Category Archives: Potential Risk of CVE

CVE-2026-24157 and CVE-2026-24159: To protect your system, NVIDIA recommends updating to NeMo Framework version 2.6.2 or later (30-03-2026)

Preface: NVIDIA NeMo is a widely adopted, end-to-end framework for building, customizing, and deploying generative AI models (LLMs) and conversational AI agents. It is primarily used to tailor open-source models—such as Llama, Mistral, and Google Gemma—using proprietary enterprise data.

Ollama, Mistral, and Google Gemma represent a powerful ecosystem for running local, open-weight Large Language Models (LLMs). Ollama acts as the engine to run models, while Mistral and Gemma are two of the most popular, high-performing model families designed to be efficient enough to run on personal computers.

Background: Regarding the restore_from() method, it is a core functionality used to load local checkpoint files with the .nemo extension.

Key Details of restore_from() –

  • Purpose: Fully restores a model instance, including its weights and configuration, from a local [.]nemo file for evaluation, inference, or fine-tuning.
  • File Structure: A [.]nemo file is an archive (specifically a tar.gz file) containing the model’s weights and a model_config[.]yaml file that defines its architecture.
  • Usage: It is called directly from the model’s base class (e.g., ASRModel[.]restore_from(restore_path="path/to/file[.]nemo")).

Vulnerability details: (see below)

CVE-2026-24157 NVIDIA NeMo Framework contains a vulnerability in checkpoint loading where an attacker could cause remote code execution. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure and data tampering.

CVE-2026-24159 NVIDIA NeMo Framework contains a vulnerability where an attacker may cause remote code execution. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure and data tampering.

Official announcement: Please refer to the link for details –

https://nvidia.custhelp.com/app/answers/detail/a_id/5800

CVE-2026-24141: NVIDIA Model Optimizer for Windows and Linux contains a vulnerability in the ONNX quantization feature. (27th Mar 2026)

Preface: A design limitation has been discovered in the ONNX quantization function of the NVIDIA model optimizer for Windows and Linux. However, confusingly, the ONXY function appears to only work on Windows/RTX (not Linux). What is the actual design limitation?

A sophisticated technical question. The confusion often stems from the fact that while ONNX is the primary deployment format for Windows/RTX, the quantization process (where the vulnerability often lies) frequently occurs on Linux development servers.

Background: Why does the vulnerability affect both Linux and Windows?

Although ONNX is the target format for Windows AI PC applications, the NVIDIA Model Optimizer (ModelOpt) library is cross-platform.

*Linux as the “Factory”: Most developers use powerful Linux servers (with A100/H100 GPUs) to run the ModelOpt quantization scripts. They generate the optimized ONNX model on Linux and then “ship” it to Windows clients. Therefore, the vulnerability exists in the Linux-based conversion tools.

Vulnerability details: NVIDIA Model Optimizer for Windows and Linux contains a vulnerability in the ONNX quantization feature, where a user could cause unsafe deserialization by providing a specially crafted input file. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, data tampering, and information disclosure. (Initial release – March 24, 2026)

Official announcement: Please refer to the link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5798

Remedy CVE-2025-33244, securely deserialize data for use with APEX or PyTorch. (26th Mar 2026)

Preface: The core design goal of NVIDIA Apex is to achieve mixed precision training, which mainly involves a combination of **16-bit (FP16)** and **32-bit (FP32)**.

Background: In NVIDIA APEX, handling FP16 and FP32 data is primarily managed through the Automatic Mixed Precision (AMP) module. You don’t need to manually cast your data.

  • Use FP32 if you are doing scientific simulations that require extreme precision or if your model fails to converge using lower bit-depths.
  • Use FP16 for Inference (running a finished model on a phone or server) or when training Large Language Models (LLMs) to save massive amounts of time and electricity.

Current Gold Standard is FP16; balances speed and memory.

Scientific simulations (such as those simulating black holes or aircraft airflow) require extremely high numerical stability to prevent errors from accumulating over time; while LLM training is more like finding a probability distribution of the “general direction,” where speed and model size are more important than accuracy to the 15th decimal place.

Vulnerability details: NVIDIA APEX for Linux contains a vulnerability where an unauthorized attacker could cause a deserialization of untrusted data. This vulnerability affects environments that use PyTorch versions earlier than 2.6. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, data tampering, and information disclosure.

Official announcement: Please refer to the link for details –

https://nvidia.custhelp.com/app/answers/detail/a_id/5782

Best Practices:

•Weight Files: Always convert and store your .pth or .bin files as .safetensors.

•API Inputs: Prefer Protocol Buffers (Protobuf) or JSON for real-time requests.

•Integrity Checks: Before deserializing, verify the file’s SHA-256 hash to ensure it hasn’t been tampered with during transit

Do not underestimate the design flaws of jsrsasign (CVE-2026-4603) – 25th Mar 2026

Preface: Software and platforms known to use jsrsasign include CustomJS, ServieNow, Postman, jwt.io, the BitcoinJS library, OpenPGP.js, Google Apps Script, and add-on utilities.

Background: Jsrsasign (RSA-Sign JavaScript Library) is a pure JavaScript cryptographic library designed to handle RSA, ECDSA, and DSA operations, including key generation, digital signature creation/verification, and encryption. It provides the mathematical and structural setup for parsing keys (PKCS#1/5/8) and managing signatures.

Objectives of Specific Code Paths

  • ext/rsa[.]js (RSASetPublic/KEYUTIL parsing path):
    • Objective: This path is responsible for initializing an RSA public key by parsing raw data (like a modulus n and exponent e).
    • Function: It takes external key formats—such as JSON Web Keys (JWK) or PEM-encoded strings—and converts them into a internal format that the library can use for cryptographic math.
  • ext/jsbn[.]js (BigInteger.modPowInt reduction logic):
    • Objective: This logic performs modular exponentiation (m to power e), which is the core mathematical operation of RSA.
    • Function: It uses an optimized algorithm (often a sliding window or Montgomery representation) to calculate high-power results efficiently on large numbers that standard JavaScript cannot handle. 

Vulnerability details: Versions of the package jsrsasign before 11.1.1 are vulnerable to Division by zero due to the RSASetPublic/KEYUTIL parsing path in ext/rsa.js and the BigInteger.modPowInt reduction logic in ext/jsbn.js. An attacker can force RSA public-key operations (e.g., verify and encryption) to collapse to deterministic zero outputs and hide “invalid key” errors by supplying a JWK whose modulus decodes to zero.

Official announcement: Please refer to the link for details –

https://nvd.nist.gov/vuln/detail/CVE-2026-4603

About Chrome: CVE-2026-3910 is triggered by CVE-2026-3543. (23rd Mar 2026)

Preface: Electron is a framework enabling developers to build cross-platform desktop applications for macOS, Windows, and Linux by combining web technologies (HTML, JavaScript, CSS) with Node.js and native code. It is open-source, MIT-licensed, and free for both commercial and personal use. JavaScript calling Inter-Process Communication (IPC) is a critical technique, particularly in desktop application frameworks like Electron, to bridge the gap between the isolated renderer process (user interface) and the main process (Node.js backend/OS access.

Background: Electron is popular for building desktop apps—like

VS Code and Slack—because it allows developers to use web technologies (HTML, CSS, JavaScript) to create cross-platform applications. By bundling Chromium and Node.js, it eliminates the need to write separate code for Windows, macOS, and Linux.

Key Facts about CVE-2026-3910

Root Cause: The flaw is a logic error specifically within the V8 engine’s JIT (Just-In-Time) optimization process.

Primary Impact: It allows a remote attacker to execute arbitrary code within the browser’s sandbox environment via a specially crafted HTML page.

Because V8 is the core engine for all Chromium-based software, these vulnerabilities exist in Google Chrome, Microsoft Edge, and Opera—none of which use the Electron framework for their internal logic. Because V8 is the core engine for all Chromium-based software, these vulnerabilities exist in Google Chrome, Microsoft Edge, and Opera—none of which use the Electron framework for their internal logic.

If an attacker uses CVE-2026-3543 to get memory access, they can then use that “foothold” to manipulate the IPC (Inter-Process Communication) and trigger CVE-2026-3910.

Vulnerability details: Inappropriate implementation in V8 in Google Chrome prior to 146.0.7680.75 allowed a remote attacker to execute arbitrary code inside a sandbox via a crafted HTML page. (Chromium security severity: High)

Official announcement: Please refer to the link for details.

https://nvd.nist.gov/vuln/detail/CVE-2026-3910

This analysis examine the security content of Background Security Improvements for iOS 26.3.1, iPadOS 26.3.1, macOS 26.3.1, and macOS 26.3.2 (23rd Mar 2026)

Preface: Since the details of the vulnerability are not described in detail, based on my interest in the topic, specific details are shown in the attached diagram.

Background: The Navigation API is a standard, modern web platform API, not specific to WebKit’s internal code, but implemented by WebKit (and other browser engines like Chromium and Gecko) for use by web application developers.

To implement the Navigation API in a WebKit-based environment (like Safari) while adhering to the Same-Origin Policy (SOP), you must focus on intercepting and managing navigation events within the same origin.

The Navigation API is designed to work strictly within the current browsing context and only exposes history entries with the same origin (matching protocol, host, and port) as the current page.

Related Mechanisms – Developers can use controlled mechanisms to relax the SOP when legitimate cross-origin communication is necessary: window[.]postMessage(): A method for securely communicating between scripts in different windows or iframes regardless of their origin, using message passing.

Vulnerability details: A cross-origin issue in the Navigation API was addressed with improved input validation. This issue is fixed in Background Security Improvements for iOS 26.3.1, iPadOS 26.3.1, macOS 26.3.1, and macOS 26.3.2. Processing maliciously crafted web content may bypass Same Origin Policy.

CWE-346 is a logic failure where the code tries to check the origin but does it incorrectly (e.g., your WebKit case where it validated the host but ignored the port).

Impact: An attacker could use maliciously crafted web content to bypass SOP entirely, potentially accessing sensitive data from other sites, such as session tokens or credentials.

Official announcement: Fix – Apple addressed this in March 2026 through its new Background Security Improvements system for iOS 26.3.1 and macOS 26.3.1. 

About INTEL-SA-01393: Do not contempt in the medium-risk UEFI design weakness.(20th Mar 2026)

Preface: Intel Xeon W processor UEFI settings differ from consumer Intel Core CPUs, primarily to support enterprise-grade features. Xeon W UEFI (BIOS) includes specialized configurations for ECC RAM management, enhanced virtualization, advanced PCIe lane configuration, and platform-specific stability settings not required for standard desktop systems.

Background: Linux tools can modify fundamental UEFI settings, including variables, boot order, and Secure Boot keys (PK, KEK, db, dbx) using tools like efibootmgr, efitools, and direct /sys/firmware/efi/efivars access. Advanced tools can even modify flash images, though direct firmware flashing is generally manufacturer-dependent.

Strengthening length validation in efivarfs

– before performing memory comparisons to prevent OOB (Out-of-Bounds) access.

Strict Length Match:

Ensure the length of the string to be compared (len)

matches the expected length (name->len) exactly.

Vulnerability details: A potential security vulnerability in UEFI for some Intel Reference Platforms may allow escalation of privilege. Intel is releasing firmware updates to mitigate these potential vulnerability.

CVE-2025-20096: Improper input validation in the UEFI firmware for some Intel Reference Platforms may allow an escalation of privilege. System software adversary with a privileged user combined with a high complexity attack may enable data manipulation. This result may potentially occur via local access when attack requirements are present without special internal knowledge and requires active user interaction. The potential vulnerability may impact the confidentiality (none), integrity (high) and availability (high) of the vulnerable system, resulting in subsequent system confidentiality (none), integrity (high) and availability (high) impacts.

Official announcement: Please refer to the link for details – https://www.intel.com/content/www/us/en/security-center/advisory/intel-sa-01393.html

CVE-2026-4295: Improper trust boundary enforcement in Kiro IDE before version 0.8.0 on all supported platforms (19th Mar 2026)

Preface: AWS launched Kiro to make it the default entry point for cloud development. When developers open Kiro, it is already pre-configured with deep connections to AWS services (such as Lambda, S3, and Bedrock), making “cloud-native development” an out-of-the-box experience. Since Kiro includes an LLM, Kiro is involved in whatever the developer does. The advantage is that any incorrectly programmed code, Kiro will advise. On the other hand, all programmer thinking will also be learned by Kiro!

Background: Visual studio code capable multi-root workspace over a folder. VS Code that allows you to configure multiple distinct folders to be part of the same workspace. Instead of opening a folder as workspace, you open a <name>[.]code-workspace JSON file that lists all folders of the workspace. In Kiro-IDE, if a user clicks “Trust this Workspace” for the [.]code-workspace file, the IDE may incorrectly extend that trust to all folders listed in the JSON. A threat actor can include a folder they control—containing a malicious [.]kiro/scripts[.]json or [.]vscode/settings[.]json—which then executes with the user’s full permissions because the parent workspace was marked as “trusted.”

Vulnerability details: Improper trust boundary enforcement in Kiro IDE before version 0.8.0 on all supported platforms might allow a remote unauthenticated threat actor to execute arbitrary code via maliciously crafted project directory files that bypass workspace trust protections when a local user opens the directory. To remediate this issue, users should upgrade to version 0.8.0 or higher.

Official announcement: Please refer to the link for more details –

https://nvd.nist.gov/vuln/detail/CVE-2026-4295

AMD ID: AMD-SB-7050: About Vector Value Injection in AMD CPUs, AMD believes that existing mitigation guidance for FPVI remains valid and covers VVI cases as well. What are your thoughts on this? (18th Mar 2026)

Background: The researchers’ paper introduces Vector Value Injection (VVI), which could allow an attacker with a deep understanding of microarchitectural behavior to inject values into vector registers during transient execution. Although they noted similarities with Floating Point Value Injection (FPVI), they reported Vector Value Injection as a new issue due to its capability to be triggered without denormal values as inputs.

AMD believes that VVI falls within the existing scope of CVE-2021-26314 (FPVI) as existing descriptions of FPVI do not specifically require denormal inputs. Additionally, AMD believes that existing mitigation guidance for FPVI remains valid and covers VVI cases as well.

Ref: CVE-2021-26314 – Potential floating point value injection in all supported CPU products, in conjunction with software vulnerabilities relating to speculative execution with incorrect floating point results, may cause the use of incorrect data from FPVI and may result in data leakage.

Official announcement: AMD ID: AMD-SB-7050 “Vector Value Injection in AMD CPUs”. Please refer to the link for details – https://www.amd.com/en/resources/product-security/bulletin/amd-sb-7050.html

CVE-2021-26314 is a vulnerability from five years ago; however, in today’s parallel environment, the situation may be different!

How does Parallel Processing handle “Different Types”?

When tasks are different (e.g., one calculates Pi, one downloads a file, one reads a database), the system handles them in three ways:

1.         Heterogeneous Task Assignment (Asynchronous):

Instead of using a “map” (which does the same thing to many items), we use apply_async. This allows Core 1 to run a “Math” function while Core 2 runs a “Data Backup” function simultaneously.

2.         OS Scheduling & Context Switching:

The Operating System (OS) is the “manager.” If Task A is waiting for a slow Hard Drive (I/O Bound), the OS immediately moves Task B (CPU Bound) onto that core so no time is wasted.

3.         Hardware Resource Partitioning:

On a chip like the 9995WX, different execution units inside the core can work at once. One part of the core handles Integer math, while another handles Floating Point (AVX-512). This allows the processor to crunch different types of data within the same clock cycle

Vector Value Injection integrated to pool.apply_async (which runs different functions simultaneously) cannot be curcumvented through Register Scrubbing or Control-Flow Enforcement (CET). In fact, manually assigning different functions using `apply_async’ lowers the defense level potentially.

Why apply_async May Lower the Defense Level?

When you use pool.apply_async to launch different functions, Python’s multiprocessing creates multiple independent OS Processes.

•          Expanded Attack Surface: Compared to a single-process loop, a multi-process environment increases the frequency of Inter-Process Communication (IPC). If an attacker leverages Vector Value Injection, they can hunt for vulnerabilities in the different logic paths of each unique function.

•          Context Switching Risks: Frequent task scheduling can increase the risk of Cache Side-channel leaks. These leaks can sometimes bypass Register Scrubbing protection by capturing data before it is cleared.

End of article

CVE-2026-0032 and CVE-2026-0038: Design weakness in Qualcomm SCM (Secure Channel Manager) and Qualcomm SCM/pKVM (Protected KVM). 17th Mar 2026

Preface: CVE-2026-0032 and CVE-2026-0038 are very similar in terms of their root cause, impact, and remedies, as they both originate from a logical error in the Android kernel memory protection subsystem.

Background: In the Android Virtualization Framework (AVF), all guest operating systems (like the main Android OS and Microdroid) run at EL1, while the actual hypervisor (pKVM) runs at EL2. In Android downstream kernels (especially those for Qualcomm or MediaTek SoCs), the log details containing 0x%llx (a 64-bit hexadecimal address) represent physical memory ranges being transitioned into an isolated state.

This isolation is a critical security layer used to protect high-value hardware components from the main Android OS.

Key Similarities – Both vulnerabilities reside in the mem_protect[.]c file, which is responsible for enforcing memory access boundaries and managing memory protection between different execution environments (like the kernel and the Secure World).

The “similar” nature of these design weakness lies in how the qcom_scm_assign_mem logic was implemented. In both cases, the system failed to properly validate or constrain memory assignment requests, allowing a local attacker to bypass security restrictions.

Vulnerability details:

CVE-2026-0032 In multiple functions of mem_protect[.]c, there is a possible out-of-bounds write due to a logic error in the code. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

Primary Driver – Qualcomm SCM (Secure Channel Manager)

CVE-2026-0038In multiple functions of mem_protect[.]c, there is a possible way to execute arbitrary code due to a logic error in the code. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

Primary Driver – Qualcomm SCM / pKVM (Protected KVM)

Official announcement: Please refer to the link for details –  

CVE-2026-0038 – https://nvd.nist.gov/vuln/detail/CVE-2026-0038 CVE-2026-0032 – https://nvd.nist.gov/vuln/detail/CVE-2026-0032