Source: psirt@nvidia.com
NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer (nvidia.ko), where an integer overflow may lead to information disclosure or data tampering.
NVIDIA GPU Display Driver vulnerabilities, like CVE-2022-42265, can allow attackers to gain unauthorized access to sensitive system information or modify data. This is due to an integer overflow within the kernel mode layer, potentially leading to privilege escalation and complete system compromise. Successful exploitation could result in data breaches, system instability, and the ability to execute arbitrary code.
Step 1: Trigger Condition: The attacker crafts a malicious input, likely a specially crafted command or data structure, that is passed to the NVIDIA GPU driver through a user-space application. This input is designed to trigger the vulnerable code path within the driver.
Step 2: Integer Overflow: The malicious input causes an integer overflow during a calculation within the kernel mode layer (nvidia.ko). This overflow results in an incorrect size or offset value.
Step 3: Memory Corruption: The incorrect size or offset value is used in subsequent memory operations (e.g., memory allocation, copy, or access). This leads to out-of-bounds reads or writes.
Step 4: Information Disclosure/Data Tampering: Depending on the specific memory locations accessed, the attacker can either read sensitive kernel memory (information disclosure) or overwrite critical data structures (data tampering). This could include kernel code, security credentials, or other sensitive information.
Step 5: Privilege Escalation (Potential): If the attacker successfully overwrites kernel data, they may be able to gain elevated privileges, potentially leading to full system compromise.
The vulnerability resides within the NVIDIA GPU Display Driver (nvidia.ko) for Linux. The root cause is an integer overflow within a kernel function responsible for handling memory allocations or calculations related to display operations. Specifically, a calculation involving a size or offset value likely overflows, leading to a smaller-than-expected value being used. This can then be leveraged to read or write to memory locations outside the intended bounds, potentially allowing an attacker to overwrite critical kernel data structures, bypass security checks, or leak sensitive information. The specific function and the exact parameters involved are not fully detailed in the CVE description, but the impact is clear: information disclosure and data tampering.
The vulnerability could be exploited by various threat actors, including those seeking to establish persistence, steal data, or disrupt operations. There is no specific APT attribution available from the provided information. The vulnerability is not listed on the CISA KEV at the time of this report, but this should be continuously monitored.
Monitor system logs for unusual activity related to the NVIDIA GPU driver (nvidia.ko). Look for errors, crashes, or unexpected behavior.
Analyze network traffic for suspicious communication patterns that might indicate data exfiltration or command and control activity.
Implement host-based intrusion detection systems (HIDS) to monitor file integrity and detect unauthorized modifications to the NVIDIA driver files.
Monitor for unusual process behavior related to GPU usage, especially processes that are not typically GPU-intensive.
Employ kernel-level debugging tools to analyze driver behavior and identify potential memory corruption issues.
Update the NVIDIA GPU driver to a patched version that addresses CVE-2022-42265. This is the primary and most effective remediation step.
Implement a robust patch management process to ensure that all systems are promptly updated with the latest security patches.
Restrict access to the NVIDIA GPU driver and related system resources to authorized users only.
Employ kernel hardening techniques, such as address space layout randomization (ASLR) and kernel address space protection (KASLR), to make exploitation more difficult.
Regularly audit system configurations and security settings to identify and address any potential vulnerabilities.
Consider using a host-based intrusion detection system (HIDS) to monitor for suspicious activity related to the NVIDIA GPU driver.