ENJ: Optimizing Noise with Genetic Algorithms to Jailbreak LSMs

The widespread application of Large Speech Models LSMs has made their security risks increasingly prominent. Traditional speech adversarial attack methods face challenges in balancing effectiveness and stealth. This paper proposes Evolutionary Noise Jailbreak ENJ, which utilizes a genetic algorit...

ODoQ: Oblivious DNS-Over-QUIC

The Domain Name System DNS, which converts domain names to their respective IP addresses, has advanced enhancements aimed at safeguarding DNS data and users' identity from attackers. The recent privacy-focused advancements have enabled the IETF to standardize several protocols. Nevertheless, thes...

Realistic Environmental Injection Attacks on GUI Agents

GUI agents built on LVLMs are increasingly used to interact with websites. However, their exposure to open-world content makes them vulnerable to Environmental Injection Attacks EIAs that hijack agent behavior via webpage elements. Many recent studies assume the attacker to be a regular user who...

From Firewalls to Frontiers: AI Red-Teaming Is a Domain-Specific Evolution of Cyber Red-Teaming

A red team simulates adversary attacks to help defenders find effective strategies to defend their systems in a real-world operational setting. As more enterprise systems adopt AI, red-teaming will need to evolve to address the unique vulnerabilities and risks posed by AI systems. We take the...

Weakly Supervised Vulnerability Localization Via Multiple Instance Learning

Software vulnerability detection has emerged as a significant concern in the field of software security recently, capturing the attention of numerous researchers and developers. Most previous approaches focus on coarse-grained vulnerability detection, such as at the function or file level. Howeve...

Securing AI Agents: Implementing Role-Based Access Control for Industrial Applications

The emergence of Large Language Models LLMs has significantly advanced solutions across various domains, from political science to software development. However, these models are constrained by their training data, which is static and limited to information available up to a specific date...

VulAgent: Hypothesis-Validation Based Multi-Agent Vulnerability Detection

The application of language models to project-level vulnerability detection remains challenging, owing to the dual requirement of accurately localizing security-sensitive code and correctly correlating and reasoning over complex program context. We present VulAgent, a multi-agent vulnerability...

TPSQLi: Test Prioritization for SQL Injection Vulnerability Detection in Web Applications

The rapid proliferation of network applications has led to a significant increase in network attacks. According to the OWASP Top 10 Projects report released in 2021, injection attacks rank among the top three vulnerabilities in software projects. This growing threat landscape has increased the...

A Comparison of Selected Image Transformation Techniques for Malware Classification

Recently, a considerable amount of malware research has focused on the use of powerful image-based machine learning techniques, which generally yield impressive results. However, before image-based techniques can be applied to malware, the samples must be converted to images, and there is no...

Finding SSH Strict Key Exchange Violations by State Learning

SSH is an important protocol for secure remote shell access to servers on the Internet. At USENIX 2024, B�umer et al. presented the Terrapin attack on SSH, which relies on the attacker injecting optional messages during the key exchange. To mitigate this attack, SSH vendors adopted an extension...

Large Language Models for Security Operations Centers: a Comprehensive Survey

Large Language Models LLMs have emerged as powerful tools capable of understanding and generating human-like text, offering transformative potential across diverse domains. The Security Operations Center SOC, responsible for safeguarding digital infrastructure, represents one of these domains. SO...

Side-Channel Inference of User Activities in AR/VR Using GPU Profiling

Over the past decade, AR/VR devices have drastically changed how we interact with the digital world. Users often share sensitive information, such as their location, browsing history, and even financial data, within third-party apps installed on these devices, assuming a secure environment...

URL2Graph++: Unified Semantic-Structural-Character Learning for Malicious URL Detection

Malicious URL detection remains a major challenge in cybersecurity, primarily due to two factors: 1 the exponential growth of the Internet has led to an immense diversity of URLs, making generalized detection increasingly difficult; and 2 attackers are increasingly employing sophisticated...

Automated Testing of Broken Authentication Vulnerabilities in Web APIs with AuthREST

We present AuthREST, an open-source security testing tool targeting broken authentication, one of the most prevalent API security risks in the wild. AuthREST automatically tests web APIs for credential stuffing, password brute forcing, and unchecked token authenticity. Empirical results show that...

Feature-Centric Approaches to Android Malware Analysis: a Survey

Sophisticated malware families exploit the openness of the Android platform to infiltrate IoT networks, enabling large-scale disruption, data exfiltration, and denial-of-service attacks. This systematic literature review SLR examines cutting-edge approaches to Android malware analysis with direct...

Five Minutes of DDoS Brings Down Tor: DDoS Attacks on the Tor Directory Protocol and Mitigations

The Tor network offers network anonymity to its users by routing their traffic through a sequence of relays. A group of nine directory authorities maintains information about all available relay nodes using a distributed directory protocol. We observe that the current protocol makes a steep...

A Cyber-Twin Based Honeypot for Gathering Threat Intelligence

Critical Infrastructure CI is prone to cyberattacks. Several techniques have been developed to protect CI against such attacks. In this work, we describe a honeypot based on a cyber twin for a water treatment plant. The honeypot is intended to serve as a realistic replica of a water treatment pla...

PARROT: Portable Android Reproducible Traffic Observation Tool

The rapid evolution of mobile security protocols and limited availability of current datasets constrains research in app traffic analysis. This paper presents PARROT, a reproducible and portable traffic capture system for systematic app traffic collection using Android Virtual Devices. The system...

Bridging the Gap in Phishing Detection: a Comprehensive Phishing Dataset Collector

To combat phishing attacks -- aimed at luring web users to divulge their sensitive information -- various phishing detection approaches have been proposed. As attackers focus on devising new tactics to bypass existing detection solutions, researchers have adapted by integrating machine learning a...

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection

The application layer of Bluetooth Low Energy BLE is a growing source of security vulnerabilities, as developers often neglect to implement critical protections such as encryption, authentication, and freshness. While formal verification offers a principled way to check these properties, the manu...

CryptoGuard: an AI-Based Cryptojacking Detection Dashboard Prototype

With the widespread adoption of cryptocurrencies, cryptojacking has become a significant security threat to crypto wallet users. This paper presents a front-end prototype of an AI-powered security dashboard, namely, CryptoGuard. Developed through a user-centered design process, the prototype was...

Fraud Detection and Risk Assessment of Online Payment Transactions on E-Commerce Platforms Based on LLM and GCN Frameworks

With the rapid growth of e-commerce, online payment fraud has become increasingly complex, posing serious threats to financial security and consumer trust. Traditional detection methods often struggle to capture the intricate relational structures inherent in transactional data. This study presen...

CISA Strategic Focus: CVE Quality for a Cyber Secure Future

The Cybersecurity and Infrastructure Security Agency CISA released CISA Strategic Focus: CVE Quality for a Cyber Secure Future. This detailed roadmap identifies priorities that will elevate the program to meet the needs of the global cybersecurity community. The roadmap and priorities are informe...

[Extended] Ethics in Computer Security Research: a Data-Driven Assessment of the Past, the Present, and the Possible Future

Ethical questions are discussed regularly in computer security. Still, researchers in computer security lack clear guidance on how to make, document, and assess ethical decisions in research when what is morally right or acceptable is not clear-cut. In this work, we give an overview of the...

Enhancing Cyber Threat Hunting -- a Visual Approach with the Forensic Visualization Toolkit

In today's dynamic cyber threat landscape, organizations must take proactive steps to bolster their cybersecurity defenses. Cyber threat hunting is a proactive and iterative process aimed at identifying and mitigating advanced threats that may go undetected by traditional security measures. Rathe...

IoTFuzzSentry: a Protocol Guided Mutation Based Fuzzer for Automatic Vulnerability Testing in Commercial IoT Devices

Protocol fuzzing is a scalable and cost-effective technique for identifying security vulnerabilities in deployed Internet of Things devices. During their operational phase, IoT devices often run lightweight servers to handle user interactions, such as video streaming or image capture in smart...

Multi-Channel Secure Communication Framework for Wireless IoT (MCSC-WoT): Enhancing Security in Internet of Things

In modern smart systems, the convergence of the Internet of Things IoT and Wireless of Things WoT have been revolutionized by offering a broad level of wireless connectivity and communication among various devices. Hitherto, this greater interconnectivity poses important security problems,...

Shell or Nothing: Real-World Benchmarks and Memory-Activated Agents for Automated Penetration Testing

Penetration testing is critical for identifying and mitigating security vulnerabilities, yet traditional approaches remain expensive, time-consuming, and dependent on expert human labor. Recent work has explored AI-driven pentesting agents, but their evaluation relies on oversimplified...

Cross-Service Token: Finding Attacks in 5G Core Networks

5G marks a major departure from previous cellular architectures, by transitioning from a monolithic design of the core network to a Service-Based Architecture SBA where services are modularized as Network Functions NFs which communicate with each other via standard-defined HTTP-based APIs called...

Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation

Phishing attacks are increasingly prevalent, with adversaries creating deceptive webpages to steal sensitive information. Despite advancements in machine learning and deep learning for phishing detection, attackers constantly develop new tactics to bypass detection models. As a result, phishing...

Phishing Webpage Detection: Unveiling the Threat Landscape and Investigating Detection Techniques

In the realm of cybersecurity, phishing stands as a prevalent cyber attack, where attackers employ various tactics to deceive users into gathering their sensitive information, potentially leading to identity theft or financial gain. Researchers have been actively working on advancing phishing...

Send to Which Account? Evaluation of an LLM-Based Scambaiting System

Scammers are increasingly harnessing generative AIGenAI technologies to produce convincing phishing content at scale, amplifying financial fraud and undermining public trust. While conventional defenses, such as detection algorithms, user training, and reactive takedown efforts remain important,...

Fluid-Antenna-Aided AAV Secure Communications in Eavesdropper Uncertain Location

For autonomous aerial vehicle AAV secure communications, traditional designs based on fixed position antenna FPA lack sufficient spatial degrees of freedom DoF, which leaves the line-of-sight-dominated AAV links vulnerable to eavesdropping. To overcome this problem, this paper proposes a framewor...

Overcoming DNSSEC Islands of Security: a TLS and IP-Based Certificate Solution

The Domain Name System DNS serves as the backbone of the Internet, primarily translating domain names to IP addresses. Over time, various enhancements have been introduced to strengthen the integrity of DNS. Among these, DNSSEC stands out as a leading cryptographic solution. It protects against...

Adversarial Attacks against Automated Fact-Checking: a Survey

In an era where misinformation spreads freely, fact-checking FC plays a crucial role in verifying claims and promoting reliable information. While automated fact-checking AFC has advanced significantly, existing systems remain vulnerable to adversarial attacks that manipulate or generate claims,...

Efficient Decoding Methods for Language Models on Encrypted Data

Large language models LLMs power modern AI applications, but processing sensitive data on untrusted servers raises privacy concerns. Homomorphic encryption HE enables computation on encrypted data for secure inference. However, neural text generation requires decoding methods like argmax and...

Flow-Based Detection and Identification of Zero-Day IoT Cameras

The majority of consumer IoT devices lack mechanisms for administrators to monitor and control them, hindering tailored security policies. A key challenge is identifying whether a new device, especially a streaming IoT camera, has joined the network. We present zCamInspector, a system for...

Establishing a Baseline of Software Supply Chain Security Task Adoption by Software Organizations

Software supply chain attacks have increased exponentially since 2020. The primary attack vectors for supply chain attacks are through: 1 software components; 2 the build infrastructure; and 3 humans a.k.a software practitioners. Software supply chain risk management frameworks provide a list of...

AgentSentinel: an End-To-End and Real-Time Security Defense Framework for Computer-Use Agents

Large Language Models LLMs have been increasingly integrated into computer-use agents, which can autonomously operate tools on a user's computer to accomplish complex tasks. However, due to the inherently unstable and unpredictable nature of LLM outputs, they may issue unintended tool commands or...

A Non-Monotonic Relationship: an Empirical Analysis of Hybrid Quantum Classifiers for Unseen Ransomware Detection

Detecting unseen ransomware is a critical cybersecurity challenge where classical machine learning often fails. While Quantum Machine Learning QML presents a potential alternative, its application is hindered by the dimensionality gap between classical data and quantum hardware. This paper...

Aspect-Oriented Programming in Secure Software Development: a Case Study of Security Aspects in Web Applications

Security remains a critical challenge in modern web applications, where threats such as unauthorized access, data breaches, and injection attacks continue to undermine trust and reliability. Traditional Object-Oriented Programming OOP often intertwines security logic with business functionality,...

I2P 2.10.0

I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version...

PatchSeeker: Mapping NVD Records to Their Vulnerability-Fixing Commits with LLM Generated Commits and Embeddings

Software vulnerabilities pose serious risks to modern software ecosystems. While the National Vulnerability Database NVD is the authoritative source for cataloging these vulnerabilities, it often lacks explicit links to the corresponding Vulnerability-Fixing Commits VFCs. VFCs encode precise code...

Empirical Security Analysis of Software-Based Fault Isolation through Controlled Fault Injection

We use browsers daily to access all sorts of information. Because browsers routinely process scripts, media, and executable code from unknown sources, they form a critical security boundary between users and adversaries. A common attack vector is JavaScript, which exposes a large attack surface d...

Backdoor Attacks and Defenses in Computer Vision Domain: a Survey

Backdoor trojan attacks embed hidden, controllable behaviors into machine-learning models so that models behave normally on benign inputs but produce attacker-chosen outputs when a trigger is present. This survey reviews the rapidly growing literature on backdoor attacks and defenses in the...

Spectral Masking and Interpolation Attack (SMIA): a Black-Box Adversarial Attack against Voice Authentication and Anti-Spoofing Systems

Voice Authentication Systems VAS use unique vocal characteristics for verification. They are increasingly integrated into high-security sectors such as banking and healthcare. Despite their improvements using deep learning, they face severe vulnerabilities from sophisticated threats like deepfake...

Breaking Android with AI: a Deep Dive into LLM-Powered Exploitation

The rapid evolution of Artificial Intelligence AI and Large Language Models LLMs has opened up new opportunities in the area of cybersecurity, especially in the exploitation automation landscape and penetration testing. This study explores Android penetration testing automation using LLM-based...

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT continues to expose critical security vulnerabilities, necessitating the development of efficient and robust intrusion detection systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detectio...

Leveraging Digital Twin-As-A-Service Towards Continuous and Automated Cybersecurity Certification

Traditional risk assessments rely on manual audits and system scans, often causing operational disruptions and leaving security gaps. To address these challenges, this work presents Security Digital Twin-as-a-Service SDT-aaS, a novel approach that leverages Digital Twin DT technology for automate...

A Decade-Long Landscape of Advanced Persistent Threats: Longitudinal Analysis and Global Trends

An advanced persistent threat APT refers to a covert, long-term cyberattack, typically conducted by state-sponsored actors, targeting critical sectors and often remaining undetected for long periods. In response, collective intelligence from around the globe collaborates to identify and trace...