CVE-2026-70945 in Payroll
Summary
by MITRE • 08/19/2026
Vulnerability in the Oracle Payroll product of Oracle E-Business Suite (component: Internal Operations). Supported versions that are affected are 12.2.3-12.2.15. Easily exploitable vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Payroll. While the vulnerability is in Oracle Payroll, attacks may significantly impact additional products (scope change). Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Payroll accessible data. CVSS 3.1 Base Score 7.7 (Confidentiality impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N).
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Analysis
by VulDB Data Team • 08/19/2026
The identified vulnerability resides within the Internal Operations component of Oracle Payroll, a critical module within the broader Oracle E-Business Suite ecosystem. This flaw affects supported software versions ranging from 12.2.3 through 12.2.15. The nature of this defect allows for exploitation by an attacker who possesses only low-level privileges and has network access via HTTP to the affected system. Unlike many vulnerabilities that are isolated to their specific module, this issue presents a significant scope change risk. While the technical flaw is located in Oracle Payroll, successful exploitation can lead to cascading effects that compromise additional products within the suite, thereby expanding the blast radius of an attack beyond the initial target area.
From a technical perspective, the vulnerability enables unauthorized access to sensitive information due to insufficient security controls or improper validation mechanisms during data processing operations. The attacker does not need user interaction to exploit this flaw, as indicated by the absence of UI requirements in the CVSS vector. Instead, the exploitation relies on network-based interactions over HTTP, which may involve crafted requests that bypass existing authentication checks or manipulate internal state variables within the payroll application logic. This lack of proper access control allows a low-privileged user to escalate their effective privileges regarding data visibility, effectively gaining read access to information they should not be able to view under normal operational circumstances.
The operational impact of this vulnerability is severe, primarily driven by high confidentiality impacts as reflected in the CVSS 3.1 base score of 7.7. Successful exploitation results in unauthorized access to critical payroll data, which typically includes highly sensitive personal identifiable information such as social security numbers, bank account details, salary histories, and tax withholding records for employees. In worst-case scenarios, an attacker could achieve complete access to all Oracle Payroll accessible data. This level of exposure poses significant risks including identity theft, financial fraud, regulatory non-compliance with standards like GDPR or HIPAA depending on the jurisdiction, and potential reputational damage to the organization hosting the E-Business Suite instance. The scope change aspect further amplifies this risk by potentially exposing other interconnected business processes that rely on payroll data integrity and confidentiality.
To mitigate these risks, organizations running affected versions of Oracle E-Business Suite must prioritize applying the latest security patches provided by Oracle for the Internal Operations component. Immediate remediation is essential to close the access control gaps that allow low-privileged users to extract sensitive data. In addition to patching, administrators should review and harden HTTP configurations to ensure that only necessary endpoints are exposed and that proper authentication mechanisms are enforced at the network level where possible. Implementing strict role-based access controls within the application itself can also help limit the potential impact if a vulnerability is exploited in the future. Continuous monitoring of system logs for anomalous data retrieval patterns related to payroll modules should be established to detect any attempted exploitation activities early.