When Security Meets Usability: An Empirical Investigation of Post-Quantum Cryptography APIs

Advances in quantum computing increasingly threaten the security and privacy of data protected by current cryptosystems, particularly those relying on public-key cryptography. In response, the international cybersecurity community has prioritized the implementation of Post-Quantum Cryptography PQ...

Exposing the Systematic Vulnerability of Open-Weight Models to Prefill Attacks

As the capabilities of large language models continue to advance, so does their potential for misuse. While closed-source models typically rely on external defenses, open-weight models must primarily depend on internal safeguards to mitigate harmful behavior. Prior red-teaming research has largel...

nfstream 6.6.0

nfstream is a Python package providing fast, flexible, and expressive data structures designed to make working with online or offline network data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world network data analysis in Python...

OpenSSL 3.x Realistic ASN.1 / PKCS#12 Denial of Service Tool

This proof of concept builds structurally correct ASN.1 DER / PKCS12 files designed to stress-test OpenSSL's parser and memory handling. It focuses on non-exploitative impacts such as denial of service, excessive memory consumption, deep recursion, malformed lengths, and duplicated/overlapping...

State of Passkey Authentication in the Wild: A Census of the Top 100K Sites

Passkeys -- discoverable WebAuthn credentials synchronised across devices are widely promoted as the future of passwordless authentication. Built on the FIDO2 standard, they eliminate shared secrets and resist phishing while offering usability through platform credential managers. Since their...

Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning

Federated learning FL enables distributed model training across edge devices while preserving data locality. This decentralized approach has emerged as a promising solution for collaborative learning on sensitive user data, effectively addressing the longstanding privacy concerns inherent in...

Stegano 2.2.0

Stegano is a basic Python Steganography module. Stegano implements two methods of hiding: using the red portion of a pixel to hide ASCII messages, and using the Least Significant Bit LSB technique. It is possible to use a more advanced LSB method based on integers sets. The sets Sieve of...

A Trajectory-Based Safety Audit of Clawdbot (OpenClaw)

Clawdbot is a self-hosted, tool-using personal AI agent with a broad action space spanning local execution and web-mediated workflows, which raises heightened safety and security concerns under ambiguity and adversarial steering. We present a trajectory-centric evaluation of Clawdbot across six...

From SFT to RL: Demystifying the Post-Training Pipeline for LLM-Based Vulnerability Detection

The integration of LLMs into vulnerability detection VD has shifted the field toward interpretable and context-aware analysis. While post-training methods have shown promise in general coding tasks, their systematic application to VD remains underexplored. In this paper, we present the first...

Toward a Military Smart Cyber Situational Awareness (CSA)

The development of technology across multiple sectors and the growing importance of cyber warfare make the development of Cyber Situational Awareness CSA a fundamental component of any cyber defense strategy. CSA, as a practice, enables understanding of the current landscape within an organizatio...

AXE: An Agentic EXploit Engine for Confirming Zero-Day Vulnerability Reports

Vulnerability detection tools are widely adopted in software projects, yet they often overwhelm maintainers with false positives and non-actionable reports. Automated exploitation systems can help validate these reports; however, existing approaches typically operate in isolation from detection...

The Baby Steps of the European Union Vulnerability Database: An Empirical Inquiry

A new European Union Vulnerability Database EUVD was introduced via a legislative act in 2022. The paper examines empirically the meta-data content of the new EUVD. According to the results, actively exploited vulnerabilities archived to the EUVD have been rather severe, having had also high...

Assessing Cybersecurity Risks and Traffic Impact in Connected Autonomous Vehicles

Given the promising future of autonomous vehicles, it is foreseeable that self-driving cars will soon emerge as the predominant mode of transportation. While autonomous vehicles offer enhanced efficiency, they remain vulnerable to external attacks. In this research, we sought to investigate the...

Applying Public Health Systematic Approaches to Cybersecurity: The Economics of Collective Defense

The U.S. public health system increased life expectancy by more than 30 years since 1900 through systematic data collection, evidence-based intervention, and coordinated response. This paper examines whether cybersecurity can benefit from similar organizational principles. We find that both domai...

A Real-Time Approach to Autonomous CAN Bus Reverse Engineering

This paper introduces a real-time method for reverse engineering a vehicle's CAN bus without prior knowledge of the vehicle or its CAN system. By comparing inertial measurement and CAN data during significant vehicle events, the method accurately identified the CAN channels associated with the...

Cryptographic Choreographies

We present CryptoChoreo, a choreography language for the specification of cryptographic protocols. Choreographies can be regarded as an extension of Alice-and-Bob notation, providing an intuitive high-level view of the protocol as a whole rather than specifying each protocol role in isolation. Th...

The Rise of AI Agent Communities: Large-Scale Analysis of Discourse and Interaction on Moltbook

Moltbook is a Reddit-like social platform where AI agents create posts and interact with other agents through comments and replies, offering a real-world setting to examine agent-to-agent communication at scale. Using a public API snapshot collected about five days after launch 122,438 posts, we...

Backdoor Attacks on Contrastive Continual Learning for IoT Systems

The Internet of Things IoT systems increasingly depend on continual learning to adapt to non-stationary environments. These environments can include factors such as sensor drift, changing user behavior, device aging, and adversarial dynamics. Contrastive continual learning CCL combines contrastiv...

In-Context Autonomous Network Incident Response: An End-To-End Large Language Model Agent Approach

Rapidly evolving cyberattacks demand incident response systems that can autonomously learn and adapt to changing threats. Prior work has extensively explored the reinforcement learning approach, which involves learning response strategies through extensive simulation of the incident. While this...

Web Application Security Developer Training Guide

This guide gives a thorough overview of 34 web application vulnerabilities with descriptions of the issues, PHP examples of vulnerable code, exploit methodologies, and remediation strategies...

pgAdmin 4 Multi‑Target Vulnerability Scanner

This project is a PHP‑based multi‑target vulnerability scanner designed to identify potential exposure to CVE‑2025‑13780 affecting pgAdmin 4 versions 8.14 and below. The tool operates as a heuristic / threat‑intelligence scanner, not an exploit...

Execution-State-Aware LLM Reasoning for Automated Proof-Of-Vulnerability Generation

Proof-of-Vulnerability PoV generation is a critical task in software security, serving as a cornerstone for vulnerability validation, false positive reduction, and patch verification. While directed fuzzing effectively drives path exploration, satisfying complex semantic constraints remains a...

Assessing Spear-Phishing Website Generation in Large Language Model Coding Agents

Large Language Models are expanding beyond being a tool humans use and into independent agents that can observe an environment, reason about solutions to problems, make changes that impact those environments, and understand how their actions impacted their environment. One of the most common...

Secrecy and Verifiability: An Introduction to Electronic Voting

Democracies are built upon secure and reliable voting systems. Electronic voting systems seek to replace ballot papers and boxes with computer hardware and software. Proposed electronic election schemes have been subjected to scrutiny, with researchers spotting inherent faults and weaknesses...

TestSSL 3.2.3

testssl.sh is a free command line tool which checks a server's service on any port for the support of TLS/SSL ciphers, protocols as well as recent cryptographic flaws, and much more. It is written in pure bash, makes only use of standard Unix utilities, openssl and last but not least bash sockets...

Automatic Simplification of Common Vulnerabilities and Exposures Descriptions

Understanding cyber security is increasingly important for individuals and organizations. However, a lot of information related to cyber security can be difficult to understand to those not familiar with the topic. In this study, we focus on investigating how large language models LLMs could be...

Favia: Forensic Agent for Vulnerability-Fix Identification and Analysis

Identifying vulnerability-fixing commits corresponding to disclosed CVEs is essential for secure software maintenance but remains challenging at scale, as large repositories contain millions of commits of which only a small fraction address security issues. Existing automated approaches, includin...

LoRA-Based Parameter-Efficient LLMs for Continuous Learning in Edge-Based Malware Detection

The proliferation of edge devices has created an urgent need for security solutions capable of detecting malware in real time while operating under strict computational and memory constraints. Recently, Large Language Models LLMs have demonstrated remarkable capabilities in recognizing complex...

Sparse Autoencoders Are Capable LLM Jailbreak Mitigators

Jailbreak attacks remain a persistent threat to large language model safety. We propose Context-Conditioned Delta Steering CC-Delta, an SAE-based defense that identifies jailbreak-relevant sparse features by comparing token-level representations of the same harmful request with and without...

Resource-Aware Deployment Optimization for Collaborative Intrusion Detection in Layered Networks

Collaborative Intrusion Detection Systems CIDS are increasingly adopted to counter cyberattacks, as their collaborative nature enables them to adapt to diverse scenarios across heterogeneous environments. As distributed critical infrastructure operates in rapidly evolving environments, such as...

Unknown Attack Detection in IoT Networks Using Large Language Models: A Robust, Data-Efficient Approach

The rapid evolution of cyberattacks continues to drive the emergence of unknown zero-day threats, posing significant challenges for network intrusion detection systems in Internet of Things IoT networks. Existing machine learning and deep learning approaches typically rely on large labeled...

Nikto Web Scanner 2.6.0

Nikto is an Open Source GPL web server scanner which performs comprehensive tests against web servers for multiple items, including thousands of potentially dangerous files/programs, checks for outdated versions of over 1500 server components, and version specific problems on hundreds of servers...

An Empirical Study of the Imbalance Issue in Software Vulnerability Detection

Vulnerability detection is crucial to protect software security. Nowadays, deep learning DL is the most promising technique to automate this detection task, leveraging its superior ability to extract patterns and representations within extensive code volumes. Despite its promise, DL-based...

Lightweight Cluster-Based Federated Learning for Intrusion Detection in Heterogeneous IoT Networks

The rise of heterogeneous Internet of Things IoT devices has raised security concerns due to their vulnerability to cyberattacks. Intrusion Detection Systems IDS are crucial in addressing these threats. Federated Learning FL offers a privacy-preserving solution, but IoT heterogeneity and limited...

Tracking the Trackers: Commercial Surveillance Occurring on U.S. Army Networks

Despite current security implementations, Internet activity on DoD networks is susceptible to web trackers and commercial data collection, which have the potential to expose information about service members and unit operations. This report documents the outcomes of a study to characterize web...

DRAMatic Speedup: Accelerating HE Operations on a Processing-In-Memory System

Homomorphic encryption HE is a promising technology for confidential cloud computing, as it allows computations on encrypted data. However, HE is computationally expensive and often memory-bound on conventional computer architectures. Processing-in-Memory PIM is an alternative hardware architectu...

Verifiable Provenance of Software Artifacts with Zero-Knowledge Compilation

Verifying that a compiled binary originates from its claimed source code is a fundamental security requirement, called source code provenance. Achieving verifiable source code provenance in practice remains challenging. The most popular technique, called reproducible builds, requires difficult...

Agentic AI for Cybersecurity: A Meta-Cognitive Architecture for Governable Autonomy

Contemporary AI-driven cybersecurity systems are predominantly architected as model-centric detection and automation pipelines optimized for task-level performance metrics such as accuracy and response latency. While effective for bounded classification tasks, these architectures struggle to...

MalTool: Malicious Tool Attacks on LLM Agents

In a malicious tool attack, an attacker uploads a malicious tool to a distribution platform; once a user installs the tool and the LLM agent selects it during task execution, the tool can compromise the user's security and privacy. Prior work primarily focuses on manipulating tool names and...

Kill It with FIRE: On Leveraging Latent Space Directions for Runtime Backdoor Mitigation in Deep Neural Networks

Machine learning models are increasingly present in our everyday lives; as a result, they become targets of adversarial attackers seeking to manipulate the systems we interact with. A well-known vulnerability is a backdoor introduced into a neural network by poisoned training data or a malicious...

motionEye 0.43.1b4 Remote Code Execution

Client-side validation in motionEye's web UI can be bypassed via overriding the JS validation function. Arbitrary values including shell interpolation syntax can be saved into the motion config. When motion is restarted, the motion process interprets the config and can execute shell syntax embedd...

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP

The rapid development of the AI agent communication protocols, including the Model Context Protocol MCP, Agent2Agent A2A, Agora, and Agent Network Protocol ANP, is reshaping how AI agents communicate with tools, services, and each other. While these protocols support scalable multi-agent...

Optimizing Agent Planning for Security and Autonomy

Indirect prompt injection attacks threaten AI agents that execute consequential actions, motivating deterministic system-level defenses. Such defenses can provably block unsafe actions by enforcing confidentiality and integrity policies, but currently appear costly: they reduce task completion...

H.265/HEVC Video Steganalysis Based on CU Block Structure Gradients and IPM Mapping

Existing H.265/HEVC video steganalysis research mainly focuses on statistical feature modeling at the levels of motion vectors MV, intra prediction modes IPM, or transform coefficients. In contrast, studies targeting the coding-structure level - especially the analysis of block-level steganograph...

glibc 2.38 Buffer Overflow

This is a local privilege escalation exploit for CVE-2023-4911, also known as "Looney Tunables", caused by a buffer overflow in the glibc dynamic loader's environment variable parsing logic. The vulnerability is triggered by crafting a maliciously long GLIBCTUNABLES string which corrupts internal...

GoodVibe: Security-By-Vibe for LLM-Based Code Generation

Large language models LLMs are increasingly used for code generation in fast, informal development workflows, often referred to as vibe coding, where speed and convenience are prioritized, and security requirements are rarely made explicit. In this setting, models frequently produce functionally...

VulReaD: Knowledge-Graph-Guided Software Vulnerability Reasoning and Detection

Software vulnerability detection SVD is a critical challenge in modern systems. Large language models LLMs offer natural-language explanations alongside predictions, but most work focuses on binary evaluation, and explanations often lack semantic consistency with Common Weakness Enumeration CWE...

Practical Quantum Tokens: Challenges and Perspectives

The concept of quantum tokens dates back alongside quantum cryptography to Stephen Wiesner's seminal work in 19831. Already this initial work proposes society-relevant applications such as secure quantum banknotes, which can be exchanged between a bank and a customer. This quantum currency is bas...

Multi Layer Protection against Low Rate DDoS Attacks in Containerized Systems

Low rate Distributed Denial of Service DDoS attacks have emerged as a major threat to containerized cloud infrastructures. Due to their low traffic volumes, these attacks can be difficult to detect and mitigate, potentially causing serious harm to internet applications. This work proposes a DDoS...

Jailbreaking Leaves a Trace: Understanding and Detecting Jailbreak Attacks from Internal Representations of Large Language Models

Jailbreaking large language models LLMs has emerged as a critical security challenge with the widespread deployment of conversational AI systems. Adversarial users exploit these models through carefully crafted prompts to elicit restricted or unsafe outputs, a phenomenon commonly referred to as...