MS SWIFT Deserialization RCE Vulnerability

This appears to be a security vulnerability report describing a remote code execution RCE exploit in the ms-swift framework through malicious pickle deserialization in adapter model files. The vulnerability allows arbitrary command execution when loading specially crafted adapter models from...

Using LLMs as a reverse engineering sidekick

This research explores how large language models LLMs can complement, rather than replace, the efforts of malware analysts in the complex field of reverse engineering. LLMs may serve as powerful assistants to streamline workflows, enhance efficiency, and provide actionable insights during malware...

PT-2025-32493 · Pypi · Ms-Swift

This appears to be a security vulnerability report describing a remote code execution RCE exploit in the ms-swift framework through malicious pickle deserialization in adapter model files. The vulnerability allows arbitrary command execution when loading specially crafted adapter models from...

CVE-2025-8319

the BMA login interface allows arbitrary JavaScript or HTML to be written straight into the page’s Document Object Model via the error= URL parameter...

Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection

With the rapid expansion of web-based applications and cloud services, malicious JavaScript code continues to pose significant threats to user privacy, system integrity, and enterprise security. But, detecting such threats remains challenging due to sophisticated code obfuscation techniques and...

Vulnerability of software for modeling, designing, and drawing in AutoCAD, related to the execution of operations beyond buffer boundaries in memory, allowing attackers to execute arbitrary code or cause system failures.

The vulnerability of software for modeling, designing, and drawing in AutoCAD is related to the execution of operations beyond the buffer boundaries in memory. Exploiting this vulnerability can allow an attacker to execute arbitrary code or cause a service failure using a specially created 3DM fi...

Cryptanalysis of LC-MUME: a Lightweight Certificateless Multi-User Matchmaking Encryption for Mobile Devices

Yang et al. proposed a lightweight certificateless multiuser matchmaking encryption LC-MUME scheme for mobile devices, published in IEEE Transactions on Information Forensics and Security TIFS DOI: 10.1109/TIFS.2023.3321961. Their construction aims to reduce computational and communication overhe...

Resource-Efficient Automatic Software Vulnerability Assessment Via Knowledge Distillation and Particle Swarm Optimization

The increasing complexity of software systems has led to a surge in cybersecurity vulnerabilities, necessitating efficient and scalable solutions for vulnerability assessment. However, the deployment of large pre-trained models in real-world scenarios is hindered by their substantial computationa...

CVE-2025-7675

A maliciously crafted 3DM file, when parsed through certain Autodesk products, can force an Out-of-Bounds Write vulnerability. A malicious actor may leverage this vulnerability to cause a crash, cause data corruption, or execute arbitrary code in the context of the current process...

CVE-2025-5043

A maliciously crafted 3DM file, when linked or imported into certain Autodesk products, can force a Heap-Based Overflow vulnerability. A malicious actor can leverage this vulnerability to cause a crash, read sensitive data, or execute arbitrary code in the context of the current process...

CVE-2025-7675

A maliciously crafted 3DM file, when parsed through certain Autodesk products, can force an Out-of-Bounds Write vulnerability. A malicious actor may leverage this vulnerability to cause a crash, cause data corruption, or execute arbitrary code in the context of the current process...

CVE-2025-5043

A maliciously crafted 3DM file, when linked or imported into certain Autodesk products, can force a Heap-Based Overflow vulnerability. A malicious actor can leverage this vulnerability to cause a crash, read sensitive data, or execute arbitrary code in the context of the current process...

POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage

Microelectronic systems are widely used in many sensitive applications e.g., manufacturing, energy, defense. These systems increasingly handle sensitive data e.g., encryption key and are vulnerable to diverse threats, such as, power side-channel attacks, which infer sensitive data through dynamic...

Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems

The increasing digitization of smart grids has improved operational efficiency but also introduced new cybersecurity vulnerabilities, such as False Data Injection Attacks FDIAs targeting Automatic Generation Control AGC systems. While machine learning ML and deep learning DL models have shown...

Securing Cloud AI and LLMs with TotalAI for Visibility, Risk Context and Control

As enterprises accelerate AI adoption, large language models LLMs hosted on public cloud platforms are quickly becoming the norm due to their simplified access and pricing model. Cloud-native services like AWS Bedrock, Azure AI Foundry, and Google Vertex AI offer powerful, pay-as-you-go access to...

CVE-2025-54412

A flaw was found in skops. An inconsistency in OperatorFuncNode can hide the execution of untrusted operator methods when a specially crafted model file is loaded. This issue allows arbitrary code execution at load time...

Hot-Swap MarkBoard: an Efficient Black-Box Watermarking Approach for Large-Scale Model Distribution

Recently, Deep Learning DL models have been increasingly deployed on end-user devices as On-Device AI, offering improved efficiency and privacy. However, this deployment trend poses more serious Intellectual Property IP risks, as models are distributed on numerous local devices, making them...

Enhanced Deep Learning DeepFake Detection Integrating Handcrafted Features

The rapid advancement of deepfake and face swap technologies has raised significant concerns in digital security, particularly in identity verification and onboarding processes. Conventional detection methods often struggle to generalize against sophisticated facial manipulations. This study...

Enhancing Jailbreak Attacks on LLMs Via Persona Prompts

Jailbreak attacks aim to exploit large language models LLMs by inducing them to generate harmful content, thereby revealing their vulnerabilities. Understanding and addressing these attacks is crucial for advancing the field of LLM safety. Previous jailbreak approaches have mainly focused on dire...

CVE-2025-54412

skops is a Python library which helps users share and ship their scikit-learn based models. Versions 0.11.0 and below contain a inconsistency in the OperatorFuncNode which can be exploited to hide the execution of untrusted operator methods. This can then be used in a code reuse attack to invoke...