[SECURITY] Fedora 41 Update: nodejs22-22.15.1-1.fc41

Node.js is a platform built on Chrome's JavaScript runtime \ for easily building fast, scalable network applications. \ Node.js uses an event-driven, non-blocking I/O model that \ makes it lightweight and efficient, perfect for data-intensive \ real-time applications that run across distributed...

[SECURITY] Fedora 42 Update: nodejs22-22.15.1-1.fc42

Node.js is a platform built on Chrome's JavaScript runtime \ for easily building fast, scalable network applications. \ Node.js uses an event-driven, non-blocking I/O model that \ makes it lightweight and efficient, perfect for data-intensive \ real-time applications that run across distributed...

[SECURITY] Fedora 42 Update: nodejs20-20.19.2-1.fc42

Node.js is a platform built on Chrome's JavaScript runtime \ for easily building fast, scalable network applications. \ Node.js uses an event-driven, non-blocking I/O model that \ makes it lightweight and efficient, perfect for data-intensive \ real-time applications that run across distributed...

Machine Learning Models Have a Supply Chain Problem

Powerful machine learning ML models are now readily available online, which creates exciting possibilities for users who lack the deep technical expertise or substantial computing resources needed to develop them. On the other hand, this type of open ecosystem comes with many risks. In this paper...

TensorShield: Safeguarding On-Device Inference by Shielding Critical DNN Tensors with TEE

To safeguard user data privacy, on-device inference has emerged as a prominent paradigm on mobile and Internet of Things IoT devices. This paradigm involves deploying a model provided by a third party on local devices to perform inference tasks. However, it exposes the private model to two primar...

Smart Contracts for SMEs and Large Companies

Research on blockchains addresses multiple issues, with one being writing smart contracts. In our previous research we described methodology and a tool to generate, in automated fashion, smart contracts from BPMN models. The generated smart contracts provide support for multi-step transactions th...

VulBinLLM: LLM-Powered Vulnerability Detection for Stripped Binaries

Recognizing vulnerabilities in stripped binary files presents a significant challenge in software security. Although some progress has been made in generating human-readable information from decompiled binary files with Large Language Models LLMs, effectively and scalably detecting vulnerabilitie...

aws-mcp-server 操作系统命令注入漏洞

aws-mcp-server is a lightweight service by Alexei Ledenev Personal Developer that enables AI assistants to execute AWS CLI commands in a secure containerized environment via the Model Context Protocol MCP. A security vulnerability exists in aws-mcp-server that stems from command injection and cou...

The vulnerability of the formDhcpv6s interface in the BOA microprogramming software of TOTOLINK A3002R routers allows a perpetrator to compromise the confidentiality and integrity of the protected information.

The vulnerability of the formDhcpv6s interface in the boa microprogramming software of TOTOLINK A3002R routers is related to buffer overflow during the processing of the addrPoolStart parameter. Exploiting this vulnerability allows an attacker to compromise the confidentiality and integrity of th...

TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy Leaking Agent

As large language models LLMs become integrated into sensitive workflows, concerns grow over their potential to leak confidential information. We propose TrojanStego, a novel threat model in which an adversary fine-tunes an LLM to embed sensitive context information into natural-looking outputs v...

The Feasibility of Topic-Based Watermarking on Academic Peer Reviews

Large language models LLMs are increasingly integrated into academic workflows, with many conferences and journals permitting their use for tasks such as language refinement and literature summarization. However, their use in peer review remains prohibited due to concerns around confidentiality...

JavaSith: a Client-Side Framework for Analyzing Potentially Malicious Extensions in Browsers, VS Code, and NPM Packages

Modern software supply chains face an increasing threat from malicious code hidden in trusted components such as browser extensions, IDE extensions, and open-source packages. This paper introduces JavaSith, a novel client-side framework for analyzing potentially malicious extensions in web...

PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects

The average treatment effect ATE is widely used to evaluate the effectiveness of drugs and other medical interventions. In safety-critical applications like medicine, reliable inferences about the ATE typically require valid uncertainty quantification, such as through confidence intervals CIs...

BitHydra: Towards Bit-Flip Inference Cost Attack against Large Language Models

Large language models LLMs have shown impressive capabilities across a wide range of applications, but their ever-increasing size and resource demands make them vulnerable to inference cost attacks, where attackers induce victim LLMs to generate the longest possible output content. In this paper,...

Red-Teaming Text-To-Image Systems by Rule-Based Preference Modeling

Text-to-image T2I models raise ethical and safety concerns due to their potential to generate inappropriate or harmful images. Evaluating these models' security through red-teaming is vital, yet white-box approaches are limited by their need for internal access, complicating their use with...

CVE-2025-5202

A vulnerability was found in Open Asset Import Library Assimp 5.4.3. It has been declared as problematic. Affected by this vulnerability is the function HL1MDLLoader::validateheader of the file assimp/code/AssetLib/MDL/HalfLife/HL1MDLLoader.cpp. The manipulation leads to out-of-bounds read. An...

UBUNTU-CVE-2025-5202

A vulnerability was found in Open Asset Import Library Assimp 5.4.3. It has been declared as problematic. Affected by this vulnerability is the function HL1MDLLoader::validateheader of the file assimp/code/AssetLib/MDL/HalfLife/HL1MDLLoader.cpp. The manipulation leads to out-of-bounds read. An...

DEBIAN-CVE-2025-5200

A vulnerability was found in Open Asset Import Library Assimp 5.4.3 and classified as problematic. This issue affects the function MDLImporter::InternReadFileQuake1 of the file assimp/code/AssetLib/MDL/MDLLoader.cpp. The manipulation leads to out-of-bounds read. It is possible to launch the attac...

Out-of-bounds Read

Overview Affected versions of this package are vulnerable to Out-of-bounds Read through the MDLImporter::InternReadFileQuake1 function. An attacker can read data outside the intended buffer boundaries by manipulating the input data to the function. Remediation There is no fixed version for assimp...

DEBIAN-CVE-2025-5169

A vulnerability classified as problematic has been found in Open Asset Import Library Assimp 5.4.3. This affects the function MDLImporter::InternReadFile3DGSMDL345 of the file assimp/code/AssetLib/MDL/MDLLoader.cpp. The manipulation leads to out-of-bounds read. Local access is required to approac...