CVE-2020-2716 in Banking Corporate Lending
Summary
by MITRE
Vulnerability in the Oracle Banking Corporate Lending product of Oracle Financial Services Applications (component: Core). Supported versions that are affected are 12.3.0-12.4.0 and 14.0.0-14.3.0. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Banking Corporate Lending. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Banking Corporate Lending accessible data. CVSS 3.0 Base Score 6.5 (Confidentiality impacts). CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N).
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Analysis
by VulDB Data Team • 03/22/2024
The vulnerability identified as CVE-2020-2716 represents a significant security weakness within Oracle Financial Services Applications' Banking Corporate Lending component. This flaw exists in versions ranging from 12.3.0 through 12.4.0 and 14.0.0 through 14.3.0, affecting organizations that rely on Oracle's financial services infrastructure for corporate lending operations. The vulnerability's classification as easily exploitable indicates that attackers with minimal privileges and network connectivity can potentially compromise the system, making it particularly dangerous for financial institutions that handle sensitive corporate lending data.
The technical nature of this vulnerability stems from insufficient access controls within the Core component of Oracle Banking Corporate Lending, allowing low privileged attackers to bypass authentication mechanisms through HTTP network connections. This weakness creates a pathway for unauthorized users to gain access to critical financial data without proper authorization, potentially leading to data breaches that could expose sensitive corporate lending information. The CVSS 3.0 scoring of 6.5 reflects the moderate to high severity impact, with confidentiality being the primary concern while integrity and availability remain unaffected in this specific instance. The vulnerability's attack vector requires network access via HTTP, suggesting that the flaw exists in the web application layer where HTTP requests are processed and validated.
The operational impact of CVE-2020-2716 extends beyond simple data exposure, as successful exploitation can result in complete access to all Oracle Banking Corporate Lending accessible data, potentially affecting loan portfolios, customer information, and financial records. Financial institutions using affected versions face risks of regulatory compliance violations, reputational damage, and potential financial losses due to unauthorized access to corporate lending systems. Organizations may experience disruption to their lending operations and could face increased scrutiny from regulatory bodies investigating security incidents. The vulnerability's potential for widespread impact across multiple versions of the Oracle Financial Services Applications suite means that affected enterprises must urgently assess their deployment configurations and implement appropriate security measures.
Mitigation strategies for this vulnerability should include immediate application of Oracle's security patches and updates released to address the specific access control flaw. Organizations should implement network segmentation and access controls to limit HTTP access to the affected applications, while also strengthening authentication mechanisms and monitoring network traffic for suspicious activities. The vulnerability aligns with CWE-284 (Improper Access Control) and may be categorized under ATT&CK technique T1078 (Valid Accounts) as attackers could leverage compromised access to maintain persistence within the financial services environment. Regular security assessments and vulnerability scanning should be conducted to identify similar access control weaknesses in other Oracle Financial Services Applications components, while implementing robust network monitoring solutions to detect unauthorized access attempts and potential exploitation activities targeting financial data systems.