REx86: A Local Large Language Model for Assisting in X86 Assembly Reverse Engineering

Reverse engineering RE of x86 binaries is indispensable for malware and firmware analysis, but remains slow due to stripped metadata and adversarial obfuscation. Large Language Models LLMs offer potential for improving RE efficiency through automated comprehension and commenting, but cloud-hosted...

On the Cybersecurity of LoRaWAN-Based System: A Smart-Lighting Case Study

Cyber-physical systems and the Internet of Things IoT are key technologies in the Industry 4.0 vision. They incorporate sensors and actuators to interact with the physical environment. However, when creating and interconnecting components to form a heterogeneous smart systems architecture, these...

Impacket 0.13.0

Impacket is a collection of Python classes for working with network protocols. Impacket is focused on providing low-level programmatic access to the packets and, for some protocols e.g. SMB1-3 and MSRPC, the protocol implementation itself. Packets can be constructed from scratch, as well as parse...

Lynis Auditing Tool 3.1.6

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...

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses

With the wide application of deep reinforcement learning DRL techniques in complex fields such as autonomous driving, intelligent manufacturing, and smart healthcare, how to improve its security and robustness in dynamic and changeable environments has become a core issue in current research...

Risk Psychology and Cyber-Attack Tactics

We examine whether measured cognitive processes predict cyber-attack behavior. We analyzed data that included psychometric scale responses and labeled attack behaviors from cybersecurity professionals who conducted red-team operations against a simulated enterprise network. We employed multilevel...

Beyond Text: Multimodal Jailbreaking of Vision-Language and Audio Models through Perceptually Simple Transformations

Multimodal large language models MLLMs have achieved remarkable progress, yet remain critically vulnerable to adversarial attacks that exploit weaknesses in cross-modal processing. We present a systematic study of multimodal jailbreaks targeting both vision-language and audio-language models,...

An Experimental Study of Trojan Vulnerabilities in UAV Autonomous Landing

This study investigates the vulnerabilities of autonomous navigation and landing systems in Urban Air Mobility UAM vehicles. Specifically, it focuses on Trojan attacks that target deep learning models, such as Convolutional Neural Networks CNNs. Trojan attacks work by embedding covert triggers...

Can You Trust What You See? Alpha Channel No-Box Attacks on Video Object Detection

As object detection models are increasingly deployed in cyber-physical systems such as autonomous vehicles AVs and surveillance platforms, ensuring their security against adversarial threats is essential. While prior work has explored adversarial attacks in the image domain, those attacks in the...

Ask What Your Country Can Do for You: Towards a Public Red Teaming Model

AI systems have the potential to produce both benefits and harms, but without rigorous and ongoing adversarial evaluation, AI actors will struggle to assess the breadth and magnitude of the AI risk surface. Researchers from the field of systems design have developed several effective sociotechnic...

Who Coordinates U.S. Cyber Defense? A Co-Authorship Network Analysis of Joint Cybersecurity Advisories (2024--2025)

Cyber threats increasingly demand joint responses, yet the organizational dynamics behind multi-agency cybersecurity collaboration remain poorly understood. Understanding who leads, who bridges, and how agencies coordinate is critical for strengthening both U.S. homeland security and allied defen...

Ultra-Fast Wireless Power Hacking

The rapid growth of electric vehicles EVs has driven the development of roadway wireless charging technology, effectively extending EV driving range. However, wireless charging introduces significant cybersecurity challenges. Any receiver within the magnetic field can potentially extract energy,...

GNUnet P2P Framework 0.25.2

GNUnet is a peer-to-peer framework with focus on providing security. All peer-to-peer messages in the network are confidential and authenticated. The framework provides a transport abstraction layer and can currently encapsulate the network traffic in UDP IPv4 and IPv6, TCP IPv4 and IPv6, HTTP, o...

Active Localization of Close-Range Adversarial Acoustic Sources for Underwater Data Center Surveillance

Underwater data infrastructures offer natural cooling and enhanced physical security compared to terrestrial facilities, but are susceptible to acoustic injection attacks that can disrupt data integrity and availability. This work presents a comprehensive surveillance framework for localizing and...

Separating Pseudorandom Generators from Logarithmic Pseudorandom States

Pseudorandom generators PRGs are a foundational primitive in classical cryptography, underpinning a wide range of constructions. In the quantum setting, pseudorandom quantum states PRSs were proposed as a potentially weaker assumption that might serve as a substitute for PRGs in cryptographic...

Exploring the Effect of DNN Depth on Adversarial Attacks in Network Intrusion Detection Systems

Adversarial attacks pose significant challenges to Machine Learning ML systems and especially Deep Neural Networks DNNs by subtly manipulating inputs to induce incorrect predictions. This paper investigates whether increasing the layer depth of deep neural networks affects their robustness agains...

FreeBSD Security Advisory - FreeBSD-SA-25:09.netinet

FreeBSD Security Advisory - Connected sockets are not intended to belong to load-balancing groups. However, the kernel failed to check the connection state of sockets when adding them to load-balancing groups. Furthermore, when looking up the destination socket for an incoming packet, the kernel...

Quantum Autoencoders for Anomaly Detection in Cybersecurity

Anomaly detection in cybersecurity is a challenging task, where normal events far outnumber anomalous ones with new anomalies occurring frequently. Classical autoencoders have been used for anomaly detection, but struggles in data-limited settings which quantum counterparts can potentially...

Everyone Needs AIR: An Agnostic Incident Reporting Framework for Cybersecurity in Operational Technology

Operational technology OT networks are increasingly coupled with information technology IT, expanding the attack surface and complicating incident response. Although OT standards emphasise incident reporting and evidence preservation, they do not specify what data to capture during an incident,...

Falco 0.42.0

Sysdig Falco is a behavioral activity monitoring agent that is open source and comes with native support for containers. Falco lets you define highly granular rules to check for activities involving file and network activity, process execution, IPC, and much more, using a flexible syntax. Falco...

LAPRAD: LLM-Assisted PRotocol Attack Discovery

With the goal of improving the security of Internet protocols, we seek faster, semi-automatic methods to discover new vulnerabilities in protocols such as DNS, BGP, and others. To this end, we introduce the LLM-Assisted Protocol Attack Discovery LAPRAD methodology, enabling security researchers...

QORE : Quantum Secure 5G/B5G Core

Quantum computing is reshaping the security landscape of modern telecommunications. The cryptographic foundations that secure todays 5G systems, including RSA, Elliptic Curve Cryptography ECC, and Diffie-Hellman DH, are all susceptible to attacks enabled by Shors algorithm. Protecting 5G networks...

Bytecode-Centric Detection of Known-To-Be-Vulnerable Dependencies in Java Projects

On average, 71% of the code in typical Java projects comes from open-source software OSS dependencies, making OSS dependencies the dominant component of modern software code bases. This high degree of OSS reliance comes with a considerable security risk of adding known security vulnerabilities to...

Sensing Security in Near-Field ISAC: Exploiting Scatterers for Eavesdropper Deception

In this paper, we explore sensing security in near-field NF integrated sensing and communication ISAC scenarios by exploiting known scatterers in the sensing scene. We propose a location deception LD scheme where scatterers are deliberately illuminated with probing power that is higher than that...

DRsam: Detection of Fault-Based Microarchitectural Side-Channel Attacks in RISC-V Using Statistical Preprocessing and Association Rule Mining

RISC-V processors are becoming ubiquitous in critical applications, but their susceptibility to microarchitectural side-channel attacks is a serious concern. Detection of microarchitectural attacks in RISC-V is an emerging research topic that is relatively underexplored, compared to x86 and ARM...

Evaluating Large Language Models in Detecting Secrets in Android Apps

Mobile apps often embed authentication secrets, such as API keys, tokens, and client IDs, to integrate with cloud services. However, developers often hardcode these credentials into Android apps, exposing them to extraction through reverse engineering. Once compromised, adversaries can exploit...

The Attribution Story of WhisperGate: An Academic Perspective

This paper explores the challenges of cyberattack attribution, specifically APTs, applying the case study approach for the WhisperGate cyber operation of January 2022 executed by the Russian military intelligence service GRU and targeting Ukrainian government entities. The study provides a detail...

Cyberattack Detection in Critical Infrastructure and Supply Chains

Cyberattack detection in Critical Infrastructure and Supply Chains has become challenging in Industry 4.0. Intrusion Detection Systems IDS are deployed to counter the cyberattacks. However, an IDS effectively detects attacks based on the known signatures and patterns, Zero-day attacks go...

The Trust Paradox in LLM-Based Multi-Agent Systems: When Collaboration Becomes a Security Vulnerability

Multi-agent systems powered by large language models are advancing rapidly, yet the tension between mutual trust and security remains underexplored. We introduce and empirically validate the Trust-Vulnerability Paradox TVP: increasing inter-agent trust to enhance coordination simultaneously expan...

HAMLOCK: HArdware-Model LOgically Combined AttacK

The growing use of third-party hardware accelerators e.g., FPGAs, ASICs for deep neural networks DNNs introduces new security vulnerabilities. Conventional model-level backdoor attacks, which only poison a model's weights to misclassify inputs with a specific trigger, are often detectable because...

Real-World Usability of Vulnerability Proof-Of-Concepts: A Comprehensive Study

The Proof-of-Concept PoC for a vulnerability is crucial in validating its existence, mitigating false positives, and illustrating the severity of the security threat it poses. However, research on PoCs significantly lags behind studies focusing on vulnerability data. This discrepancy can be...

Quantifying Security for Networked Control Systems: A Review

Networked Control Systems NCSs are integral in critical infrastructures such as power grids, transportation networks, and production systems. Ensuring the resilient operation of these large-scale NCSs against cyber-attacks is crucial for societal well-being. Over the past two decades, extensive...

Genesis: Evolving Attack Strategies for LLM Web Agent Red-Teaming

As large language model LLM agents increasingly automate complex web tasks, they boost productivity while simultaneously introducing new security risks. However, relevant studies on web agent attacks remain limited. Existing red-teaming approaches mainly rely on manually crafted attack strategies...

HarmNet: A Framework for Adaptive Multi-Turn Jailbreak Attacks on Large Language Models

Large Language Models LLMs remain vulnerable to multi-turn jailbreak attacks. We introduce HarmNet, a modular framework comprising ThoughtNet, a hierarchical semantic network; a feedback-driven Simulator for iterative query refinement; and a Network Traverser for real-time adaptive attack...

Forward to Hell? on the Potentials of Misusing Transparent DNS Forwarders in Reflective Amplification Attacks

The DNS infrastructure is infamous for facilitating reflective amplification attacks. Various countermeasures such as server shielding, access control, rate limiting, and protocol restrictions have been implemented. Still, the threat remains throughout the deployment of DNS servers. In this paper...

Censorship Chokepoints: New Battlegrounds for Regional Surveillance, Censorship and Influence on the Internet

Undoubtedly, the Internet has become one of the most important conduits to information for the general public. Nonetheless, Internet access can be and has been limited systematically or blocked completely during political events in numerous countries and regions by various censorship mechanisms...

Prompting the Priorities: A First Look at Evaluating LLMs for Vulnerability Triage and Prioritization

Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models LLMs offer a potential aid by automating parts of the interpretation process. We evaluate four models ChatGPT, Claude, Gemini, and DeepSeek across twelve prompting techniques to...

CLASP: Cost-Optimized LLM-Based Agentic System for Phishing Detection

Phishing websites remain a significant cybersecurity threat, necessitating accurate and cost-effective detection mechanisms. In this paper, we present CLASP, a novel system that effectively identifies phishing websites by leveraging multiple intelligent agents, built using large language models...

Securing IoT Communications Via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method

The rapid growth of the Internet of Things IoT has transformed industries by enabling seamless data exchange among connected devices. However, IoT networks remain vulnerable to security threats such as denial of service DoS attacks, anomalous traffic, and data manipulation due to decentralized...

RESCUE: Retrieval Augmented Secure Code Generation

Despite recent advances, Large Language Models LLMs still generate vulnerable code. Retrieval-Augmented Generation RAG has the potential to enhance LLMs for secure code generation by incorporating external security knowledge. However, the conventional RAG design struggles with the noise of raw...

Cybersecurity AI: Evaluating Agentic Cybersecurity in Attack/Defense CTFs

We empirically evaluate whether AI systems are more effective at attacking or defending in cybersecurity. Using CAI Cybersecurity AI's parallel execution framework, we deployed autonomous agents in 23 Attack/Defense CTF battlegrounds. Statistical analysis reveals defensive agents achieve 54.3%...

The Hidden Dangers of Public Serverless Repositories: An Empirical Security Assessment

Serverless computing has rapidly emerged as a prominent cloud paradigm, enabling developers to focus solely on application logic without the burden of managing servers or underlying infrastructure. Public serverless repositories have become key to accelerating the development of serverless...

CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks

Multimodal Large Language Models MLLMs achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak attacks. While existing work focuses on explicit attacks, where malicious content resides in a single modality, recent studies reveal implicit attacks, in which...

WhatWeb Scanner 0.6.3

WhatWeb is a next-generation web scanner. WhatWeb recognizes web technologies including content management systems CMS, blogging platforms, statistic/analytics packages, JavaScript libraries, web servers, and embedded devices. WhatWeb has over 1800 plugins, each to recognize something different...

BlueCodeAgent: A Blue Teaming Agent Enabled by Automated Red Teaming for CodeGen AI

As large language models LLMs are increasingly used for code generation, concerns over the security risks have grown substantially. Early research has primarily focused on red teaming, which aims to uncover and evaluate vulnerabilities and risks of CodeGen models. However, progress on the blue...

Exploiting the Potential of Linearity in Automatic Differentiation and Computational Cryptography

The concept of linearity plays a central role in both mathematics and computer science, with distinct yet complementary meanings. In mathematics, linearity underpins functions and vector spaces, forming the foundation of linear algebra and functional analysis. In computer science, it relates to...

Multimodal Safety Is Asymmetric: Cross-Modal Exploits Unlock Black-Box MLLMs Jailbreaks

Multimodal large language models MLLMs have demonstrated significant utility across diverse real-world applications. But MLLMs remain vulnerable to jailbreaks, where adversarial inputs can collapse their safety constraints and trigger unethical responses. In this work, we investigate jailbreaks i...

ThreatIntel-Andro: Expert-Verified Benchmarking for Robust Android Malware Research

The rapidly evolving Android malware ecosystem demands high-quality, real-time datasets as a foundation for effective detection and defense. With the widespread adoption of mobile devices across industrial systems, they have become a critical yet often overlooked attack surface in industrial...

BreakFun: Jailbreaking LLMs Via Schema Exploitation

The proficiency of Large Language Models LLMs in processing structured data and adhering to syntactic rules is a capability that drives their widespread adoption but also makes them paradoxically vulnerable. In this paper, we investigate this vulnerability through BreakFun, a jailbreak methodolog...

When AI Takes the Wheel: Security Analysis of Framework-Constrained Program Generation

In recent years, the AI wave has grown rapidly in software development. Even novice developers can now design and generate complex framework-constrained software systems based on their high-level requirements with the help of Large Language Models LLMs. However, when LLMs gradually "take the whee...