WordPress Backup Migration 1.3.7 Remote Code Execution

The Backup Migration plugin for WordPress is vulnerable to remote Code execution in all versions up to, and including, 1.3.7 via the /includes/backup-heart.php file. An attacker can control the values passed to an include statement, leveraging that to achieve remote code execution. This...

Membership Inference Attack with Partial Features

Machine learning models have been shown to be susceptible to membership inference attack, which can be used to determine whether a given sample appears in the training data. Existing membership inference methods commonly assume that the adversary has full access to the features of the target...

Tigo Energy CCA Command Injection

This repository contains a proof of concept exploit exploit for CVE‑2025‑7769, a critical remote command injection vulnerability found in Tigo Energy CCA appliances exposing the /cgi-bin/mobileapi endpoint...

PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction

Redacting Personally Identifiable Information PII from unstructured text is critical for ensuring data privacy in regulated domains. While earlier approaches have relied on rule-based systems and domain-specific Named Entity Recognition NER models, these methods fail to generalize across formats...

Secure and Practical Quantum Digital Signatures

Digital signatures represent a crucial cryptographic asset that must be protected against quantum adversaries. Quantum Digital Signatures QDS can offer solutions that are information-theoretically IT secure and thus immune to quantum attacks. In this work, we analyze three existing practical QDS...

An Overview of 7726 User Reports: Uncovering SMS Scams and Scammer Strategies

Mobile network operators implement firewalls to stop illicit messages, but scammers find ways to evade detection. Previous work has looked into SMS texts that are blocked by these firewalls. However, there is little insight into SMS texts that bypass them and reach users. To this end, we...

Efficient Mediated Multiparty Semi-Quantum Secret Sharing Protocol Based on Single-Qubit Reordering

Typical multiparty semi-quantum secret sharing MSQSS protocols require the dealer to possess full quantum capabilities, while the classical users usually need to perform three operations. To address this practical limitation, this paper introduces a new mediated MSQSS protocol that enables Alice,...

RL-MoE: an Image-Based Privacy Preserving Approach in Intelligent Transportation System

The proliferation of AI-powered cameras in Intelligent Transportation Systems ITS creates a severe conflict between the need for rich visual data and the fundamental right to privacy. Existing privacy-preserving mechanisms, such as blurring or encryption, are often insufficient, creating an...

Non-Omniscient Backdoor Injection with a Single Poison Sample: Proving the One-Poison Hypothesis for Linear Regression and Linear Classification

Backdoor injection attacks are a threat to machine learning models that are trained on large data collected from untrusted sources; these attacks enable attackers to inject malicious behavior into the model that can be triggered by specially crafted inputs. Prior work has established bounds on th...

Optimizing IoT Threat Detection with Kolmogorov-Arnold Networks (KANs)

The exponential growth of the Internet of Things IoT has led to the emergence of substantial security concerns, with IoT networks becoming the primary target for cyberattacks. This study examines the potential of Kolmogorov-Arnold Networks KANs as an alternative to conventional machine learning...

Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucination

Timely and effective incident response is key to managing the growing frequency of cyberattacks. However, identifying the right response actions for complex systems is a major technical challenge. A promising approach to mitigate this challenge is to use the security knowledge embedded in large...

Semi-Supervised Supply Chain Fraud Detection with Unsupervised Pre-Filtering

Detecting fraud in modern supply chains is a growing challenge, driven by the complexity of global networks and the scarcity of labeled data. Traditional detection methods often struggle with class imbalance and limited supervision, reducing their effectiveness in real-world applications. This...

Secure Quantum Key Distribution Via Entangled Quantum Walkers

Quantum Key Distribution QKD is an emerging cryptographic method designed for secure key sharing. Its security is theoretically guaranteed by fundamental principles of quantum mechanics, making it a leading candidate for future communication protocols. Quantum Random Walks QRWs, on the other hand...

A Comparative Performance Evaluation of Kyber, Sntrup761, and FrodoKEM for Post-Quantum Cryptography

Post-quantum cryptography PQC aims to develop cryptographic algorithms that are secure against attacks from quantum computers. This paper compares the leading postquantum cryptographic algorithms, such as Kyber, sntrup761, and FrodoKEM, in terms of their security, performance, and real-world...

System Security Framework for 5G Advanced /6G IoT Integrated Terrestrial Network-Non-Terrestrial Network (TN-NTN) with AI-Enabled Cloud Security

The integration of Terrestrial Networks TN and Non-Terrestrial Networks NTN, including 5G Advanced/6G and the Internet of Things IoT technologies, using Low Earth Orbit LEO satellites, high-altitude platforms HAPS, and Unmanned Aerial Vehicles UAVs, is redefining the landscape of global...

Exploring Satellite Quantum Key Distribution under Atmospheric Constraints

Satellite Quantum Key Distribution creates a pathway for secure global communication with a level of security that is peerless. However, ground-to-satellite Quantum Key Distribution links are degraded due to the atmospheric turbulence. This paper gives a numerical framework using angular spectrum...

Quantum Circuit Benchmarking on IBM Brisbane: Performance Insights from Superconducting Qubit Models

This paper investigates quantum communication using superconducting qubits, emphasizing the simulation and control of quantum systems via IBM Brisbane quantum processor. We focus on implementing fundamental quantum gates and analyzing the evolution of entangled states, which are essential for...

Enhancing Software Vulnerability Detection through Adaptive Test Input Generation Using Genetic Algorithm

Software vulnerabilities continue to undermine the reliability and security of modern systems, particularly as software complexity outpaces the capabilities of traditional detection methods. This study introduces a genetic algorithm-based method for test input generation that innovatively...

Performance and Storage Analysis of CRYSTALS Kyber As a Post Quantum Replacement for RSA and ECC

The steady advancement in quantum computer error correction technology has pushed the current record to 48 stable logical qubits, bringing us closer to machines capable of running Shor's algorithm at scales that threaten RSA and ECC cryptography. While the timeline for developing such quantum...

AuthPrint: Fingerprinting Generative Models against Malicious Model Providers

Generative models are increasingly adopted in high-stakes domains, yet current deployments offer no mechanisms to verify the origin of model outputs. We address this gap by extending model fingerprinting techniques beyond the traditional collaborative setting to one where the model provider may a...

Multi-Stage Knowledge-Distilled VGAE and GAT for Robust Controller-Area-Network Intrusion Detection

The Controller Area Network CAN protocol is a standard for in-vehicle communication but remains susceptible to cyber-attacks due to its lack of built-in security. This paper presents a multi-stage intrusion detection framework leveraging unsupervised anomaly detection and supervised graph learnin...

From Learning to Unlearning: Biomedical Security Protection in Multimodal Large Language Models

The security of biomedical Multimodal Large Language Models MLLMs has attracted increasing attention. However, training samples easily contain private information and incorrect knowledge that are difficult to detect, potentially leading to privacy leakage or erroneous outputs after deployment. An...

SelectiveShield: Lightweight Hybrid Defense against Gradient Leakage in Federated Learning

Federated Learning FL enables collaborative model training on decentralized data but remains vulnerable to gradient leakage attacks that can reconstruct sensitive user information. Existing defense mechanisms, such as differential privacy DP and homomorphic encryption HE, often introduce a...

Policy Design in Zero-Trust Distributed Networks: Challenges and Solutions

Traditional security architectures are becoming more vulnerable to distributed attacks due to significant dependence on trust. This will further escalate when implementing agentic AI within the systems, as more components must be secured over a similar distributed space. These scenarios can be...

Secure Development of a Hooking-Based Deception Framework against Keylogging Techniques

Keyloggers remain a serious threat in modern cybersecurity, silently capturing user keystrokes to steal credentials and sensitive information. Traditional defenses focus mainly on detection and removal, which can halt malicious activity but do little to engage or mislead adversaries. In this pape...

From Split to Share: Private Inference with Distributed Feature Sharing

Cloud-based Machine Learning as a Service MLaaS raises serious privacy concerns when handling sensitive client data. Existing Private Inference PI methods face a fundamental trade-off between privacy and efficiency: cryptographic approaches offer strong protection but incur high computational...

Measuring the Carbon Footprint of Cryptographic Privacy-Enhancing Technologies

Privacy-enhancing technologies PETs have attracted significant attention in response to privacy regulations, driving the development of applications that prioritize user data protection. At the same time, the information and communication technology ICT sector faces growing pressure to reduce its...

SenseCrypt: Sensitivity-Guided Selective Homomorphic Encryption for Joint Federated Learning in Cross-Device Scenarios

Homomorphic Encryption HE prevails in securing Federated Learning FL, but suffers from high overhead and adaptation cost. Selective HE methods, which partially encrypt model parameters by a global mask, are expected to protect privacy with reduced overhead and easy adaptation. However, in...

atjiu pybbs 6.0.0 Cross Site Scripting

atjiu pybbs versions 6.0.0 and below suffer from a cross site scripting vulnerability...

Drone Detection with Event Cameras

The diffusion of drones presents significant security and safety challenges. Traditional surveillance systems, particularly conventional frame-based cameras, struggle to reliably detect these targets due to their small size, high agility, and the resulting motion blur and poor performance in...

Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems

This work focuses on validation of attack pattern mining in the context of Industrial Control System ICS security. A comprehensive security assessment of an ICS requires generating a large and variety of attack patterns. For this purpose we have proposed a data driven technique to generate attack...

SVC 2025: the First Multimodal Deception Detection Challenge

Deception detection is a critical task in real-world applications such as security screening, fraud prevention, and credibility assessment. While deep learning methods have shown promise in surpassing human-level performance, their effectiveness often depends on the availability of high-quality a...

Cybersecurity of Quantum Key Distribution Implementations

Practical implementations of Quantum Key Distribution QKD often deviate from the theoretical protocols, exposing the implementations to various attacks even when the underlying ideal protocol is proven secure. We present new analysis tools and methodologies for quantum cybersecurity, adapting the...

Log2Sig: Frequency-Aware Insider Threat Detection Via Multivariate Behavioral Signal Decomposition

Insider threat detection presents a significant challenge due to the deceptive nature of malicious behaviors, which often resemble legitimate user operations. However, existing approaches typically model system logs as flat event sequences, thereby failing to capture the inherent frequency dynami...

Leveraging Large Language Models for SQL Behavior-Based Database Intrusion Detection

Database systems are extensively used to store critical data across various domains. However, the frequency of abnormal database access behaviors, such as database intrusion by internal and external attacks, continues to rise. Internal masqueraders often have greater organizational knowledge,...

MambaITD: an Efficient Cross-Modal Mamba Network for Insider Threat Detection

Enterprises are facing increasing risks of insider threats, while existing detection methods are unable to effectively address these challenges due to reasons such as insufficient temporal dynamic feature modeling, computational efficiency and real-time bottlenecks and cross-modal information...

Multilingual Source Tracing of Speech Deepfakes: a First Benchmark

Recent progress in generative AI has made it increasingly easy to create natural-sounding deepfake speech from just a few seconds of audio. While these tools support helpful applications, they also raise serious concerns by making it possible to generate convincing fake speech in many languages...

Writebot AI Content Generator SaaS React Template 4.0.0 Shell Upload

Writebot AI Content Generator SaaS React Template versions 4.0.0 and below suffer from a remote shell upload vulnerability...

Per-Element Secure Aggregation against Data Reconstruction Attacks in Federated Learning

Federated learning FL enables collaborative model training without sharing raw data, but individual model updates may still leak sensitive information. Secure aggregation SecAgg mitigates this risk by allowing the server to access only the sum of client updates, thereby concealing individual...

Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals

Cyber attacks continue to be a cause of concern despite advances in cyber defense techniques. Although cyber attacks cannot be fully prevented, standard decision-making frameworks typically focus on how to prevent them from succeeding, without considering the cost of cleaning up the damages...

Isolate Trigger: Detecting and Eradicating Evade-Adaptive Backdoors

All current detection of backdoor attacks on deep learning models fall under the category of a non essential featuresNEF, which focus on fighting against simple and efficient vertical class backdoor -- trigger is small, few and not overlapping with the source. Evade-adaptive backdoor EAB attacks...

Evaluating Selective Encryption against Gradient Inversion Attacks

Gradient inversion attacks pose significant privacy threats to distributed training frameworks such as federated learning, enabling malicious parties to reconstruct sensitive local training data from gradient communications between clients and an aggregation server during the aggregation process...

Eavesdropping Risk in Terahertz Channels by Covered Wavy Surfaces

Terahertz communications offer unprecedented data rates for next-generation wireless networks but suffer blockage susceptibility that restrict coverage and introduce physical-layer security vulnerabilities. Non-line-of-sight relay schemes using metallic wavy surfaces MWS address coverage...

Large Language Models Versus Static Code Analysis Tools: a Systematic Benchmark for Vulnerability Detection

Modern software relies on a multitude of automated testing and quality assurance tools to prevent errors, bugs and potential vulnerabilities. This study sets out to provide a head-to-head, quantitative and qualitative evaluation of six automated approaches: three industry-standard rule-based stat...

Privacy Risk Predictions Based on Fundamental Understanding of Personal Data and an Evolving Threat Landscape

It is difficult for individuals and organizations to protect personal information without a fundamental understanding of relative privacy risks. By analyzing over 5,000 empirical identity theft and fraud cases, this research identifies which types of personal data are exposed, how frequently...

Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy

Large Language Models LLMs are gaining traction as a method to generate consensus statements and aggregate preferences in digital democracy experiments. Yet, LLMs may introduce critical vulnerabilities in these systems. Here, we explore the impact of prompt-injection attacks targeting consensus...

FlashVault: Versatile In-NAND Self-Encryption with Zero Area Overhead

We present FlashVault, an in-NAND self-encryption architecture that embeds a reconfigurable cryptographic engine into the unused silicon area of a state-of-the-art 4D V-NAND structure. FlashVault supports not only block ciphers for data encryption but also public-key and post-quantum algorithms f...

Evaluating Software Supply Chain Security in Research Software

The security of research software is essential for ensuring the integrity and reproducibility of scientific results. However, research software security is still largely unexplored. Due to its dependence on open source components and distributed development practices, research software is...

From Legacy to Standard: LLM-Assisted Transformation of Cybersecurity Playbooks into CACAO Format

Existing cybersecurity playbooks are often written in heterogeneous, non-machine-readable formats, which limits their automation and interoperability across Security Orchestration, Automation, and Response platforms. This paper explores the suitability of Large Language Models, combined with Prom...

Bidirectional TLS Handshake Caching for Constrained Industrial IoT Scenarios

While TLS has become the de-facto standard for end-to-end security, its use to secure critical communication in evolving industrial IoT scenarios is severely limited by prevalent resource constraints of devices and networks. Most notably, the TLS handshake to establish secure connections incurs...