CVE-2024-21064 in Business Intelligence Enterprise Edition
Summary
by MITRE • 04/17/2024
Vulnerability in the Oracle Business Intelligence Enterprise Edition product of Oracle Analytics (component: Analytics Web Answers). Supported versions that are affected are 7.0.0.0.0 and 12.2.1.4.0. 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 and while the vulnerability is in Oracle Business Intelligence Enterprise Edition, attacks may significantly impact additional products (scope change). Successful attacks of this vulnerability can result in unauthorized update, insert or delete access to some of Oracle Business Intelligence Enterprise Edition accessible data as well as unauthorized read access to a subset of Oracle Business Intelligence Enterprise Edition accessible data. CVSS 3.1 Base Score 5.4 (Confidentiality and Integrity impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N).
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Analysis
by VulDB Data Team • 05/08/2025
The vulnerability identified as CVE-2024-21064 represents a significant security weakness within Oracle Business Intelligence Enterprise Edition, specifically within the Analytics Web Answers component. This flaw affects two major version streams including 7.0.0.0.0 and 12.2.1.4.0, indicating a wide-reaching impact across different deployment scenarios. The vulnerability classification as easily exploitable suggests that threat actors with minimal technical expertise can leverage this weakness, making it particularly concerning for organizations that rely heavily on business intelligence platforms for critical decision-making processes. The attack vector requires network access via HTTP, which means that any system with exposed web interfaces could potentially be targeted, creating an expansive attack surface that extends beyond the immediate application boundaries.
The technical nature of this vulnerability stems from insufficient access controls and authentication mechanisms within the Analytics Web Answers component, allowing low privileged attackers to execute unauthorized operations against the underlying business intelligence platform. The CVSS 3.1 score of 5.4 reflects a moderate severity level that combines confidentiality and integrity impacts, indicating that successful exploitation could lead to unauthorized modification of data as well as unauthorized data reading capabilities. The scope change aspect of this vulnerability is particularly concerning as it suggests that while the initial attack targets Oracle Business Intelligence Enterprise Edition, the impact may extend to other interconnected systems or applications within the broader enterprise environment. This cascading effect demonstrates how vulnerabilities in business intelligence platforms can potentially compromise entire data ecosystems, especially in organizations where such platforms integrate with multiple data sources and operational systems.
The requirement for human interaction from a person other than the attacker indicates that this vulnerability likely involves social engineering components or requires specific user actions to initiate the exploit chain. This characteristic makes the vulnerability more challenging to defend against as traditional network-based security measures may not prevent the attack from succeeding once a user performs the required interaction. The attack scenario typically involves an attacker crafting malicious web requests that exploit the authentication bypass or access control flaw, potentially leading to data manipulation or unauthorized data access. Organizations must consider that this vulnerability could be exploited through various attack vectors including phishing campaigns that trick users into interacting with malicious web content or through compromised user accounts that are then leveraged to execute the exploit.
From a security operations perspective, the impact of this vulnerability extends beyond simple data theft or modification to potentially disrupt business operations and compromise strategic decision-making processes that rely on accurate business intelligence data. The unauthorized update, insert, or delete access capabilities could corrupt analytical datasets that organizations depend upon for financial reporting, performance monitoring, or strategic planning. Additionally, the unauthorized read access to subsets of accessible data could expose sensitive business information including customer data, financial metrics, or operational details that could be valuable to competitors or malicious actors. Organizations should recognize that business intelligence platforms often contain highly sensitive and valuable data that, when compromised, can have significant financial and operational implications. The vulnerability's classification under CWE categories related to insufficient access control and authentication mechanisms aligns with common attack patterns documented in the ATT&CK framework, particularly those involving credential access and privilege escalation techniques that target enterprise applications.
Mitigation strategies for CVE-2024-21064 should include immediate implementation of the vendor-provided patches and updates to eliminate the underlying access control flaws. Organizations should also implement additional network segmentation measures to limit access to the affected Oracle Business Intelligence systems, particularly restricting HTTP access to authorized administrative networks. Security monitoring should be enhanced to detect anomalous access patterns or unusual data modification activities that could indicate exploitation attempts. User education and awareness programs should be strengthened to prevent successful social engineering attacks that might leverage this vulnerability, including training on recognizing suspicious web content and understanding the risks of interacting with untrusted web applications. The implementation of additional authentication controls and multi-factor authentication for access to business intelligence platforms should be considered as defensive measures, while regular security assessments should be conducted to identify and remediate similar access control weaknesses across the enterprise infrastructure.