CVE-2020-4612 in Data Risk Manager
Summary
by MITRE
IBM Data Risk Manager (iDNA) 2.0.6 could allow an authenticated user to obtain sensitive information using a specially crafted HTTP request. IBM X-Force ID: 184924.
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Analysis
by VulDB Data Team • 09/23/2020
IBM Data Risk Manager version 2.0.6 contains a vulnerability that enables authenticated users to extract sensitive information through carefully constructed HTTP requests. This issue represents a classic case of information disclosure vulnerability where legitimate authenticated users can exploit the system's response handling mechanisms to access data they should not be authorized to view. The vulnerability stems from inadequate input validation and response sanitization within the web application layer, allowing maliciously crafted requests to trigger unintended data exposure. Attackers with valid credentials can manipulate HTTP request parameters to bypass normal access controls and retrieve confidential information including user data, system configurations, or other sensitive operational details that should remain protected within the application's secure boundaries.
The technical flaw manifests in the application's insufficient validation of incoming HTTP request parameters and headers, particularly affecting how the system processes and responds to user-supplied data. This weakness creates an information disclosure pathway where authenticated sessions can be leveraged to access unauthorized data through crafted request structures. The vulnerability aligns with CWE-200, which categorizes information exposure issues, and represents a specific instance of improper input validation that allows attackers to extract sensitive data beyond normal operational boundaries. When an authenticated user submits a specially crafted HTTP request, the application fails to properly validate the request structure or sanitize the response content, potentially revealing internal system information, user credentials, or other confidential data elements that should remain hidden from unauthorized access attempts.
The operational impact of this vulnerability extends beyond simple data exposure, as it can compromise the overall security posture of organizations using IBM Data Risk Manager. The authenticated nature of the exploit means that attackers must first obtain valid credentials, but once achieved, they can systematically extract sensitive information from the application's data stores. This vulnerability directly impacts the confidentiality aspect of the CIA triad and can enable further attacks such as privilege escalation, lateral movement, or data exfiltration. Organizations may face regulatory compliance violations, data breach notifications, and potential legal consequences if sensitive information is exposed through this vulnerability. The impact is particularly severe for organizations handling sensitive data such as financial records, personal identification information, or proprietary business data that requires strict access controls and audit trails.
Mitigation strategies for this vulnerability should focus on implementing comprehensive input validation and response sanitization measures within the IBM Data Risk Manager application. Organizations should immediately apply the vendor-provided security patches or updates that address this specific information disclosure issue. Network segmentation and access controls should be reviewed to limit the blast radius of potential exploitation, while implementing robust monitoring and logging mechanisms to detect anomalous HTTP request patterns. Security teams should conduct thorough penetration testing and code reviews to identify similar vulnerabilities in other application components, particularly focusing on areas where user input is processed and returned to clients. Additionally, implementing web application firewalls and request filtering mechanisms can provide additional layers of protection against crafted HTTP requests that attempt to exploit this vulnerability, while maintaining compliance with industry standards such as those outlined in the OWASP Top Ten and NIST cybersecurity frameworks.