Category Archives: Potential Risk of CVE

CVE-2026-5164: A flaw has been found in virtio-win. Don’t underestimate this; the field of artificial intelligence also needs virtio-win! (1st April 2026)

Preface: While NVIDIA CUDA provides powerful parallel processing capabilities on both Linux and Windows, developers still need to run Windows on top of Linux using virtio-win in several specific environments:

For example: Windows-Exclusive HPC Applications

Many specialized scientific and engineering applications are only developed for Windows and cannot be easily recompiled for Linux.

Background: To programmatically use RhelDoUnMap() while ensuring user requests are correctly validated, you must specifically address the descriptor count validation to prevent buffer overflows. This function is part of the virtio-win drivers used in Red Hat Enterprise Linux environments.

Key Components of virtio-win include Network (NetKVM), Storage (viostor / virtio-scsi), Memory Balloon (balloon), Serial (virtio-serial), Graphics (virtio-gpu), Input (virtio-input) and Guest Agent (qemu-ga). The RhelDoUnMap() function is part of the virtio-win driver suite, specifically within the VioStor (Virtio Storage) driver.

Vulnerability details : A flaw was found in virtio-win. The `RhelDoUnMap()` function does not properly validate the number of descriptors provided by a user during an unmap request. A local user could exploit this input validation vulnerability by supplying an excessive number of descriptors, leading to a buffer overrun. This can cause a system crash, resulting in a Denial of Service (DoS).

Official announcement: Please refer to the link for details –

https://nvd.nist.gov/vuln/detail/cve-2026-5164

About Trivy: Closer Look what is happen through CI/CD Ecosystems. Staying alert! (31st Mar 2026)

Preface: According to Mandiant, over a thousand SaaS environments have been impacted by ongoing supply chain compromises of Aqua Security’s open-source scanner Trivy, and researchers predict that the impact may grow by an order of magnitude.

Researchers have since reported multiple downstream attacks enabled by the compromise, possibly via implementations of Trivy. Sysdig observed the TeamPCP infostealer deployed in a GitHub action belonging to another software supply chain security developer, Checkmarx. Aikido Security reported attacks targeting the npm ecosystem and Kubernetes, spreading a persistent Python backdoor through “CanisterWorm,” which steals npm tokens to propagate itself through developers’ packages.

Background: Trivy is a popular open-source vulnerability and security scanner maintained by Aqua Security. Trivy is a “universal” scanner that consolidates multiple security checks into a single tool:

  • Vulnerability Scanning: Detects known vulnerabilities (CVEs) in operating system packages (e.g., Alpine, RHEL, Ubuntu) and language-specific dependencies (e.g., npm, pip, Go modules).
  • Misconfiguration Detection: Scans Infrastructure as Code (IaC) files like Terraform, Dockerfiles, Kubernetes manifests, and CloudFormation to find security flaws.
  • Secret Scanning: Identifies hardcoded sensitive information such as passwords, API keys, and tokens within code or container images.

Closer Look of Trivy design weakness:

The Mechanism: In Git, version tags (like @v1 or @v0.24.0) are mutable, meaning they can be reassigned to a different commit. The attackers used compromised credentials to “poison” 76 out of 77 existing version tags for trivy-action, pointing them to a new, malicious commit that contained a credential stealer.

The “Design Weakness”: Because pipelines are usually configured to pull the latest version of a tag automatically, thousands of organizations executed the malicious code without any changes to their own workflow files.

Official details: Please refer to the link for details  – https://nvd.nist.gov/vuln/detail/CVE-2026-33634

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