CVE-2020-2938 in Financial Services Loan Loss Forecasting
Summary
by MITRE
Vulnerability in the Oracle Financial Services Loan Loss Forecasting and Provisioning product of Oracle Financial Services Applications (component: User Interface). Supported versions that are affected are 8.0.6 - 8.0.8. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Financial Services Loan Loss Forecasting and Provisioning. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Financial Services Loan Loss Forecasting and Provisioning accessible data as well as unauthorized read access to a subset of Oracle Financial Services Loan Loss Forecasting and Provisioning accessible data. CVSS 3.0 Base Score 7.1 (Confidentiality and Integrity impacts). CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:H/A:N).
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Analysis
by VulDB Data Team • 05/21/2024
The vulnerability identified as CVE-2020-2938 represents a critical security flaw within Oracle Financial Services Applications' Loan Loss Forecasting and Provisioning module, specifically affecting versions 8.0.6 through 8.0.8. This weakness resides in the User Interface component of the financial services application suite, making it particularly concerning given the sensitive nature of loan loss forecasting data that organizations rely upon for financial stability and regulatory compliance. The vulnerability's classification as easily exploitable indicates that attackers with minimal privileges and network access can potentially compromise the system, highlighting the severity of the issue within financial institutions that depend on these applications for critical business operations.
The technical nature of this vulnerability stems from insufficient access controls within the user interface layer, allowing a low privileged attacker to perform unauthorized modifications and access operations against the underlying data repository. The CVSS score of 7.1 reflects the significant impact this vulnerability can have on both confidentiality and integrity aspects of the system, with the vector AV:N/AC:L/PR:L/UI:N/S:U indicating that exploitation requires only network access, low complexity, and low privilege levels. This configuration means that an attacker who gains network access to the application can potentially execute unauthorized data manipulation operations that could fundamentally alter loan loss projections and provisioning calculations, which directly impacts financial reporting accuracy and regulatory compliance.
The operational impact of this vulnerability extends beyond simple data compromise, as it enables attackers to create, delete, or modify critical financial data that organizations depend upon for risk assessment and financial planning. The ability to perform unauthorized read access to subsets of accessible data further compounds the risk, potentially exposing sensitive financial information that could be used for competitive advantage or malicious activities. This vulnerability directly affects the integrity of financial forecasting processes that banks and financial institutions use to determine appropriate provisioning levels for potential loan losses, potentially leading to significant financial consequences if attackers manipulate these critical calculations.
Organizations affected by this vulnerability should prioritize immediate remediation through Oracle's official security patches and updates, while implementing network segmentation and access controls to limit exposure. The vulnerability aligns with CWE-284 (Improper Access Control) and represents a clear violation of the principle of least privilege, as described in the ATT&CK framework under privilege escalation techniques. Additional mitigations should include monitoring for unusual access patterns, implementing network-based intrusion detection systems, and conducting thorough security assessments of the affected applications. The financial services industry should also consider implementing additional data validation and integrity checking mechanisms to detect potential tampering with loan loss forecasting data, as this vulnerability could be exploited to manipulate financial reports and potentially violate regulatory requirements under frameworks such as SOX and Basel III compliance standards.