CVE-2022-26076 in oneAPI Deep Neural Network
Summary
by MITRE • 02/16/2023
Uncontrolled search path element in the Intel(R) oneAPI Deep Neural Network (oneDNN) before version 2022.1 may allow an authenticated user to potentially enable escalation of privilege via local access.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 02/17/2023
The vulnerability identified as CVE-2022-26076 resides within Intel's oneAPI Deep Neural Network library, commonly known as oneDNN, which serves as a critical component for deep learning inference and training workloads across various computing platforms. This issue represents a classic path traversal or search path manipulation vulnerability that manifests when the library fails to properly validate or sanitize dynamic library loading paths during runtime operations. The flaw specifically affects versions prior to 2022.1 and operates under the assumption that an authenticated user possesses local access to the system, creating a potential attack surface that could be exploited to elevate privileges.
The technical implementation of this vulnerability stems from improper handling of library search paths during dynamic linking operations within the oneDNN runtime environment. When the library attempts to load dependent shared objects or dynamic libraries, it may inadvertently incorporate user-controlled or untrusted paths into its search sequence without adequate validation mechanisms. This behavior aligns with CWE-427 Uncontrolled Search Path Element, a well-documented weakness where applications fail to properly control the search paths used to locate libraries or executables. The vulnerability is particularly concerning because it operates at the system level where library loading occurs, potentially allowing an attacker to inject malicious code through crafted library dependencies that get loaded in place of legitimate components.
From an operational perspective, the impact of this vulnerability extends beyond simple privilege escalation to encompass broader system compromise potential. An authenticated local user who can manipulate the library loading environment could potentially replace legitimate shared libraries with malicious counterparts, thereby executing arbitrary code with elevated privileges. This attack vector represents a significant concern for environments where oneDNN is deployed with elevated permissions or where the library is used in security-critical applications. The vulnerability's exploitation requires local access and authentication, which reduces its exposure compared to remote attack vectors, but it remains a serious concern for privileged user accounts or systems where local privilege escalation could provide access to sensitive data or system resources.
The security implications of CVE-2022-26076 align with several tactics and techniques documented in the MITRE ATT&CK framework, particularly those related to privilege escalation and defense evasion. The vulnerability enables techniques such as T1068 Local Privilege Escalation and T1574 Hijacking Execution Flow, where attackers manipulate the execution environment to redirect library loading to malicious components. Organizations utilizing oneDNN in production environments should consider this vulnerability as part of their broader security posture assessment, particularly in scenarios involving containerized deployments or systems where the library executes with elevated privileges. The remediation approach centers on updating to oneDNN version 2022.1 or later, which incorporates proper path validation mechanisms and mitigates the uncontrolled search path element issue.
Mitigation strategies for this vulnerability should encompass both immediate remediation and long-term security hardening measures. The primary and most effective mitigation involves upgrading to oneDNN version 2022.1 or subsequent releases that address the search path validation flaw. Additionally, system administrators should implement proper access controls and privilege separation to limit the impact of potential exploitation. The principle of least privilege should be enforced where oneDNN processes operate with minimal required permissions, reducing the potential damage from successful exploitation attempts. Regular security assessments and vulnerability scanning should include verification of oneDNN installations to ensure proper patching status and prevent unauthorized library modifications that could facilitate exploitation of this vulnerability.