Potential Risk of CVE

CVE-2025-47319: Exposure of Sensitive System Information to an Unauthorized Control Sphere in HLOS (4th Dec 2025)

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Published: 12/01/2025

Preface: Qualcomm HLOS (High-Level Operating System) refers to the operating system layer, like Android, that runs on a Qualcomm Snapdragon chipset and is responsible for general device functionality. “TA” (Trusted Application) is a component of the Qualcomm Trusted Execution Environment (QTEE) that runs in a secure environment, separate from the HLOS. Security issues arise when vulnerabilities exist at the boundary between the HLOS and a TA, such as memory corruption when the HLOS improperly processes commands from a TA, as described in Qualcomm security bulletins.

Background: The Qualcomm Secure Execution Environment Communication (QSEECom) lifecycle describes how a client application in the normal world interacts with a trusted application (TA) in the secure world via the qseecom kernel driver.

Step 1. QSEECom_start_app: Loads the TA into QTEE and allocates shared memory (ion_sbuffer) for communication.

Step 2. ion_sbuffer: The shared memory buffer used for both input and output.

Step 3:QSEECom_send_cmd: Sends a command to the TA, using the shared buffer.

Step 4: QSEECom_shutdown_app: Cleans up and unloads the TA.

Vulnerability details: CVE-2025-47319

  • Component: High-Level Operating System (HLOS)
  • Nature: Design weakness in buffer size calculation when processing commands from a Trusted Application (TA).
  • Impact: Could lead to buffer overflow, exposing sensitive system information and enabling arbitrary code execution.
  • Severity: Qualcomm rates it as critical, though its CVSS score is medium.
  • Discovery: Internal Qualcomm security team.

Mitigation: Patches have been shared with OEMs; users should update devices promptly.

Official announcement: Please refer to the link for details –

https://docs.qualcomm.com/product/publicresources/securitybulletin/december-2025-bulletin.html

IoT, Potential Risk of CVE

CVE-2025-66216: About AIS-catcher (3rd Dec 2025)

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Preface: AIS-Catcher is a MIT licensed dual band AIS receiver for Linux, Windows and Raspberry Pi. It is compatible with RTL-SDR dongles and the Airspy HF+.

AIS stands for Automatic Identification System and is used by marine vessels to broadcast their GPS locations in order to help avoid collisions and aide with rescues. An RTL-SDR with the right software can be used to receive and decode these signals, and plot ship positions on a map.

Background: You can set up your own receiver at home. With just a small USB radio adapter and a simple antenna, you can receive live signals from nearby ships and decode them directly on your computer or Raspberry Pi.

Setup requirement for an SDR AIS Receiver:

-RTL-SDR dongle (e.g. Nooelec NESDR, RTL-SDR Blog V3)

-VHF antenna (marine band, tuned for ~162 MHz)

-Raspberry Pi (Model 3 or later) or any PC

-Internet connection (for updates, optional data sharing)

Recommended Command (Dual-channel AIS, Auto Gain)

This does the following:

-A listens to both AIS frequencies:

Channel 1: 161.975 MHz

Channel 2: 162.025 MHz

-g auto lets AIS-catcher automatically choose the gain setting

Uses default device (-d 0) unless otherwise specified

You should see continuous outputs like this:

!AIVDM,1,1,,B,15MuqP001oK>rWnE`D0?;wvP0<2R,0*6D

These are raw NMEA AIS messages being received in real time.

Vulnerability details: CVE-2025-66216 – AIS-catcher is a multi-platform AIS receiver. Prior to version 0.64, a heap buffer overflow vulnerability has been identified in the AIS::Message class of AIS-catcher. This vulnerability allows an attacker to write approximately 1KB of arbitrary data into a 128-byte buffer. This issue has been patched in version 0.64.

Best Practices:

Never store data() pointer across operations that can reallocate (like push_back, resize, insert, emplace).

If you need a stable pointer, consider:

  • std::deque (doesn’t invalidate all pointers on growth).
  • std::vector::reserve() before operations to avoid reallocation.
  • Or use indices instead of raw pointers.

Official announcement: Please refer to the link for details – https://www.tenable.com/cve/CVE-2025-66216

Potential Risk of CVE

CVE-2025-12183: About official lz4-java library (2nd Dec 2025)

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Published: 2025-11-28

Preface: Apache Hadoop and Apache Spark are both prominent and widely used frameworks for big data analytics. They are central to the processing and analysis of large datasets that cannot be handled by traditional data processing tools.

Apache Hadoop utilizes the MapReduce programming model as a core component for processing and analyzing large datasets in a distributed manner.

How memory is used in Hadoop? Application Memory – Hadoop applications, such as those running on YARN (Yet Another Resource Negotiator), also utilize RAM for their processing needs. For instance, MapReduce tasks and Spark applications perform computations in memory, leveraging RAM for faster data access and processing.

Background: LZ4 is a very fast lossless compression algorithm, providing compression speed > 500 MB/s per core, scalable with multi-cores CPU. It also features an extremely fast decoder, with speed in multiple GB/s per core, typically reaching RAM speed limits on multi-core systems.

The liblz4-java[.]so file is a native shared library that provides the underlying LZ4 compression and decompression functionality for the lz4-java library in Java applications.

From technical point of view,  liblz4-java[.]so acts as the high-performance engine for LZ4 operations, while the Java lz4-java library provides a convenient and type-safe API for Java developers to interact with this engine.

Remark: Since the maintainers of the official lz4-java library could not be contacted, the lz4 organization decided to discontinue the project.

Vulnerability details:

CVE-2025-12183 – Out-of-bounds memory operations in org.lz4:lz4-java 1.8.0 and earlier allow remote attackers to cause denial of service and read adjacent memory via untrusted compressed input.

Official announcement: Please refer to the link for details –

https://www.tenable.com/cve/CVE-2025-12183

AI and ML, Potential Risk of CVE

CVE-2025-33204: About NVIDIA NeMo Framework (1st Dec 2025)

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Official Update 11/21/2025 04:36 PM

Preface: NeMo Curator is a Python library that includes a suite of modules for data-mining and synthetic data generation. They are scalable and optimized for GPUs, making them ideal for curating natural language data to train or fine-tune LLMs. With NeMo Curator, researchers in Natural Language Processing (NLP) can efficiently extract high-quality text from extensive raw web data sources.

NVIDIA NeMo Curator, particularly its image curation modules, requires a CUDA-enabled NVIDIA GPU and the corresponding CUDA Toolkit. The CUDA Toolkit is not installed as part of the NeMo Curator installation process itself, but rather is a prerequisite for utilizing GPU-accelerated features.

Background: NeMo Framework includes NeMo Curator because high-quality data is essential for training accurate generative AI models, and Curator provides a scalable, GPU-accelerated toolset for processing and preparing large datasets efficiently. It handles everything from cleaning and deduplicating text to generating synthetic data for model customization and evaluation, preventing data processing from becoming a bottleneck.

Potential risks under observation: The vulnerability arises when malicious files—such as JSONL files—are loaded by NeMo Curator. If these files are crafted to exploit weaknesses in how NeMo Curator parses or processes them, they can inject executable code.

Ref: Parser is related to predefined variables, as it can either parse data into variables or use predefined variables to perform its task.

Vulnerability details:

CVE-2025-33204         NVIDIA NeMo Framework for all platforms contains a vulnerability in the NLP and LLM components, where malicious data created by an attacker could cause code injection. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.

CVE-2025-33205         NVIDIA NeMo framework contains a vulnerability in a predefined variable, where an attacker could cause inclusion of functionality from an untrusted control sphere by use of a predefined variable. A successful exploit of this vulnerability may lead to code execution.

Official announcement: Please refer to the link for details –

https://nvidia.custhelp.com/app/answers/detail/a_id/5729

Science

Comets share similar characteristics. What makes Comet 3I/ATLAS special is that the main volatile substance in its coma is carbon dioxide (CO₂)?

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Preface: In 14th April,1561, an unidentified flying objects (UFO) above Nuremberg, Germany. Above diagram shown a broadsheet news article printed in April 1561. Is it a coincidence? A pillar shape unknown flying object shown on the picture. As we know, in 1903 the Wright brothers had invented the first successful airplane. Talking about three hundred and fifty years ago, human being do not have airplane concept. As a result, when they seen similar shape of UFO. Perhaps they will only draw or use the key word pillar for description.

Point of view: 3I/ATLAS is unusual because carbon dioxide CO₂ is the dominant volatile material in its coma, with an observed ratio of CO₂ to water H₂O around 8 to 1. This is in contrast to most comets in our solar system, where water is typically the primary component.

Technical perspective: Compounds that release CO2 when heated include metal carbonates and bicarbonates, and organic compounds.

Hypothesis: If 3I/ATLAS is not a comet, and its coma contains volatile carbon dioxide (CO₂), what technology would have this effect?

Compounds that release CO2 when heated include metal carbonates and bicarbonates, and organic compounds.

Metal carbonates have several applications in nuclear facilities, including the removal of radionuclides from liquid waste via co-precipitation, use in the fabrication of nuclear fuel, and cleaning of condenser tubes.

The use of metal carbonates in nuclear fuel fabrication and condenser tube cleaning will likely release carbon dioxide CO2 under certain conditions, as both processes can involve heating. In nuclear fuel fabrication, metal carbonates can be heated, causing their decomposition into metal oxides and releasing CO2.

Humanity: Pride and Prejudice

The scientific community avoids discussing advanced civilizations to prevent conflicts with mainstream views and traditional cultures. However, many remnants of ancient civilizations exist on our planet that not made by mankind. Example. Puma Punku (at the junction of present-day Peru and Bolivia), The Temple of Bacchus is part of the Baalbek temple complex located in the broad Al-biqā (Bekaa Valley), Lebanon (stone base structure cannot build by human)……etc.

The most senior priests of the Dogon people have learned about a phenomenon four hundred years ago. The religious doctrines that have been circulated for four hundred years in the Dogon population contain a wealth of knowledge about a star. The star is invisible with the naked eye, even with a telescope. It is Sirius B star.

Current status of 3I/Atlas:  provided by Dr. Avi Loeb. (see below link):

https://avi-loeb.medium.com/a-remarkable-new-anomaly-of-3i-atlas-420065c2cddf

AI and ML, Potential Risk of CVE

CVE-2025-33203 – Design weakness of NVIDIA NeMo Agent Toolkit UI for Web. Another preventive approach. (28th Nov 2025)

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Preface: While web vulnerabilities can lead to various cyberattacks, they don’t directly or exclusively cause ransomware attacks. CSRF attacks exploit the trust a website has in a user’s browser to perform unauthorized actions on that website, while ransomware involves malware that encrypts a user’s system and demands payment.

Background: The official frontend user interface component for NeMo Agent Toolkit, an open-source library for building AI agents and workflows.

Prerequisites

  • NeMo Agent Toolkit installed and configured
  • Git
  • Node.js (v18 or higher)
  • npm or Docker

While Node.js v18 itself doesn’t inherently prevent or cause CSRF, it’s crucial to implement proper CSRF protection in your Node.js applications built with this version. Node.js v18 is now End-of-Life (EOL), meaning it no longer receives security updates, which makes implementing robust security measures even more critical.

Vulnerability details: CVE-2025-33203 – NVIDIA NeMo Agent Toolkit UI for Web contains a vulnerability in the chat API endpoint where an attacker may cause a Server-Side Request Forgery. A successful exploit of this vulnerability may lead to information disclosure and denial of service.

Affected Products:      NeMo Agent ToolKit  

Platforms or OS: All platforms

Affected Product: NeMo Agent ToolKit

Affected Versions: All versions prior to 1.3.0

Updated Version: 1.3.0

Official announcement: Please refer to the link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5726

AI and ML, Potential Risk of CVE

AI developers, please do not underestimate the CVE-2025-33187 (NVIDIA DGX Spark GB10) vulnerability (26th Nov 2025)

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Updated 11/21/2025 04:36 PM

Preface: NVIDIA DGX Spark will be used by AI developers, researchers, and data scientists who need to prototype and deploy large AI models on their desktop, including those working with agentic AI, LLMs, and robotics.

The NVIDIA DGX Secure Root of Trust (SRoT), more commonly referred to as the Hardware Root of Trust (HRoT), is a foundational security component embedded in the system’s hardware, including the main GPUs and the BlueField Data Processing Units (DPUs).

The term “NVIDIA DGX SROOT” refers to the Secure Root of Trust (SROOT) firmware component within the NVIDIA DGX Spark personal AI supercomputer. It is a security feature designed to ensure the integrity of the system’s secure boot process and certificate management.

Background: The DGX Spark runs on NVIDIA DGX OS, a customized Ubuntu Linux distribution that includes a full-stack NVIDIA AI software ecosystem. The NVIDIA GB10 is a Superchip that integrates separate CPU and GPU dies in a single package, and the operating system is not embedded within the CPU die itself. Instead, the OS is installed on external NVMe storage, and the system uses unified memory accessible by both dies.

The OS and related software stack are stored on external NVMe solid-state drives (SSDs), not on the CPU die. The DGX Spark workstation typically includes up to 4 TB of NVMe storage.

However, Nvidia SROOT is an internal firmware element located in the Nvidia DGX Spark GB10 systems. It is a specific firmware component that runs on the system’s hardware.

Vulnerability details: CVE-2025-33187 – NVIDIA DGX Spark GB10 contains a vulnerability in SROOT, where an attacker could use privileged access to gain access to SoC protected areas. A successful exploit of this vulnerability might lead to code execution, information disclosure, data tampering, denial of service, or escalation of privileges.

Official announcement: Please refer to the link for details – https://nvd.nist.gov/vuln/detail/CVE-2025-33187

IoT, Potential Risk of CVE

CVE-2025-48507: About calling processor into Arm Trusted Firmware (26th Nov 2025)

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Preface: AMD’s Zynq™ UltraScale+™ RFSoCs are a family of highly integrated adaptive Systems-on-Chip (SoCs) that combine a multi-core Arm® processing system, programmable logic (FPGA fabric), and direct RF-sampling data converters (ADCs and DACs) on a single chip. CVE-2025-48507 Affected Devices: Kria™ SOM, Zynq™ UltraScale+™ MPSoCs and Zynq™ UltraScale+™ RFSoCs.

Background: The crypto operations in Arm® Trusted Firmware (TF-A) are part of a subsystem, which can be implemented through various components like the Runtime Security Engine (RSE) or a dedicated secure enclave. This subsystem provides hardware-assisted security services, such as cryptographic acceleration and secure storage, which are distinct from the main processor and are protected by the system’s security architecture.

From a cyber security perspective, calling a processor into TF-A is different because it uses a specialized, secure boot process and requires the processor to switch to a secure state via a Secure Monitor Call (SMC) instruction, as outlined in the Arm Developer and Trusted Firmware-A Documentation. This differs from standard OS calls which typically use different mechanisms for switching between user and kernel modes.

*Secure Monitor Call (SMC): TF-A calls are initiated using the SMC instruction, which is specifically designed for secure operations and causes the processor to switch to a privileged secure state (like EL3).

Vulnerability details: The security state of the calling processor into Arm® Trusted Firmware (TF-A) is not used and could potentially allow non-secure processors access to secure memories, access to crypto operations, and the ability to turn on and off subsystems within the SOC.

Official announcement: Please refer to the link for details – https://www.tenable.com/cve/CVE-2025-48507

Cell Phone (iPhone, Android, windows mobile), Potential Risk of CVE

CVE-2025-65947: The thread_amount function calls, risk level change according to definitions. (25th Nov 2025)

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Published: 2025-11-21

Preface: The “mach kernel” in iOS refers to the **Mach kernel component of the XNU hybrid kernel, which is the core of Apple’s iOS operating system. XNU is a hybrid kernel that merges the Mach microkernel with components from the BSD Unix system to create a single, cohesive kernel that runs iOS and other Apple operating systems like macOS. This kernel architecture applies to all current iOS versions and will continue to be used in future versions running on Apple Silicon.

Background: In Apple platforms, the thread_amount function calls task_threads (via Mach kernel APIs) which allocates memory for the thread list. iOS uses a hybrid kernel called XNU, which is an acronym for “X is Not Unix”. This kernel combines components of the Mach microkernel and the FreeBSD Unix kernel to form the core of Apple’s Darwin operating system, which underpins iOS, macOS, watchOS, and other Apple platforms.

Vulnerability details: thread-amount is a tool that gets the amount of threads in the current process. Prior to version 0.2.2, there are resource leaks when querying thread counts on Windows and Apple platforms. In Windows platforms, the thread_amount function calls CreateToolhelp32Snapshot but fails to close the returned HANDLE using CloseHandle. Repeated calls to this function will cause the handle count of the process to grow indefinitely, eventually leading to system instability or process termination when the handle limit is reached. In Apple platforms, the thread_amount function calls task_threads (via Mach kernel APIs) which allocates memory for the thread list. The function fails to deallocate this memory using vm_deallocate. Repeated calls will result in a steady memory leak, eventually causing the process to be killed by the OOM (Out of Memory) killer. This issue has been patched in version 0.2.2.

Official announcement: Please refer to the link for details –

https://www.tenable.com/cve/CVE-2025-65947

Potential Risk of CVE

CVE-2025-29934 – A vulnerability exists in the TLB entries of certain AMD CPUs. (20th Nov 2025)

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Official announcement: November 11, 2025

Preface: AMD EPYC processors support an Input-Output Memory Management Unit (IOMMU), a hardware component essential for managing memory access for peripheral devices. IOMMU technology on EPYC platforms is a critical component for virtualization, device passthrough (PCIe passthrough), and system security.

Background: SEV-SNP mitigates many TLB (Translation Lookaside Buffer) attacks by having the CPU hardware perform automatic TLB flushes to maintain consistency between the TLB and the guest’s memory mappings, preventing a malicious hypervisor from poisoning a VM’s TLB. In contrast, earlier versions of SEV (without SNP) relied on the hypervisor for TLB consistency, which created a vulnerability to TLB poisoning attacks where the hypervisor could manipulate TLB entries between processes in a VM.

AMD Reverse Page Table, also known as the Reverse Map Table (RMP), is a hardware-managed data structure used in AMD processors, particularly with SEV-SNP (Secure Encrypted Virtualization – Secure Nested Paging), to track memory page ownership and security states. It works by having a single, system-wide table where the index is the physical memory frame number, and the entry contains the virtual page number and the process ID (or other identifier) that owns it. This is different from traditional page tables, which are process-specific and indexed by virtual page numbers. 

Ref: Improper handling of invalid nested page table entries in the IOMMU may allow a privileged attacker to induce page table entry (PTE) faults to bypass RMP checks in SEV-SNP, potentially leading to a loss of guest memory integrity.

Vulnerability details: CVE-2025-29934 – A bug within some AMD CPUs could allow a local admin-privileged attacker to run a SEV-SNP guest using stale TLB entries, potentially resulting in loss of data integrity.

Official announcement: Please refer to the link for details – https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3029.html#details

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