CVE-2023-21952 in Business Intelligence Enterprise Edition
Summary
by MITRE • 04/18/2023
Vulnerability in the Oracle Business Intelligence Enterprise Edition product of Oracle Analytics (component: Analytics Server). The supported version that is affected is 6.4.0.0.0. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Business Intelligence Enterprise Edition. Successful attacks require human interaction from a person other than the attacker. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Business Intelligence Enterprise Edition accessible data. CVSS 3.1 Base Score 5.7 (Confidentiality impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:N/A:N).
VulDB is the best source for vulnerability data and more expert information about this specific topic.
Analysis
by VulDB Data Team • 05/11/2023
The vulnerability identified as CVE-2023-21952 affects Oracle Business Intelligence Enterprise Edition version 6.4.0.0.0 within the Analytics Server component, representing a significant security weakness that could enable unauthorized access to sensitive business intelligence data. This vulnerability operates under the Common Weakness Enumeration category CWE-284, which addresses improper access control mechanisms, specifically targeting the authentication and authorization controls within the analytics platform. The affected system presents a medium severity risk with a CVSS base score of 5.7, indicating that while the vulnerability is not trivially exploitable, it poses a substantial threat to data confidentiality and system integrity.
The technical flaw manifests as an insufficient access control mechanism that allows low-privileged attackers to potentially compromise the Oracle Business Intelligence Enterprise Edition through HTTP network connections. This vulnerability requires human interaction from an unwitting user, suggesting that the attack vector likely involves social engineering or phishing techniques that trick legitimate users into performing actions that facilitate exploitation. The attack scenario typically involves an attacker who cannot directly access the system but can influence user behavior to execute malicious actions that lead to unauthorized access. The CVSS vector indicates network accessibility with low attack complexity and requires only low privileges, making it particularly dangerous in environments where user interaction is common.
The operational impact of this vulnerability extends beyond simple data theft, as successful exploitation can result in unauthorized access to critical business intelligence data or complete access to all data accessible through the Oracle Business Intelligence Enterprise Edition system. This comprehensive access capability means that attackers could potentially view sensitive financial reports, strategic business plans, customer data, and other confidential information that organizations rely on for competitive advantage and regulatory compliance. The confidentiality impact is rated as high, indicating that the vulnerability could lead to significant data breaches that compromise business operations and potentially violate data protection regulations such as gdpr or hipaa.
Organizations should implement multiple layers of defense to mitigate this vulnerability, beginning with immediate patching of affected systems to address the identified access control flaw. Network segmentation and monitoring should be enhanced to detect unusual HTTP traffic patterns that might indicate exploitation attempts. Additionally, user awareness training programs should be strengthened to reduce the risk of social engineering attacks that could facilitate exploitation. The mitigation strategy should also include implementing robust access controls, regularly reviewing user permissions, and establishing comprehensive audit trails to monitor access to critical business intelligence systems. Security teams should conduct regular vulnerability assessments and penetration testing to identify similar weaknesses in the broader Oracle Analytics ecosystem and ensure that all components are properly secured against both direct exploitation attempts and indirect attack vectors that could leverage this vulnerability.