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...

Intrusion Detection in Heterogeneous Networks with Domain-Adaptive Multi-Modal Learning

Network Intrusion Detection Systems NIDS play a crucial role in safeguarding network infrastructure against cyberattacks. As the prevalence and sophistication of these attacks increase, machine learning and deep neural network approaches have emerged as effective tools for enhancing NIDS...

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...

When Good Sounds Go Adversarial: Jailbreaking Audio-Language Models with Benign Inputs

As large language models become increasingly integrated into daily life, audio has emerged as a key interface for human-AI interaction. However, this convenience also introduces new vulnerabilities, making audio a potential attack surface for adversaries. Our research introduces WhisperInject, a...

Simulating Cyberattacks through a Breach Attack Simulation (BAS) Platform Empowered by Security Chaos Engineering (SCE)

In today digital landscape, organizations face constantly evolving cyber threats, making it essential to discover slippery attack vectors through novel techniques like Security Chaos Engineering SCE, which allows teams to test defenses and identify vulnerabilities effectively. This paper proposes...

WiFinger: Fingerprinting Noisy IoT Event Traffic Using Packet-Level Sequence Matching

IoT environments such as smart homes are susceptible to privacy inference attacks, where attackers can analyze patterns of encrypted network traffic to infer the state of devices and even the activities of people. While most existing attacks exploit ML techniques for discovering such traffic...

Selection-Based Vulnerabilities: Clean-Label Backdoor Attacks in Active Learning

Active learningAL, which serves as the representative label-efficient learning paradigm, has been widely applied in resource-constrained scenarios. The achievement of AL is attributed to acquisition functions, which are designed for identifying the most important data to label. Despite this...

Reputation-Based Partition Scheme for IoT Security

With the popularity of smart terminals, such as the Internet of Things, crowdsensing is an emerging data aggregation paradigm, which plays a pivotal role in data-driven applications. There are some key issues in the development of crowdsensing such as platform security and privacy protection. As...

libxslt Key Data Storage Use-After-Free

libxslt suffers from a use-after-free vulnerability with key data stored cross-RVT...

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-To-Image Diffusion Models

In recent years,Diffusion models have achieved remarkable progress in the field of image generation.However,recent studies have shown that diffusion models are susceptible to backdoor attacks,in which attackers can manipulate the output by injecting covert triggers such as specific visual pattern...

ASTRA: Autonomous Spatial-Temporal Red-Teaming for AI Software Assistants

AI coding assistants like GitHub Copilot are rapidly transforming software development, but their safety remains deeply uncertain-especially in high-stakes domains like cybersecurity. Current red-teaming tools often rely on fixed benchmarks or unrealistic prompts, missing many real-world...

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...

Botan C++ Crypto Algorithms Library 3.9.0

Botan is a C++ library of cryptographic algorithms, including AES, DES, SHA-1, RSA, DSA, Diffie-Hellman, and many others. It also supports X.509 certificates and CRLs, and PKCS 10 certificate requests, and has a high level filter/pipe message processing system. The library is easily portable to...

BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS

In this paper, we endeavor to address the challenges of backdoor attacks countermeasures in black-box scenarios, thereby fortifying the security of inference under MLaaS. We first categorize backdoor triggers from a new perspective, i.e., their impact on the patched area, and divide them into:...

Anti-Tamper Protection for Unauthorized Individual Image Generation

With the advancement of personalized image generation technologies, concerns about forgery attacks that infringe on portrait rights and privacy are growing. To address these concerns, protection perturbation algorithms have been developed to disrupt forgery generation. However, the protection...

MalFlows: Context-Aware Fusion of Heterogeneous Flow Semantics for Android Malware Detection

Static analysis, a fundamental technique in Android app examination, enables the extraction of control flows, data flows, and inter-component communications ICCs, all of which are essential for malware detection. However, existing methods struggle to leverage the semantic complementarity across...

RX-INT: a Kernel Engine for Real-Time Detection and Analysis of In-Memory Threats

Malware and cheat developers use fileless execution techniques to evade traditional, signature-based security products. These methods include various types of manual mapping, module stomping, and threadless injection which work entirely within the address space of a legitimate process, presenting...

Smart Car Privacy: Survey of Attacks and Privacy Issues

Automobiles are becoming increasingly important in our day to day life. Modern automobiles are highly computerized and hence potentially vulnerable to attack. Providing many wireless connectivity for vehicles enables a bridge between vehicles and their external environments. Such a connected...

Swagger UI 1.0.3 Cross Site Scripting

Proof of concept cross site scripting exploit for Swagger UI versions 1.0.3 and below...

WordPress Alone Theme 7.8.3 Arbitrary Plugin Upload / Code Execution

WordPress Alone Theme versions 7.8.3 and below are vulnerable to an unauthenticated arbitrary file upload vulnerability. This flaw allows unauthenticated attackers to upload and install arbitrary plugin ZIP files from remote URLs via an unprotected AJAX endpoint — resulting in remote code executi...

SUAD: Solid-Channel Ultrasound Injection Attack and Defense to Voice Assistants

As a versatile AI application, voice assistants VAs have become increasingly popular, but are vulnerable to security threats. Attackers have proposed various inaudible attacks, but are limited by cost, distance, or LoS. Therefore, we propose \nameAttack, a long-range, cross-barrier, and...

WordPress Alone Theme 7.8.3 Arbitrary Plugin Upload

WordPress Alone Theme versions 7.8.3 and below suffer from an arbitrary plugin upload vulnerability...

WordPress Sala Theme 1.1.4 Privilege Escalation

WordPress Sala Theme versions 1.1.4 and below are vulnerable to an unauthenticated privilege escalation vulnerability. This flaw allows unauthenticated attackers to reset passwords of arbitrary users — including administrators — by directly invoking an exposed AJAX endpoint without verifying the...

PhishParrot: LLM-Driven Adaptive Crawling to Unveil Cloaked Phishing Sites

Phishing attacks continue to evolve, with cloaking techniques posing a significant challenge to detection efforts. Cloaking allows attackers to display phishing sites only to specific users while presenting legitimate pages to security crawlers, rendering traditional detection systems ineffective...

Real-World Evaluation of Protocol-Compliant Denial-Of-Service Attacks on C-V2X-Based Forward Collision Warning Systems

Cellular Vehicle-to-Everything C-V2X technology enables low-latency, reliable communications essential for safety applications such as a Forward Collision Warning FCW system. C-V2X deployments operate under strict protocol compliance with the 3rd Generation Partnership Project 3GPP and the Societ...

Whispering Agents: an Event-Driven Covert Communication Protocol for the Internet of Agents

The emergence of the Internet of Agents IoA introduces critical challenges for communication privacy in sensitive, high-stakes domains. While standard Agent-to-Agent A2A protocols secure message content, they are not designed to protect the act of communication itself, leaving agents vulnerable t...

Can LLMs Effectively Provide Game-Theoretic-Based Scenarios for Cybersecurity?

Game theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large Language Models LLMs offers new tools and challenges for the security of computer systems; In this work, we investiga...

ASINT: Learning AS-To-Organization Mapping from Internet Metadata

Accurately mapping Autonomous Systems ASNs to their owning or operating organizations underpins Internet measurement research and security applications. Yet existing approaches commonly rely solely on WHOIS or PeeringDB, missing important relationships e.g., cross-regional aliases, parent-child...

LPAR2RRD Remote Code Execution

This repository contains a proof of concept exploit for CVE-2025-54769, a vulnerability found in lpar2rrd. The vulnerability allows remote code execution and directory traversal by abusing the /lpar2rrd-cgi/upgrade.sh endpoint...

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...

Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems

As power systems evolve with increased integration of renewable energy sources, they become more complex and vulnerable to both cyber and physical threats. This study validates a centralized Dynamic State Estimation DSE algorithm designed to enhance the protection of power systems, particularly...

Hashcat Advanced Password Recovery 7.0.0 Binary Release

Hashcat is an advanced GPU hash cracking utility that includes the World's fastest md5crypt, phpass, mscash2 and WPA / WPA2 cracker. It also has the first and only GPGPU-based rule engine, focuses on highly iterated modern hashes, single dictionary-based attacks, and more. This is the binary...

Gandia Integra Total 4.4.2236.1 SQL Injection

Gandia Integra Total versions 2.1.2217.3 through 4.4.2236.1 suffer from a remote SQL injection vulnerability...

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...

DINA: a Dual Defense Framework against Internal Noise and External Attacks in Natural Language Processing

As large language models LLMs and generative AI become increasingly integrated into customer service and moderation applications, adversarial threats emerge from both external manipulations and internal label corruption. In this work, we identify and systematically address these dual adversarial...

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...

Towards Effective Offensive Security LLM Agents: Hyperparameter Tuning, LLM As a Judge, and a Lightweight CTF Benchmark

Recent advances in LLM agentic systems have improved the automation of offensive security tasks, particularly for Capture the Flag CTF challenges. We systematically investigate the key factors that drive agent success and provide a detailed recipe for building effective LLM-based offensive securi...

LMDG: Advancing Lateral Movement Detection through High-Fidelity Dataset Generation

Lateral Movement LM attacks continue to pose a significant threat to enterprise security, enabling adversaries to stealthily compromise critical assets. However, the development and evaluation of LM detection systems are impeded by the absence of realistic, well-labeled datasets. To address this...

Thwart Me If You Can: an Empirical Analysis of Android Platform Armoring against Stalkerware

Stalkerware is a serious threat to individuals' privacy that is receiving increased attention from the security and privacy research communities. Existing works have largely focused on studying leading stalkerware apps, dual-purpose apps, monetization of stalkerware, or the experience of survivor...

Copyparty 1.18.6 Cross Site Scripting

Copyparty versions 1.18.6 and below suffer from a cross site scripting vulnerability...

Microsoft Edge Information Disclosure

Microsoft Edge Chromium-based suffers from an information disclosure vulnerability...

Secure MmWave Beamforming with Proactive-ISAC Defense against Beam-Stealing Attacks

Millimeter-wave mmWave communication systems face increasing susceptibility to advanced beam-stealing attacks, posing a significant physical layer security threat. This paper introduces a novel framework employing an advanced Deep Reinforcement Learning DRL agent for proactive and adaptive defens...

Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools

Large language model LLM agents have demonstrated remarkable capabilities in complex reasoning and decision-making by leveraging external tools. However, this tool-centric paradigm introduces a previously underexplored attack surface: adversaries can manipulate tool metadata -- such as names,...

Experimental Evaluation of Post-Quantum Homomorphic Encryption for Privacy-Preserving V2X Communication

Intelligent Transportation Systems ITS fundamentally rely on vehicle-generated data for applications such as congestion monitoring and route optimization, making the preservation of user privacy a critical challenge. Homomorphic Encryption HE offers a promising solution by enabling computation on...

The Dark Side of Upgrades: Uncovering Security Risks in Smart Contract Upgrades

Smart contract upgrades are increasingly common due to their flexibility in modifying deployed contracts, such as fixing bugs or adding new functionalities. Meanwhile, upgrades compromise the immutability of contracts, introducing significant security concerns. While existing research has explore...

PentestJudge: Judging Agent Behavior against Operational Requirements

We introduce PentestJudge, a system for evaluating the operations of penetration testing agents. PentestJudge is a large language model LLM-as-judge with access to tools that allow it to consume arbitrary trajectories of agent states and tool call history to determine whether a security agent's...

PRIME: Plasticity-Robust Incremental Model for Encrypted Traffic Classification in Dynamic Network Environments

With the continuous development of network environments and technologies, ensuring cyber security and governance is increasingly challenging. Network traffic classificationETC can analyzes attributes such as application categories and malicious intent, supporting network management services like...

Beyond Vulnerabilities: a Survey of Adversarial Attacks As Both Threats and Defenses in Computer Vision Systems

Adversarial attacks against computer vision systems have emerged as a critical research area that challenges the fundamental assumptions about neural network robustness and security. This comprehensive survey examines the evolving landscape of adversarial techniques, revealing their dual nature a...

"Energon": Unveiling Transformers from GPU Power and Thermal Side-Channels

Transformers have become the backbone of many Machine Learning ML applications, including language translation, summarization, and computer vision. As these models are increasingly deployed in shared Graphics Processing Unit GPU environments via Machine Learning as a Service MLaaS, concerns aroun...

LLM-Assisted Model-Based Fuzzing of Protocol Implementations

Testing network protocol implementations is critical for ensuring the reliability, security, and interoperability of distributed systems. Faults in protocol behavior can lead to vulnerabilities and system failures, especially in real-time and mission-critical applications. A common approach to...