Category Archives: Potential Risk of CVE

CVE‑2025‑23244: About NVIDIA GPU Display Driver (24-04-2025)

Preface: The NVIDIA Tesla R570 driver is used for various data center GPUs, including the NVIDIA A100 and NVIDIA V100. These GPUs are designed for high-performance computing, AI, and deep learning applications.

Background:

The CUDA software environment consists of three parts:

  • CUDA Toolkit (libraries, runtime and tools) – User-mode SDK used to build CUDA applications
  • CUDA driver – User-mode driver component used to run CUDA applications (for example, libcuda.so on Linux systems)
  • NVIDIA GPU device driver – Kernel-mode driver component for NVIDIA GPUs

On Linux systems, the CUDA driver and kernel mode components are delivered together in the NVIDIA display driver package.

DxgkDdiEscape is a function used in Windows drivers, specifically within the DirectX graphics kernel subsystem. In Linux, a similar function to DxgkDdiEscape is ioctl (Input/Output Control).

The ioctl system call can indeed be a potential vector forIncorrect Authorization vulnerabilities if not implemented correctly.

Vulnerability details: NVIDIA GPU Display Driver for Linux contains a vulnerability which could allow an unprivileged attacker to escalate permissions. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, and data tampering.

Impact: Code execution, denial of service, escalation of privileges, information disclosure, and data tampering

Official announcement: Please see the link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5630

CVE-2025-23253: NVIDIA NvContainer service for Windows contains a vulnerability (24-4-2025)

Preface: The most common way is Attackers place a malicious DLL in a directory that is checked before the legitimate system paths.

Because the application loading the DLL is trusted, security solutions may not flag the execution as suspicious.

Cybercriminals often use several common program instructions when creating malicious DLLs. For example, dll injection, Registry Manipulation,…etc.

Evasion Techniques:

Obfuscation: Code within the DLL is often obfuscated to avoid detection by security tools.

Steganography: Hiding malicious code within seemingly benign files.

Background: The NVIDIA NvContainer service is part of the NVIDIA graphics driver package and is responsible for various tasks, including telemetry data gathering, overlay management, and high-performance GPU scheduling. It doesn’t imply that Windows OS runs on a container runtime like Docker or Kubernetes. Instead, it refers to the way NVIDIA organizes and manages its services and processes within the driver package.

The term “container” in this context is more about how NVIDIA encapsulates its services to ensure they run efficiently and independently, rather than using a full-fledged containerization technology

Vulnerability details: NVIDIA NvContainer service for Windows contains a vulnerability in its usage of OpenSSL, where an attacker could exploit a hard-coded constant issue by copying a malicious DLL in a hard-coded path. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, or data tampering.

Official announcement: Please see the official link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5644

CVE‑2025‑23249, CVE-2025-23250 & CVE-2025-23251: NVIDIA Nemo Framework contains vulnerabilities (23rd Apr 2025)

Preface: The symbol ~/. by itself is not a relative path traversal; it simply refers to the home directory of the current user. However, when combined with ./.., it can be part of a relative path traversal.

Relative path traversal involves using sequences like ../ to navigate up the directory hierarchy. For example, ~/. refers to the home directory, and ./.. moves up one directory level from the current directory. So, ~/. ./.. would navigate to the parent directory of the home directory, which can be considered a form of relative path traversal

Background: NVIDIA NeMo is an end-to-end platform designed for developing and deploying generative AI models. This includes large language models (LLMs), vision language models (VLMs), video models, and speech AI. NeMo offers tools for data curation, fine-tuning, retrieval-augmented generation (RAG), and inference, making it a comprehensive solution for creating enterprise-ready AI models. Here are some key capabilities of NeMo LLMs:

  1. Customization: NeMo allows you to fine-tune pre-trained models to suit specific enterprise needs. This includes adding domain-specific knowledge and skills, and continuously improving the model with reinforcement learning from human feedback (RLHF).
  2. Scalability: NeMo supports large-scale training and deployment across various environments, including cloud, data centers, and edge devices. This ensures high performance and flexibility for different use cases.
  3. Foundation Models: NeMo offers a range of pre-trained foundation models, such as GPT-8, GPT-43, and GPT-530, which can be used for tasks like text classification, summarization, creative writing, and chatbots.
  4. Data Curation: The platform includes tools for processing and curating large datasets, which helps improve the accuracy and relevance of the models.
  5. Integration: NeMo can be integrated with other NVIDIA AI tools and services, providing a comprehensive ecosystem for AI development.

Vulnerability details:

CVE-2025-23249: NVIDIA NeMo Framework contains a vulnerability where a user could cause a deserialization of untrusted data by remote code execution. A successful exploit of this vulnerability might lead to code execution and data tampering.

CVE-2025-23250: NVIDIA NeMo Framework contains a vulnerability where an attacker could cause an improper limitation of a pathname to a restricted directory by an arbitrary file write. A successful exploit of this vulnerability might lead to code execution and data tampering.

CVE-2025-23251: NVIDIA NeMo Framework contains a vulnerability where a user could cause an improper control of generation of code by remote code execution. A successful exploit of this vulnerability might lead to code execution and data tampering.

Official announcement: Please see the official link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5641

About AXI Protocol Checker IP (22-04-2025)

When light weight AI become your partner. In the office, all people skill become equal. As a result, the inherent kindness in human nature will be hidden!

Preface: High Performance Computing (HPC) systems using AMD chips can utilize AXI crossbars. The AXI crossbar is used to route AXI4-Lite requests to corresponding sub-cores based on the address. This is particularly useful in complex SoC designs where efficient data routing and high throughput are essential.

However, it’s worth noting that AMD’s Versal adaptive SoCs feature a programmable Network-on-Chip (NoC), which replaces traditional AXI interconnects in the programmable logic. This NoC can achieve higher levels of design efficiency and performance compared to traditional AXI interconnects.

Background:

AXI Crossbar

  • In an AXI Crossbar, the master interfaces are the sources of transactions, and the slave interfaces are the destinations.
  • The crossbar routes transactions from multiple masters to multiple slaves based on address decoding and arbitration logic.
  • It ensures efficient communication and data transfer within a System-on-Chip (SoC) design.

AXI4-Lite and the Orchestrator serve distinct roles within an AXI Crossbar:

AXI4-Lite: AXI4-Lite is a simplified subset of the AXI4 protocol designed for low-complexity, low-throughput applications. It supports:

  • 32-bit address and data widths.
  • Single data transfer per transaction, making it ideal for control register access and configuration tasks.

The Orchestrator in an AXI Crossbar manages the routing and arbitration of transactions between multiple masters and slaves.

Vulnerability details: Researchers from ETH Zurich, UC San Diego, and RPTU Kaiserslautern-Landau shared a paper with AMD titled “EXPECT: On the Security Implications of Violations in AXI Implementations” and “XRAY Detecting and Exploiting Vulnerabilities in ARM AXI Interconnects” which explore methods for exposing vulnerabilities related to the AXI interface when utilizing the AMD AXI Crossbar IP in Vivado™ designs. The AXI Protocol Checker IP was included in the design as a debug check but failed to catch all protocol violations in the design.

Official announcement: Please see the link for details – https://www.amd.com/en/resources/product-security/bulletin/amd-sb-8005.html

CVE-2025-3619: Heap buffer overflow in Codecs in Google Chrome on Windows (17-04-2025)

Preface: OpenH264 is a free software library for real-time encoding and decoding video streams in the H. 264/MPEG-4 AVC format.

Background: The Best Video Formats for Uploading to Google Drive. You can upload and preview several video types in Google Drive, such as MP4, WMV, FLV, AVI, H. 264, MPEG4, VP8, to mention a few.

Ref: OpenH264 is a free license codec library which supports H.264 encoding and decoding. A vulnerability in the decoding functions of OpenH264 codec library could allow a remote, unauthenticated attacker to trigger a heap overflow. This vulnerability is due to a race condition between a Sequence Parameter Set (SPS) memory allocation and a subsequent non Instantaneous Decoder Refresh (non-IDR) Network Abstraction Layer (NAL) unit memory usage.

Vulnerability details: Heap buffer overflow in Codecs in Google Chrome on Windows prior to 135.0.7049.95 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: Critical)

Official announcement: Please refer to the link for details – https://nvd.nist.gov/vuln/detail/CVE-2025-3619

CVE-2024-45551: Weak Authentication in HLOS (16-04-2025)

NVD Published Date: 04/07/2025

NVD Last Modified: 04/07/2025

Preface: Released on September 3, 2024 as Android 15. Android 16, Internal codename as Baklava, released on 2nd April 2025.

Background: The core of the Android OS operating system is the Android Open Source Project (AOSP), which is free open source software (FOSS) licensed primarily under the Apache License. However, most devices run a proprietary version of Android developed by Google, which comes pre-installed with additional proprietary, closed-source software, most popular Google Mobile Services (GMS), which includes core applications such as Google Chrome, the digital distribution platform Google Play, and the related Google Play Services development platform.

Qualcomm Android source code is divided into development source code and proprietary source code. Proprietary source code is further divided into proprietary non-HLOS software and proprietary HLOS software. HLOS is the High-level Operating System, and non-HLOS software refers to software below the HLOS layer.

Vulnerability details: Cryptographic issue occurs during PIN/password verification using Gatekeeper, where RPMB writes can be dropped on verification failure, potentially leading to a user throttling bypass.

Official announcement: Please see the link for details –

https://nvd.nist.gov/vuln/detail/CVE-2024-45551

CVE-2024-10929: Staying alert! Spectre-BSE exploits affects ARM® Cortex®-A72 (revisions prior to r1p0), Cortex-A73 and Cortex-A75. (15-04-2025)

Preface: The Cortex-A75 is still being used by manufacturers today. For instance, UNISOC and MediaTek continue to incorporate Cortex-A75 cores in their chipsets.

These processors are found in various mid-range and entry-level devices, providing a balance of performance and efficiency.

Background: Branch Status Eviction (BSE) is a vulnerability related to the Spectre class of security issues. It exploits a microarchitectural mechanism that allows an attacker to gain a weak form of control over the victim’s branch history, despite existing protections. This can lead to the manipulation of indirect branches and potentially result in data exfiltration.

Vulnerability details: According to the ARM® security team, Spectre-BSE exploits a micro-architectural mechanism that equips an adversary with a weak form of control over the victim’s branch history despite existing protections.

This can lead to exploitative control of indirect branches and potentially to data exfiltration. This issue affects ARM Cortex®-A72 (revisions prior to r1p0), Cortex-A73 and Cortex-A75.

Official announcement: Please see the link for details – https://www.amd.com/en/resources/product-security/bulletin/amd-sb-8007.html

About the mysterious mask of CVE-2025-22429 (14-4-2025)

Preface: The reason why an unparcel error involving Parcel and BaseBundle is considered a critical Common Vulnerabilities and Exposures (CVE) is due to the potential security risks it poses. Specifically, such errors can lead to: Data Corruption, Security Vulnerabilities and Denial of Service (DoS).

Background: BaseBundle[.]java in Android is a class that provides a mapping from String keys to values of various types. It serves as a base class for Bundle and PersistableBundle, which are more commonly used in Android development. Here are some key functions of BaseBundle:

  • Storing and retrieving data: It allows you to store various types of data (like int, boolean, String, etc.) and retrieve them using specific keys.
  • Clearing data: You can remove all elements from the mapping using the clear() method.
  • Checking for keys: The containsKey(String key) method lets you check if a particular key exists in the mapping.

In most cases, developers work directly with Bundle or PersistableBundle, which extend BaseBundle and provide additional functionalities.

Vulnerability: An unparcel error in Android, often caused by issues with Parcel and BaseBundle, can lead to several consequences.

Ref: If an attacker can manipulate the data being parceled, they might exploit the unparceling process to execute arbitrary code or gain unauthorized access to sensitive information.

Official announcement: Please refer to the link for details –https://android.googlesource.com/platform/frameworks/base/+/ece83fb425b1e912a036e9985b710910e2e3ca37

CVE-2025-21443: Memory corruption while processing message content in eAVB. (13th Apr 2025)

Preface: The Snapdragon SA8540P SoC and SA9000P AI accelerator are designed to work together seamlessly, particularly in advanced driver-assistance systems (ADAS) like GM’s Ultra Cruise. The buffer sharing design between these components is crucial for efficient data processing and low-latency performance. In automotive Ethernet Audio Video Bridging (eAVB), processors handle various types of message content to ensure efficient and reliable communication within the vehicle’s network.

Background: In Automotive Ethernet Audio Video Bridging (eAVB), processors handle the content of various types of messages to ensure efficient and reliable communication within the vehicle network.

Synchronization: eAVB ensures that audio and video streams are synchronized across different devices in the vehicle, providing a seamless infotainment experience.

Low Latency: Messages are designed to be transmitted with minimal delay, which is crucial for real-time applications like advanced driver-assistance systems (ADAS) and infotainment

Fault Tolerance: The system is built to handle faults and ensure continuous operation even in the presence of network issues

High Bandwidth: eAVB supports high-speed data transmission, which is necessary for handling large amounts of audio and video data

Vulnerability details: in Automotive Vehicle Networks. Memory corruption while processing message content in eAVB. Found that Buffer Copy Without Checking Size of Input (‘Classic Buffer Overflow’).

Official announcement: Please refer to the link for details – https://nvd.nist.gov/vuln/detail/CVE-2025-21443

CVE-2025-21425: Memory corruption may occur due to improper access control in HAB process. (10th Apr 2025)

Announcement on January 6, 2022: GM and Qualcomm showcase collaboration at CES that brings first dedicated Snapdragon system-on-chips to GM’s upcoming advanced driver assistance system for fast, robust data processing.

Preface: When the Snapdragon SA8540P SoC and SA9000P AI accelerator work together, they typically use a coordinated boot process. Each component has its own firmware, but they are designed to work seamlessly together within the system.

Background: The High Assurance Boot (HAB) process is indeed located within the embedded OS environment, specifically in the normal world. It is designed to ensure that only authenticated and trusted software images are executed on the device, providing a secure boot mechanism.

Here’s a brief overview of how HAB works:

  1. Digital Signatures: HAB uses digital signatures to authenticate the initial software image. This involves creating a unique identifier (certificate) for the image using asymmetric encryption. The private key is used to encrypt the image, while the public key is attached to it.
  2. Authentication: During boot, the boot ROM uses the public key to decrypt the certificate and verify the image. If the certificate matches the image, it is considered trusted and allowed to run. Otherwise, it is rejected.
  3. Chain of Trust: HAB establishes a chain of trust for subsequent software components, such as the kernel image, ensuring that the entire system remains secure.

Vulnerability details: Improper Access Control in Automotive Linux OS. Memory corruption may occur due top improper access control in HAB process.

Technology Area – Automotive Linux OS

Vulnerability Type – CWE-284 Improper Access Control

Official announcement: Please refer to the link for details –

https://nvd.nist.gov/vuln/detail/CVE-2025-21425