CVE-2018-1369 in Security Guardium Big Data Intelligence
Summary
by MITRE
IBM Security Guardium Big Data Intelligence (SonarG) 3.1 stores sensitive information in URL parameters. This may lead to information disclosure if unauthorized parties have access to the URLs via server logs, referrer header or browser history. IBM X-Force ID: 137767.
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Analysis
by VulDB Data Team • 03/17/2023
The vulnerability identified as CVE-2018-1369 affects IBM Security Guardium Big Data Intelligence SonarG version 3.1, representing a critical information disclosure weakness that stems from improper handling of sensitive data within web application interfaces. This flaw manifests when the system incorporates confidential information directly into URL parameters during web requests, creating a persistent exposure vector that extends beyond the immediate application boundaries. The vulnerability resides in the application's design philosophy where security-sensitive data elements are not adequately abstracted from the client-side communication channels, thereby violating fundamental security principles of least privilege and secure data handling.
The technical implementation of this vulnerability demonstrates a clear violation of CWE-540, which addresses the inclusion of sensitive information in exception messages and web parameters. When sensitive data such as authentication tokens, user credentials, or system identifiers are embedded within URL structures, they become susceptible to interception and exploitation through multiple attack vectors. The flaw specifically exploits the inherent characteristics of web protocols where URLs are logged in server-side access logs, transmitted through HTTP referrer headers, and stored in browser history mechanisms, creating multiple persistent storage points for the exposed sensitive information. This design oversight allows attackers to gain unauthorized access to confidential data simply by intercepting or retrieving these URL parameters from various logging mechanisms.
The operational impact of this vulnerability extends far beyond the immediate scope of data exposure, creating cascading security implications that can compromise entire organizational infrastructures. When unauthorized parties gain access to URLs containing sensitive information through server logs, they can potentially reconstruct complete authentication sessions, access privileged system functions, or extract confidential operational data that could facilitate further attacks. The vulnerability's exploitation requires minimal technical skill and can be automated through simple log analysis or browser history examination, making it particularly dangerous in environments where multiple users interact with the application or where logging mechanisms are not properly secured. This exposure creates a persistent threat vector that remains active as long as the URLs containing the sensitive data remain accessible through the various storage mechanisms mentioned.
The security implications of this vulnerability align with ATT&CK technique T1071.004, which addresses application layer protocol usage for data exfiltration, and T1567.002, concerning the exploitation of remote services for credential access. Organizations utilizing IBM Security Guardium Big Data Intelligence SonarG 3.1 face significant risks including unauthorized access to privileged accounts, potential data breaches, and compromise of sensitive operational intelligence that the system is specifically designed to protect. The vulnerability creates a scenario where the security controls intended to protect sensitive data become ineffective due to the application's own design flaws in parameter handling and information exposure.
Mitigation strategies for CVE-2018-1369 require immediate implementation of proper parameter handling mechanisms and comprehensive security architecture reviews. Organizations should implement URL parameter validation and sanitization processes to prevent sensitive data from being embedded in web requests, while also ensuring that server logging mechanisms are configured to exclude sensitive information from log entries. The recommended approach involves adopting secure coding practices that align with OWASP Top Ten security guidelines, specifically focusing on proper input validation and output encoding techniques. Additionally, organizations should implement network monitoring solutions to detect and alert on suspicious URL patterns containing sensitive data elements, while also conducting regular security audits to identify and remediate similar vulnerabilities across their entire application portfolio. The implementation of proper session management and token-based authentication mechanisms can further reduce the attack surface and limit the potential impact of this vulnerability.