentication flow or execute scripts in the context of authenticated sessions.
The operational impact of this vulnerability extends beyond simple script injection, as it could enable attackers to perform session hijacking, steal user credentials, or manipulate the HLstats monitoring environment. When users interact with the vulnerable application, particularly during authentication processes, the injected scripts would execute in their browsers, potentially leading to unauthorized access to game server statistics, manipulation of monitoring data, or redirection to malicious sites. The vulnerability affects the core functionality of HLstats which is designed to provide real-time statistics and monitoring for multiplayer games, making it a prime target for attackers seeking to compromise gaming infrastructure. The reflected nature of the XSS attack means that the malicious scripts would be executed immediately upon page load, requiring minimal user interaction beyond accessing the vulnerable application.
Mitigation strategies for this vulnerability should prioritize immediate input sanitization and output encoding of all user-supplied parameters, particularly those used in authentication contexts. The implementation of proper parameter validation, including length restrictions and character filtering, would prevent malicious payloads from being processed. Additionally, the application should employ Content Security Policy headers to limit script execution and prevent unauthorized code injection. Security best practices recommend implementing a whitelist approach for all input parameters, ensuring that only expected character sets and formats are accepted. Organizations should also consider implementing web application firewalls to detect and block suspicious input patterns, though this represents a defensive measure rather than a primary fix. The vulnerability highlights the importance of following secure coding practices as outlined in the OWASP Top Ten and emphasizes the need for regular security assessments of web applications handling user authentication data, particularly in environments where monitoring and statistics applications are deployed.