atjiu pybbs 6.0.0 Cross Site Scripting

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

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...

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...

Attack the Messages, Not the Agents: a Multi-Round Adaptive Stealthy Tampering Framework for LLM-MAS

Large language model-based multi-agent systems LLM-MAS effectively accomplish complex and dynamic tasks through inter-agent communication, but this reliance introduces substantial safety vulnerabilities. Existing attack methods targeting LLM-MAS either compromise agent internals or rely on direct...

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...

Lightweight Fault Detection Architecture for NTT on FPGA

Post-Quantum Cryptographic PQC algorithms are mathematically secure and resistant to quantum attacks but can still leak sensitive information in hardware implementations due to natural faults or intentional fault injections. The intent fault injection in side-channel attacks reduces the reliabili...

Linux 6.9 AF_UNIX MSG_OOB Handling Use-After-Free

Linux versions starting at 6.9 have a security bug in the handling of MSGOOB, which causes use-after-free read+write when a sequence of syscalls is executed...

Large Reasoning Models Are Autonomous Jailbreak Agents

Jailbreaking -- bypassing built-in safety mechanisms in AI models -- has traditionally required complex technical procedures or specialized human expertise. In this study, we show that the persuasive capabilities of large reasoning models LRMs simplify and scale jailbreaking, converting it into a...

A Survey on Data Security in Large Language Models

Large Language Models LLMs, now a foundation in advancing natural language processing, power applications such as text generation, machine translation, and conversational systems. Despite their transformative potential, these models inherently rely on massive amounts of training data, often...

Coward: toward Practical Proactive Federated Backdoor Defense Via Collision-Based Watermark

Backdoor detection is currently the mainstream defense against backdoor attacks in federated learning FL, where malicious clients upload poisoned updates that compromise the global model and undermine the reliability of FL deployments. Existing backdoor detection techniques fall into two...

A Survey on Privacy-Preserving Computing in the Automotive Domain

As vehicles become increasingly connected and autonomous, they accumulate and manage various personal data, thereby presenting a key challenge in preserving privacy during data sharing and processing. This survey reviews applications of Secure Multi-Party Computation MPC and Homomorphic Encryptio...

GPU in the Blind Spot: Overlooked Security Risks in Transportation

Graphics processing units GPUs are becoming an essential part of the intelligent transportation system ITS for enabling video-based and artificial intelligence AI based applications. GPUs provide high-throughput and energy-efficient computing for tasks like sensor fusion and roadside video...

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...

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...

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...

Lynis Auditing Tool 3.1.5

Lynis is an auditing tool for Unix specialists. It scans the system and available software to detect security issues. Beside security related information it will also scan for general system information, installed packages and configuration mistakes. This software aims in assisting automated...

Optimal Planning for Enhancing the Resilience of Modern Distribution Systems against Cyberattacks

The increasing integration of IoT-connected devices in smart grids has introduced new vulnerabilities at the distribution level. Of particular concern is the potential for cyberattacks that exploit high-wattage IoT devices, such as EV chargers, to manipulate local demand and destabilize the grid...

Characterizing the Sensitivity to Individual Bit Flips in Client-Side Operations of the CKKS Scheme

Homomorphic Encryption HE enables computation on encrypted data without decryption, making it a cornerstone of privacy-preserving computation in untrusted environments. As HE sees growing adoption in sensitive applications such as secure machine learning and confidential data analysis ensuring it...

Testbed and Software Architecture for Enhancing Security in Industrial Private 5G Networks

In the era of Industry 4.0, the growing need for secure and efficient communication systems has driven the development of fifth-generation 5G networks characterized by extremely low latency, massive device connectivity and high data transfer speeds. However, the deployment of 5G networks presents...

Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy

This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks QNNs in the Noisy Intermediate-Scale Quantum NISQ era. In this paper, we present an integrated framework that leverages and combines existing approaches to enhance...

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...

Cryptographic Data Exchange for Nuclear Warheads

Nuclear arms control treaties have historically focused on strategic nuclear delivery systems, leaving nuclear warheads outside formal verification frameworks. This paper presents a cryptographic protocol for secure and verifiable warhead tracking, addressing challenges in nuclear warhead...

KD-GAT: Combining Knowledge Distillation and Graph Attention Transformer for a Controller Area Network Intrusion Detection System

The Controller Area Network CAN protocol is widely adopted for in-vehicle communication but lacks inherent security mechanisms, making it vulnerable to cyberattacks. This paper introduces KD-GAT, an intrusion detection framework that combines Graph Attention Networks GATs with knowledge...

Transcript Franking for Encrypted Messaging

Message franking is an indispensable abuse mitigation tool for end-to-end encrypted E2EE messaging platforms. With it, users who receive harmful content can securely report that content to platform moderators. However, while real-world deployments of reporting require the disclosure of multiple...

OneShield -- the Next Generation of LLM Guardrails

The rise of Large Language Models has created a general excitement about the great potential for a myriad of applications. While LLMs offer many possibilities, questions about safety, privacy, and ethics have emerged, and all the key actors are working to address these issues with protective...

On the Security of a Code-Based PIR Scheme

Private Information Retrieval PIR schemes allow clients to retrieve files from a database without disclosing the requested file's identity to the server. In the pursuit of post-quantum security, most recent PIR schemes rely on hard lattice problems. In contrast, the so called CB-cPIR scheme stand...

LLM Meets the Sky: Heuristic Multi-Agent Reinforcement Learning for Secure Heterogeneous UAV Networks

This work tackles the physical layer security PLS problem of maximizing the secrecy rate in heterogeneous UAV networks HetUAVNs under propulsion energy constraints. Unlike prior studies that assume uniform UAV capabilities or overlook energy-security trade-offs, we consider a realistic scenario...

PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python

Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting...

Performance Evaluation and Threat Mitigation in Large-Scale 5G Core Deployment

The deployment of large-scale software-based 5G core functions presents significant challenges due to their reliance on optimized and intelligent resource provisioning for their services. Many studies have focused on analyzing the impact of resource allocation for complex deployments using...

WaveVerify: a Novel Audio Watermarking Framework for Media Authentication and Combatting Deepfakes

The rapid advancement of voice generation technologies has enabled the synthesis of speech that is perceptually indistinguishable from genuine human voices. While these innovations facilitate beneficial applications such as personalized text-to-speech systems and voice preservation, they have als...

From Cracks to Crooks: YouTube As a Vector for Malware Distribution

With billions of users and an immense volume of daily uploads, YouTube has become an attractive target for cybercriminals aiming to leverage its vast audience. The platform's openness and trustworthiness provide an ideal environment for deceptive campaigns that can operate under the radar of...

LLM4MEA: Data-Free Model Extraction Attacks on Sequential Recommenders Via Large Language Models

Recent studies have demonstrated the vulnerability of sequential recommender systems to Model Extraction Attacks MEAs. MEAs collect responses from recommender systems to replicate their functionality, enabling unauthorized deployments and posing critical privacy and security risks. Black-box...

QSAF: a Novel Mitigation Framework for Cognitive Degradation in Agentic AI

We introduce Cognitive Degradation as a novel vulnerability class in agentic AI systems. Unlike traditional adversarial external threats such as prompt injection, these failures originate internally, arising from memory starvation, planner recursion, context flooding, and output suppression. Thes...

ChatGPTUtil Cross Site Scripting

ChatGPTUtil is an AI-powered chatbot assistant, providing access to both ChatGPT and an AI image generator. A self cross site scripting vulnerability exists in the chat component. This can lead to cookie theft leading to remote account hijacking...

Metaverse Security and Privacy Research: a Systematic Review

The rapid growth of metaverse technologies, including virtual worlds, augmented reality, and lifelogging, has accelerated their adoption across diverse domains. This rise exposes users to significant new security and privacy challenges due to sociotechnical complexity, pervasive connectivity, and...

Exploiting Jailbreaking Vulnerabilities in Generative AI to Bypass Ethical Safeguards for Facilitating Phishing Attacks

The advent of advanced Generative AI GenAI models such as DeepSeek and ChatGPT has significantly reshaped the cybersecurity landscape, introducing both promising opportunities and critical risks. This study investigates how GenAI powered chatbot services can be exploited via jailbreaking techniqu...

DNN Unicode Path Normalization NTLM Hash Disclosure

This exploit targets a vulnerability in DNN formerly DotNetNuke versions 6.0.0 to before 10.0.1 that allows attackers to disclose NTLM hashes through Unicode path normalization attacks...

Differentially Private Federated Low Rank Adaptation beyond Fixed-Matrix

Large language models LLMs typically require fine-tuning for domain-specific tasks, and LoRA offers a computationally efficient approach by training low-rank adapters. LoRA is also communication-efficient for federated LLMs when multiple users collaboratively fine-tune a global LLM model without...

DESIGN: Encrypted GNN Inference Via Server-Side Input Graph Pruning

Graph Neural Networks GNNs have achieved state-of-the-art performance in various graph-based learning tasks. However, enabling privacy-preserving GNNs in encrypted domains, such as under Fully Homomorphic Encryption FHE, typically incurs substantial computational overhead, rendering real-time and...

LLMalMorph: on the Feasibility of Generating Variant Malware Using Large-Language-Models

Large Language Models LLMs have transformed software development and automated code generation. Motivated by these advancements, this paper explores the feasibility of LLMs in modifying malware source code to generate variants. We introduce LLMalMorph, a semi-automated framework that leverages...

CLIProv: a Contrastive Log-To-Intelligence Multimodal Approach for Threat Detection and Provenance Analysis

With the increasing complexity of cyberattacks, the proactive and forward-looking nature of threat intelligence has become more crucial for threat detection and provenance analysis. However, translating high-level attack patterns described in Tactics, Techniques, and Procedures TTP intelligence...

ARPaCCino: an Agentic-RAG for Policy As Code Compliance

Policy as Code PaC is a paradigm that encodes security and compliance policies into machine-readable formats, enabling automated enforcement in Infrastructure as Code IaC environments. However, its adoption is hindered by the complexity of policy languages and the risk of misconfigurations. In th...

Phishing Detection in the Gen-AI Era: Quantized LLMs Vs Classical Models

Phishing attacks are becoming increasingly sophisticated, underscoring the need for detection systems that strike a balance between high accuracy and computational efficiency. This paper presents a comparative evaluation of traditional Machine Learning ML, Deep Learning DL, and quantized...

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks

This paper presents a novel approach to intrusion detection by integrating traditional signature-based methods with the contextual understanding capabilities of the GPT-2 Large Language Model LLM. As cyber threats become increasingly sophisticated, particularly in distributed, heterogeneous, and...

libxslt xmlNode.psvi Type Confusion

libxslt suffers from a type confusion vulnerability in xmlNode.psvi between stylesheet and source nodes...

On the Impossibility of Separating Intelligence from Judgment: the Computational Intractability of Filtering for AI Alignment

With the increased deployment of large language models LLMs, one concern is their potential misuse for generating harmful content. Our work studies the alignment challenge, with a focus on filters to prevent the generation of unsafe information. Two natural points of intervention are the filterin...

Enter, Exit, Page Fault, Leak: Testing Isolation Boundaries for Microarchitectural Leaks

CPUs provide isolation mechanisms like virtualization and privilege levels to protect software. Yet these focus on architectural isolation while typically overlooking microarchitectural side channels, exemplified by Meltdown and Foreshadow. Software must therefore supplement architectural defense...

TuneShield: Mitigating Toxicity in Conversational AI While Fine-Tuning on Untrusted Data

Recent advances in foundation models, such as LLMs, have revolutionized conversational AI. Chatbots are increasingly being developed by customizing LLMs on specific conversational datasets. However, mitigating toxicity during this customization, especially when dealing with untrusted training dat...

TELSAFE: Security Gap Quantitative Risk Assessment Framework

Gaps between established security standards and their practical implementation have the potential to introduce vulnerabilities, possibly exposing them to security risks. To effectively address and mitigate these security and compliance challenges, security risk management strategies are essential...

A Novel APVD Steganography Technique Incorporating Pseudorandom Pixel Selection for Robust Image Security

Steganography is the process of embedding secret information discreetly within a carrier, ensuring secure exchange of confidential data. The Adaptive Pixel Value Differencing APVD steganography method, while effective, encounters certain challenges like the "unused blocks" issue. This problem can...