CVE-2014-0894 in Algorithmics
Summary
by MITRE
RICOS in IBM Algo Credit Limits (aka ACLM) 4.5.0 through 4.7.0 before 4.7.0.03 FP5 in IBM Algorithmics allows context-dependent attackers to discover database credentials by reading the DbUser and DbPass fields in an XML document.
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Analysis
by VulDB Data Team • 09/22/2024
The vulnerability identified as CVE-2014-0894 affects IBM Algo Credit Limits (also known as ACLM) versions 4.5.0 through 4.7.0 before 4.7.0.03 FP5. This issue resides within the RICOS component of the IBM Algorithmics suite, which is designed for credit limit management and algorithmic trading applications. The flaw represents a significant security weakness that directly impacts the confidentiality of database authentication credentials, creating potential pathways for unauthorized access to critical financial data systems.
The technical implementation of this vulnerability stems from improper handling of database credential storage within XML configuration files. Attackers can exploit this weakness by accessing specific XML documents that contain DbUser and DbPass fields, which are stored in plain text format rather than being properly encrypted or obfuscated. This configuration error violates fundamental security principles and creates an information disclosure vulnerability that allows context-dependent attackers to extract authentication credentials without requiring elevated privileges or complex exploitation techniques.
The operational impact of this vulnerability extends beyond simple credential theft, as it enables attackers to gain unauthorized access to underlying database systems that may contain sensitive financial information, customer data, and trading algorithms. This exposure creates risks for financial institutions that rely on these systems for credit limit calculations and risk management. The vulnerability affects organizations using IBM Algorithmics solutions for credit risk management, potentially exposing them to data breaches, financial loss, and regulatory compliance violations. The impact is particularly severe given that these systems typically handle highly sensitive financial data that requires strict access controls and audit trails.
Organizations should implement immediate mitigations including encrypting database credential fields within XML configuration files, implementing proper access controls for configuration files, and conducting regular security assessments of system components. The vulnerability aligns with CWE-312 (Sensitive Data Exposure) and represents a clear violation of the principle of least privilege. From an att&ck framework perspective, this vulnerability maps to technique T1552.001 (Unsecured Credentials) and could enable subsequent attacks such as credential dumping, lateral movement, and data exfiltration. System administrators should also consider implementing file integrity monitoring solutions to detect unauthorized modifications to configuration files and establish proper logging mechanisms to track access to sensitive credential information. The vulnerability highlights the importance of secure configuration management practices and proper encryption of sensitive data at rest, particularly in financial services environments where regulatory compliance requirements mandate strict data protection measures.