Learning to Look Benign: Targeted Evasion of Malware Detectors Via API Import Injection

Machine learning-based malware detectors are widely deployed in antivirus and endpoint detection systems, yet their reliance on static features makes them vulnerable to adversarial manipulation. This paper investigates whether a malware sample can be intentionally misclassified as a specific beni...

CVE-2025-57622

An issue in Step-Video-T2V allows a remote attacker to execute arbitrary code via the /vae-api , /caption-api , feature = pickle.loadsrequest.getdata component...

CVE-2025-57622

An issue in Step-Video-T2V allows a remote attacker to execute arbitrary code via the /vae-api , /caption-api , feature = pickle.loadsrequest.getdata component...

How the Graph Construction Technique Shapes Performance in IoT Botnet Detection

The increasing incidence of IoT-based botnet attacks has driven interest in advanced learning models for detection. Recent efforts have focused on leveraging attention mechanisms to model long-range feature dependencies and Graph Neural Networks GNNs to capture relationships between data instance...

Comparative Evaluation of VAE, GAN, and SMOTE for Tor Detection in Encrypted Network Traffic

Encrypted network traffic poses significant challenges for intrusion detection due to the lack of payload visibility, limited labeled datasets, and high class imbalance between benign and malicious activities. Traditional data augmentation methods struggle to preserve the complex temporal and...

PHANTOM: Progressive High-Fidelity Adversarial Network for Threat Object Modeling

The scarcity of cyberattack data hinders the development of robust intrusion detection systems. This paper introduces PHANTOM, a novel adversarial variational framework for generating high-fidelity synthetic attack data. Its innovations include progressive training, a dual-path VAE-GAN...

PT-2025-48585

Name of the Vulnerable Software and Affected Versions Tencent HunyuanVideo affected versions not specified Description A flaw exists within the load vae function that allows remote attackers to execute arbitrary code on affected installations of Tencent HunyuanVideo. The issue stems from a lack o...

Secure Low-Altitude Maritime Communications Via Intelligent Jamming

Low-altitude wireless networks LAWNs have emerged as a viable solution for maritime communications. In these maritime LAWNs, unmanned aerial vehicles UAVs serve as practical low-altitude platforms for wireless communications due to their flexibility and ease of deployment. However, the open and...

HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions

Software security testing, particularly when enhanced with deep learning models, has become a powerful approach for improving software quality, enabling faster detection of known flaws in source code. However, many approaches miss post-fix latent vulnerabilities that remain even after patches...

Security-Robustness Trade-Offs in Diffusion Steganography: A Comparative Analysis of Pixel-Space and VAE-Based Architectures

Current generative steganography research mainly pursues computationally expensive mappings to perfect Gaussian priors within single diffusion model architectures. This work introduces an efficient framework based on approximate Gaussian mapping governed by a scale factor calibrated through...

Collusion-Driven Impersonation Attack on Channel-Resistant RF Fingerprinting

Radio frequency fingerprint RFF is a promising device identification technology, with recent research shifting from robustness to security due to growing concerns over vulnerabilities. To date, while the security of RFF against basic spoofing such as MAC address tampering has been validated, its...

Designing with Deception: ML- and Covert Gate-Enhanced Camouflaging to Thwart IC Reverse Engineering

Integrated circuits ICs are essential to modern electronic systems, yet they face significant risks from physical reverse engineering RE attacks that compromise intellectual property IP and overall system security. While IC camouflage techniques have emerged to mitigate these risks, existing...

ARGOS: Anomaly Recognition and Guarding through O-RAN Sensing

Rogue Base Station RBS attacks, particularly those exploiting downgrade vulnerabilities, remain a persistent threat as 5G Standalone SA deployments are still limited and User Equipment UE manufacturers continue to support legacy network connectivity. This work introduces ARGOS, a comprehensive...

Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications

This work empirically evaluates machine learning models on two imbalanced public datasets KDDCUP99 and Credit Card Fraud 2013. The method includes data preparation, model training, and evaluation, using an 80/20 train/test split. Models tested include eXtreme Gradient Boosting XGB, Multi Layer...