CVE-2016-9711 in Predictive Solutions Foundation
Summary
by MITRE
IBM Predictive Solutions Foundation (IBM Cognos Analytics 11.0) reveals sensitive information in detailed error messages that could aid an attacker in further attacks against the system. IBM X-Force ID: 119619.
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Analysis
by VulDB Data Team • 02/22/2023
The vulnerability identified as CVE-2016-9711 affects IBM Predictive Solutions Foundation, specifically within IBM Cognos Analytics 11.0, where the system inadvertently exposes sensitive information through detailed error messages. This flaw represents a classic information disclosure vulnerability that undermines the security posture of the affected system by providing attackers with valuable insights into the underlying infrastructure and application architecture. The issue stems from the application's tendency to include verbose error details in its responses, which can reveal internal system paths, component names, and other operational details that should remain confidential. Such exposure creates opportunities for threat actors to craft more sophisticated attacks by leveraging the leaked information to identify potential attack vectors and system weaknesses.
The technical nature of this vulnerability aligns with CWE-209, which describes "Information Exposure Through an Error Message," and demonstrates how improper error handling can lead to security breaches. When the system encounters an error condition, it generates responses that contain not just the basic error information but also detailed technical diagnostics that can be exploited by malicious actors. This includes stack traces, internal file paths, database connection details, and other metadata that would typically be suppressed in production environments to prevent information leakage. The vulnerability is particularly concerning because it affects a business intelligence platform that likely handles sensitive corporate data, making the exposure of system internals even more dangerous.
The operational impact of this vulnerability extends beyond simple information disclosure, as it enables attackers to perform reconnaissance activities that would otherwise be difficult or impossible to conduct. Threat actors can use the leaked information to map the application architecture, identify running services, and understand the underlying technology stack. This intelligence can then be leveraged to target specific components or modules within the system, potentially leading to privilege escalation, data exfiltration, or other malicious activities. The vulnerability essentially provides an attacker with a roadmap for further exploitation, making it a critical concern for organizations that rely on predictive analytics solutions for business intelligence and decision-making processes.
Organizations should implement comprehensive error handling mechanisms that sanitize all error messages before they are returned to clients, ensuring that only generic error information is displayed to end users while detailed technical information is logged securely for administrators. The remediation approach should include configuring the application to suppress stack traces, internal paths, and component-specific details in error responses, while maintaining proper logging for security operations teams. Additionally, implementing web application firewalls and security monitoring tools can help detect and prevent exploitation attempts. This vulnerability underscores the importance of following security best practices outlined in the OWASP Top Ten and demonstrates how seemingly minor implementation flaws can create significant security risks in enterprise applications.