CVE-2023-28512 in Watson CP4D Data Stores
Summary
by MITRE • 03/03/2024
IBM Watson CP4D Data Stores 4.6.0, 4.6.1, and 4.6.2 could allow an attacker with specific knowledge about the system to manipulate data due to improper input validation. IBM X-Force ID: 250396.
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Analysis
by VulDB Data Team • 03/03/2024
The vulnerability identified as CVE-2023-28512 affects IBM Watson CP4D Data Stores versions 4.6.0, 4.6.1, and 4.6.2, representing a critical weakness in input validation mechanisms that could enable targeted attackers to manipulate system data. This issue stems from inadequate sanitization and validation of user inputs within the data storage components of the platform, creating potential pathways for data corruption and unauthorized modifications. The vulnerability is particularly concerning as it requires only specific knowledge about the system's internal workings rather than extensive reconnaissance, making it accessible to determined attackers who understand the platform's architecture. The affected IBM Watson CP4D Data Stores implementation processes user-supplied data without sufficient validation checks, allowing malicious inputs to bypass normal security controls and potentially alter or corrupt stored information.
The technical flaw manifests through improper input validation that fails to adequately filter or sanitize data before processing within the database storage layers. This weakness creates opportunities for attackers to inject malformed or malicious data that can manipulate the underlying data structures, potentially leading to data integrity violations, unauthorized access to sensitive information, or complete data corruption within the system. The vulnerability falls under CWE-20, which specifically addresses improper input validation, a fundamental security principle that when compromised can lead to various downstream security issues including data manipulation, privilege escalation, and information disclosure. Attackers exploiting this vulnerability could leverage the system's trust in validated inputs to perform unauthorized data modifications, potentially altering critical business data or compromising the integrity of the entire data store ecosystem.
The operational impact of this vulnerability extends beyond simple data manipulation to encompass potential business continuity risks and regulatory compliance violations. Organizations utilizing these IBM Watson CP4D versions may face unauthorized data alterations that could compromise decision-making processes, financial reporting accuracy, or customer data integrity. The vulnerability's exploitation could lead to significant operational disruptions, requiring extensive forensic analysis and system restoration procedures. From an attack perspective, this issue aligns with ATT&CK technique T1566.001 which involves social engineering through spearphishing, as attackers with specific system knowledge could craft targeted attacks that exploit this validation weakness. The impact is particularly severe in enterprise environments where Watson CP4D Data Stores serve as critical components for data analytics, machine learning model training, and business intelligence operations, making any data integrity compromise potentially catastrophic for organizational operations.
Organizations should immediately implement mitigations including applying the latest IBM security patches and updates for Watson CP4D Data Stores versions 4.6.0 through 4.6.2, implementing additional input validation layers at network boundaries, and conducting comprehensive security assessments of data handling processes. System administrators should also establish monitoring protocols to detect anomalous data modification patterns that could indicate exploitation attempts, while implementing network segmentation to limit potential attack vectors. The vulnerability demonstrates the critical importance of robust input validation as a foundational security control, emphasizing that even seemingly minor validation gaps can create significant security risks in complex enterprise systems. Organizations should also review their incident response procedures to ensure readiness for potential data manipulation events and consider implementing data integrity verification mechanisms to detect unauthorized modifications. Regular security awareness training for system administrators and developers can help prevent similar issues by emphasizing proper input validation practices and secure coding standards throughout the software development lifecycle.