Rethinking Cybersecurity Ontology Classification and Evaluation: Towards a Credibility-Centered Framework

This paper analyzes the proliferation of cybersecurity ontologies, arguing that this surge cannot be explained solely by technical shortcomings related to quality, but also by a credibility deficit - a lack of trust, endorsement, and adoption by users. This conclusion is based on our first...

An Introductory Review of the Theory of Continuous-Variable Quantum Key Distribution: Fundamentals, Protocols, and Security

Continuous-variable quantum key distribution CV-QKD has emerged as a promising approach for secure quantum communication, offering advantages such as high key generation rates, compatibility with standard telecommunication infrastructure, and potential for integration on photonic chips. This revi...

Behind the Curtain: How Shared Hosting Providers Respond to Vulnerability Notifications

Large-scale vulnerability notifications VNs can help hosting provider organizations HPOs identify and remediate security vulnerabilities that attackers can exploit in data breaches or phishing campaigns. Previous VN studies have primarily focused on factors under the control of reporters, such as...

Systems Security Foundations for Agentic Computing

This paper articulates short- and long-term research problems in AI agent security and privacy, using the lens of computer systems security. This approach examines end-to-end security properties of entire systems, rather than AI models in isolation. While we recognize that hardening a single mode...

Apache bRPC Server Crash

Apache bRPC versions prior to 1.15.0 has an uncontrolled recursion vulnerability that allows for a server crash...

Securing Large Language Models (LLMs) from Prompt Injection Attacks

Large Language Models LLMs are increasingly being deployed in real-world applications, but their flexibility exposes them to prompt injection attacks. These attacks leverage the model's instruction-following ability to make it perform malicious tasks. Recent work has proposed JATMO, a task-specif...

Secure Over-The-Air Computation against Multiple Eavesdroppers Using Correlated Artificial Noise

In the era of the Internet of Things and massive connectivity, many engineering applications, such as sensor fusion and federated edge learning, rely on efficient data aggregation from geographically distributed users over wireless networks. Over-the-air computation shows promising potential for...

CVE Breadcrumbs: Tracking Vulnerabilities through Versioned Apache Libraries

The Apache Software Foundation ASF ecosystem underpins a vast portion of modern software infrastructure, powering widely used components such as Log4j, Tomcat, and Struts. However, the ubiquity of these libraries has made them prime targets for high-impact security vulnerabilities, as illustrated...

FortiWeb Authentication Bypass Artifact Generator

This script attempts to detect if FortiWeb is vulnerable to authentication bypass. FortiWeb versions below 8.0.2 are affected...

Demystifying Feature Engineering in Malware Analysis of API Call Sequences

Machine learning ML has been widely used to analyze API call sequences in malware analysis, which typically requires the expertise of domain specialists to extract relevant features from raw data. The extracted features play a critical role in malware analysis. Traditional feature extraction is...

CTF Archive: Capture, Curate, Learn Forever

Capture the Flag CTF competitions represent a powerful experiential learning approach within cybersecurity education, blending diverse concepts into interactive challenges. However, the short duration typically 24-48 hours and ephemeral infrastructure of these events often impede sustained...

Banking System Stability: A Global Analysis of Cybercrime Laws

We examine the role of cybercrime legislation around the world in shaping the stability of the banking system. We compile a novel dataset covering the enactment of cybercrime legislation in 132 developed and developing countries to empirically test this research question. We find that the enactme...

Quantum Ramp Secret Sharing from Haar Scrambling

Quantum information scrambling has emerged as a powerful tool for studying the dynamics of chaotic quantum many-body systems, assessing benchmarking protocols, and even investigating exotic black hole models. During quantum information scrambling, localized quantum information disperses across th...

Large Language Models Cannot Reliably Detect Vulnerabilities in JavaScript: The First Systematic Benchmark and Evaluation

Researchers have proposed numerous methods to detect vulnerabilities in JavaScript, especially those assisted by Large Language Models LLMs. However, the actual capability of LLMs in JavaScript vulnerability detection remains questionable, necessitating systematic evaluation and comprehensive...

MASCOT: Analyzing Malware Evolution through a Well-Curated Source Code Dataset

In recent years, the explosion of malware and extensive code reuse have formed complex evolutionary connections among malware specimens. The rapid pace of development makes it challenging for existing studies to characterize recent evolutionary trends. In addition, intuitive tools to untangle the...

Logic Encryption: This Time for Real

Modern circuits face various threats like reverse engineering, theft of intellectual property IP, side-channel attacks, etc. Here, we present a novel approach for IP protection based on logic encryption LE. Unlike established schemes for logic locking, our work obfuscates the circuit's structure...

Reverse Engineering and Control-Aware Security Analysis of the ArduPilot UAV Framework

Unmanned Aerial Vehicle UAV technologies are gaining high interest for many domains, which makes UAV security of utmost importance. ArduPilot is among the most widely used open-source autopilot UAV frameworks; yet, many studies demonstrate the vulnerabilities affecting such systems. Vulnerabiliti...

Hesperus Is Phosphorus: Mapping Threat Actor Naming Taxonomies at Scale

This paper studies the problem of Threat Actor TA naming convention inconsistency across leading Cyber Threat Intelligence CTI vendors. The current decentralized and proprietary nomenclature creates confusion and significant obstacles for researchers, including difficulties in integrating and...

Deterministic Random Bit Generators Based on Ascon for Embedded Systems

As the Deterministic Random Bit Generator DRBG serves as a fundamental component in random number generation and cryptographic applications, its performance and security are particularly critical in resource-constrained embedded systems, where memory capacity and computational efficiency are...

Red Teaming Large Reasoning Models

Large Reasoning Models LRMs have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical consistency through explicit chains of thought CoT. However, these models introduce novel safety and reliability risks, such as CoT-hijacking and...

RECTor: Robust and Efficient Correlation Attack on Tor

Tor is a widely used anonymity network that conceals user identities by routing traffic through encrypted relays, yet it remains vulnerable to traffic correlation attacks that deanonymize users by matching patterns in ingress and egress traffic. However, existing correlation methods suffer from t...

GAPS: Guiding Dynamic Android Analysis with Static Path Synthesis

Dynamically resolving method reachability in Android applications remains a critical and largely unsolved problem. Despite notable advancements in GUI testing and static call graph construction, current tools are insufficient for reliably driving execution toward specific target methods, especial...

Evaluating LLMs for One-Shot Patching of Real and Artificial Vulnerabilities

Automated vulnerability patching is crucial for software security, and recent advancements in Large Language Models LLMs present promising capabilities for automating this task. However, existing research has primarily assessed LLMs using publicly disclosed vulnerabilities, leaving their...

Identification of Malicious Posts on the Dark Web Using Supervised Machine Learning

Given the constant growth and increasing sophistication of cyberattacks, cybersecurity can no longer rely solely on traditional defense techniques and tools. Proactive detection of cyber threats has become essential to help security teams identify potential risks and implement effective mitigatio...

IoTEdu: Access Control, Detection, and Automatic Incident Response in Academic IoT Networks

The growing presence of IoT devices in academic environments has increased operational complexity and exposed security weaknesses, especially in academic institutions without unified policies for registration, monitoring, and incident response involving IoT. This work presents IoTEdu, an integrat...

SD-CGAN: Conditional Sinkhorn Divergence GAN for DDoS Anomaly Detection in IoT Networks

The increasing complexity of IoT edge networks presents significant challenges for anomaly detection, particularly in identifying sophisticated Denial-of-Service DoS attacks and zero-day exploits under highly dynamic and imbalanced traffic conditions. This paper proposes SD-CGAN, a Conditional...

Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection

Few-shot prompting has emerged as a practical alternative to fine-tuning for leveraging the capabilities of large language models LLMs in specialized tasks. However, its effectiveness depends heavily on the selection and quality of in-context examples, particularly in complex domains. In this wor...

Clustering Malware at Scale: A First Full-Benchmark Study

Recent years have shown that malware attacks still happen with high frequency. Malware experts seek to categorize and classify incoming samples to confirm their trustworthiness or prove their maliciousness. One of the ways in which groups of malware samples can be identified is through malware...

An Empirical Study on the Security Vulnerabilities of GPTs

Equipped with various tools and knowledge, GPTs, one kind of customized AI agents based on OpenAI's large language models, have illustrated great potential in many fields, such as writing, research, and programming. Today, the number of GPTs has reached three millions, with the range of specific...

CacheTrap: Injecting Trojans in LLMs without Leaving Any Traces in Inputs or Weights

Adversarial weight perturbation has emerged as a concerning threat to LLMs that either use training privileges or system-level access to inject adversarial corruption in model weights. With the emergence of innovative defensive solutions that place system- and algorithm-level checks and correctio...

Enhancing the Security of Rollup Sequencers Using Decentrally Attested TEEs

The growing scalability demand of public Blockchains led to the rise of Layer-2 solutions, such as Rollups. Rollups improve transaction throughput by processing operations off-chain and posting the results on-chain. A critical component in Rollups is the Sequencer, responsible for receiving,...

Abacre Restaurant Point of Sale Insecure Storage

All versions of Abacre Restaurant Point of Sale POS up to 15.0.0.1656 leave device-bound license keys in process memory insecurely...

Keyless Entry: Breaking and Entering EMMC RPMB with EMFI

The Replay Protected Memory Block RPMB in modern storage systems provides a secure area where data integrity is ensured by authentication. This block is used in digital devices to store pivotal information that must be safeguarded against modification by potential attackers. This paper targets th...

Exploring the SECURITY.Md in the Dependency Chain: Preliminary Analysis of the PyPI Ecosystem

Security policies, such as SECURITY.md files, are now common in open-source projects. They help guide responsible vulnerability reporting and build trust among users and contributors. Despite their growing use, it is still unclear how these policies influence the structure and evolution of softwa...

Exposing Vulnerabilities in RL: A Novel Stealthy Backdoor Attack through Reward Poisoning

Reinforcement learning RL has achieved remarkable success across diverse domains, enabling autonomous systems to learn and adapt to dynamic environments by optimizing a reward function. However, this reliance on reward signals creates a significant security vulnerability. In this paper, we study ...

An Efficient Privacy-Preserving Intrusion Detection Scheme for UAV Swarm Networks

The rapid proliferation of unmanned aerial vehicles UAVs and their applications in diverse domains, such as surveillance, disaster management, agriculture, and defense, have revolutionized modern technology. While the potential benefits of swarm-based UAV networks are growing significantly, they...

Department-Specific Security Awareness Campaigns: A Cross-Organizational Study of HR and Accounting

Many cyberattacks succeed because they exploit flaws at the human level. To address this problem, organizations rely on security awareness programs, which aim to make employees more resilient against social engineering. While some works have suggested that such programs should account for...

HarmonicAttack: An Adaptive Cross-Domain Audio Watermark Removal

The availability of high-quality, AI-generated audio raises security challenges such as misinformation campaigns and voice-cloning fraud. A key defense against the misuse of AI-generated audio is by watermarking it, so that it can be easily distinguished from genuine audio. As those seeking to...

Standardized Threat Taxonomy for AI Security, Governance, and Regulatory Compliance

The accelerating deployment of artificial intelligence systems across regulated sectors has exposed critical fragmentation in risk assessment methodologies. A significant "language barrier" currently separates technical security teams, who focus on algorithmic vulnerabilities e.g., MITRE ATLAS,...

Secure Command, Control and Communications Systems (C3) for Army UxVs

Unmanned Vehicles UxVs are increasingly used in modern military operations for reconnaissance, surveillance, and strike missions, enhancing situational awareness while reducing risk to personnel. Their affordability and rapid deployment have encouraged the adoption of commercial solutions. Howeve...

Exploring Hidden Geographic Disparities in Android Apps

While mobile app evolution has been widely studied, geographical variation in app behavior remains largely unexplored. This paper presents a large-scale study of location-based Android app differentiation, uncovering two important and underexamined phenomena with security and fairness implication...

A Safety and Security Framework for Real-World Agentic Systems

This paper introduces a dynamic and actionable framework for securing agentic AI systems in enterprise deployment. We contend that safety and security are not merely fixed attributes of individual models but also emergent properties arising from the dynamic interactions among models, orchestrator...

Constructing and Benchmarking: A Labeled Email Dataset for Text-Based Phishing and Spam Detection Framework

Phishing and spam emails remain a major cybersecurity threat, with attackers increasingly leveraging Large Language Models LLMs to craft highly deceptive content. This study presents a comprehensive email dataset containing phishing, spam, and legitimate messages, explicitly distinguishing betwee...

Unsupervised Anomaly Detection for Smart IoT Devices: Performance and Resource Comparison

The rapid expansion of Internet of Things IoT deployments across diverse sectors has significantly enhanced operational efficiency, yet concurrently elevated cybersecurity vulnerabilities due to increased exposure to cyber threats. Given the limitations of traditional signature-based Anomaly...

IGEL OS Persistent Payload

This Metasploit module provides persistence for IGEL OS Workspace Edition for a specified payload. It writes a payload to disk or base64-encodes it and executes from the registry...

Finite-Key Security Analysis of the Decoy-State BB84 QKD with Passive Measurement

The decoy-state Bennett-Brassard 1984 BB84 quantum key distribution QKD protocol is widely regarded as the de facto standard for practical implementations. On the receiver side, passive basis choice is attractive because it significantly reduces the need for random number generators and eliminate...

Digital Twin-Driven Secure Access Strategy for SAGIN-Enabled IoT Networks

In space-air-ground integrated networks SAGIN-enabled IoT networks, secure access has become a significant challenge due to the increasing risks of eavesdropping attacks. To address these threats to data confidentiality, this paper proposes a Digital Twin DT-driven secure access strategy. The...

FreeBSD Security Advisory - FreeBSD-SA-25:10.unbound

FreeBSD Security Advisory - Promiscuous NS RRSets that complement DNS replies in the authority section can be used to trick resolvers to update their delegation information for the zone. Usually these RRSets are used to update the resolver's knowledge of the zone's name servers. If a malicious...

TOR Virtual Network Tunneling Tool 0.4.8.21

Tor is a network of virtual tunnels that allows people and groups to improve their privacy and security on the Internet. It also enables software developers to create new communication tools with built-in privacy features. It provides the foundation for a range of applications that allow...

Categorical Framework for Quantum-Resistant Zero-Trust AI Security

The rapid deployment of AI models necessitates robust, quantum-resistant security, particularly against adversarial threats. Here, we present a novel integration of post-quantum cryptography PQC and zero trust architecture ZTA, formally grounded in category theory, to secure AI model access. Our...