Credential Leakage in LLM Agent Skills: A Large-Scale Empirical Study

Third-party skills extend LLM agents with powerful capabilities but often handle sensitive credentials in privileged environments, making leakage risks poorly understood. We present the first large-scale empirical study of this problem, analyzing 17,022 skills sampled from 170,226 on SkillsMP usi...

A Tsetlin Machine-Driven Intrusion Detection System for Next-Generation IoMT Security

The rapid adoption of the Internet of Medical Things IoMT is transforming healthcare by enabling seamless connectivity among medical devices, systems, and services. However, it also introduces serious cybersecurity and patient safety concerns as attackers increasingly exploit new methods and...

A Systematic Security Evaluation of OpenClaw and Its Variants

Tool-augmented AI agents substantially extend the practical capabilities of large language models, but they also introduce security risks that cannot be identified through model-only evaluation. In this paper, we present a systematic security assessment of six representative OpenClaw-series agent...

Apple Live Caller ID Privacy Concerns

Apple's oblivious HTTP relay for Live Caller ID Lookup iOS 18+ routes traffic through 14 third-party endpoints across six countries. These include an anonymous Delaware LLC sharing data with OpenAI, a Russian endpoint Yandex, and a Swiss GmbH whose privacy policy names "The Legal Entity to be...

Vienna Assistant 1.2.542 Local Privilege Escalation

Vienna Assistant MacOS version 1.2.542 suffers from a missing validation vulnerability that allows for privilege escalation...

OWASP CRS Arbitrary File Upload

A vulnerability was identified in OWASP CRS where whitespace padding in filenames can bypass file upload extension checks, allowing uploads of dangerous files such as .php, .phar, .jsp, and .jspx. This has been addressed in versions 3.3.9, 4.25.x LTS, and 4.8.x...

ContractShield: Bridging Semantic-Structural Gaps Via Hierarchical Cross-Modal Fusion for Multi-Label Vulnerability Detection in Obfuscated Smart Contracts

Smart contracts are increasingly targeted by adversaries employing obfuscation techniques such as bogus code injection and control flow manipulation to evade vulnerability detection. Existing multimodal methods often process semantic, temporal, and structural features in isolation and fuse them...

ML Defender (ARGus NDR): An Open-Source Embedded ML NIDS for Botnet and Anomalous Traffic Detection in Resource-Constrained Organizations

Ransomware and DDoS attacks disproportionately impact hospitals, schools, and small organizations that cannot afford enterprise security solutions. We present ML Defender aRGus NDR, an open-source network intrusion detection system built in C++20, deployable on commodity hardware at approximately...

RuleForge: Automated Generation and Validation for Web Vulnerability Detection at Scale

Security teams face a challenge: the volume of newly disclosed Common Vulnerabilities and Exposures CVEs far exceeds the capacity to manually develop detection mechanisms. In 2025, the National Vulnerability Database published over 48,000 new vulnerabilities, motivating the need for automation. W...

AgentWatcher: A Rule-Based Prompt Injection Monitor

Large language models LLMs and their applications, such as agents, are highly vulnerable to prompt injection attacks. State-of-the-art prompt injection detection methods have the following limitations: 1 their effectiveness degrades significantly as context length increases, and 2 they lack...

Street-Legal Physical-World Adversarial Rim for License Plates

Automatic license plate reader ALPR systems are widely deployed to identify and track vehicles. While prior work has demonstrated vulnerabilities in ALPR systems, far less attention has been paid to their legality and physical-world practicality. We investigate whether low-resourced threat actors...

Seclens: Role-Specific Evaluation of LLM'S for Security Vulnerablity Detection

Existing benchmarks for LLM-based vulnerability detection compress model performance into a single metric, which fails to reflect the distinct priorities of different stakeholders. For example, a CISO may emphasize high recall of critical vulnerabilities, an engineering leader may prioritize...

Automated Malware Family Classification Using Weighted Hierarchical Ensembles of Large Language Models

Malware family classification remains a challenging task in automated malware analysis, particularly in real-world settings characterized by obfuscation, packing, and rapidly evolving threats. Existing machine learning and deep learning approaches typically depend on labeled datasets, handcrafted...

From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers

The model context protocol MCP standardizes how LLMs connect to external tools and data sources, enabling faster integration but introducing new attack vectors. Despite the growing adoption of MCP, existing MCP security studies classify attacks by their observable effects, obscuring how attacks...

WhatWeb Scanner 0.6.4

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...

Architectural Implications of the UK Cyber Security and Resilience Bill

The UK Cyber Security and Resilience CS&R Bill represents the most significant reform of UK cyber legislation since the Network and Information Systems NIS Regulations 2018. While existing analysis has addressed the Bill's regulatory requirements, there is a critical gap in guidance on the...

Design and Implementation of an Open-Source Security Framework for Cloud Infrastructure

Misconfiguration, excessive privilege, and tool fragmentation remain the main reasons why enterprise cloud environments are breached. Recent reports on cloud-native application protection note that most incidents can be traced back to configuration or identity errors rather than platform flaws, a...

The Quantum-Cryptographic Co-Evolution

As quantum computing matures toward the realization of Cryptographically Relevant Quantum Computers CRQC, global cryptographic infrastructure faces an existential threat. This paper introduces a two-dimensional coordinate system to map the co-evolution of cryptographic resilience x-axis and...

AEGIS: Adversarial Entropy-Guided Immune System -- Thermodynamic State Space Models for Zero-Day Network Evasion Detection

As TLS 1.3 encryption limits traditional Deep Packet Inspection DPI, the security community has pivoted to Euclidean Transformer-based classifiers e.g., ET-BERT for encrypted traffic analysis. However, these models remain vulnerable to byte-level adversarial morphing -- recent pre-padding attacks...

Synthetic Trust Attacks: Modeling How Generative AI Manipulates Human Decisions in Social Engineering Fraud

Imagine receiving a video call from your CFO, surrounded by colleagues, asking you to urgently authorise a confidential transfer. You comply. Every person on that call was fake, and you just lost $25 million. This is not a hypothetical. It happened in Hong Kong in January 2024, and it is becoming...

WPProbe Plugin Enumeration Tool 0.11.4

A fast WordPress plugin and theme scanner that detects installed plugins via REST API enumeration and themes from HTML discovery, then maps them to known vulnerabilities. Over 5,000 plugins detectable without brute-force, thousands more with it...

Windows Persistence Via UserInitMprLogonScript

This Metasploit module establishes persistence by setting the UserInitMprLogonScript value in HKCU\Environment. During user logon, userinit.exe checks this value and executes the specified command or binary. The module writes a payload executable to disk and points UserInitMprLogonScript to that...

python-ecdsa Denial of Service

python-ecdsa suffers from a denial of service vulnerability...

Poison Once, Exploit Forever: Environment-Injected Memory Poisoning Attacks on Web Agents

Memory makes LLM-based web agents personalized, powerful, yet exploitable. By storing past interactions to personalize future tasks, agents inadvertently create a persistent attack surface that spans websites and sessions. While existing security research on memory assumes attackers can directly...

Combating Data Laundering in LLM Training

Data rights owners can detect unauthorized data use in large language model LLM training by querying with proprietary samples. Often, superior performance e.g., higher confidence or lower loss on a sample relative to the untrained data implies it was part of the training corpus, as LLMs tend to...

LightGuard: Transparent WiFi Security Via Physical-Layer LiFi Key Bootstrapping

WiFi is inherently vulnerable to eavesdropping because RF signals may penetrate many physical boundaries, such as walls and floors. LiFi, by contrast, is an optical method confined to line-of-sight and blocked by opaque surfaces. We present LightGuard, a dual-link architecture built on this...

Automated Generation of Cybersecurity Exercise Scenarios

There is a growing need for cybersecurity professionals with practical knowledge and experience to meet societal needs and comply with new standards and regulations. At the same time, the advances in software technology and artificial intelligence point towards a future where software agents will...

Secure Network Function Computation for General Target and Security Functions

Secure network function computation is a critical research direction in network coding, which aims to ensure that the target function is correctly computed at the sink node while preventing the wiretapper from obtaining any information about the security function. In this paper, we focus on the...

Automated Framework to Evaluate and Harden LLM System Instructions against Encoding Attacks

System Instructions in Large Language Models LLMs are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational context in agentic AI applications. These instructions may contain sensitive information such as API credentials, internal policies, and...

"The System Will Choose Security over Humanity Every Time": Understanding Security and Privacy for U.S. Incarcerated Users

Digital devices like tablets, media players, and kiosks are increasingly deployed in U.S. prisons. These technologies can enable incarcerated people to access education, communicate with loved ones, and develop vital reentry skills. However, they can also introduce new privacy and security risks...

Assertain: Automated Security Assertion Generation Using Large Language Models

The increasing complexity of modern system-on-chip designs amplifies hardware security risks and makes manual security property specification a major bottleneck in formal property verification. This paper presents Assertain, an automated framework that integrates RTL design analysis, Common...

Obfuscating Code Vulnerabilities against Static Analysis in JavaScript Code

Code obfuscation is widely adopted in modern software development to protect intellectual property and hinder reverse engineering, but it also provides attackers with a powerful means to conceal malicious logic inside otherwise legitimate JavaScript code. In a software supply chain where a single...

VibeGuard: A Security Gate Framework for AI-Generated Code

"Vibe coding," in which developers delegate code generation to AI assistants and accept the output with little manual review, has gained rapid adoption in production settings. On March 31, 2026, Anthropic's Claude Code CLI shipped a 59.8 MB source map file in its npm package, exposing roughly...

Quantum-Safe Code Auditing: LLM-Assisted Static Analysis and Quantum-Aware Risk Scoring for Post-Quantum Cryptography Migration

The impending arrival of cryptographically relevant quantum computers CRQCs threatens the security foundations of modern software: Shor's algorithm breaks RSA, ECDSA, ECDH, and Diffie-Hellman, while Grover's algorithm reduces the effective security of symmetric and hash-based schemes. Despite NIS...

AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications

Large-scale web applications are widely deployed with complex third-party components, inheriting security risks arising from component vulnerabilities. Security assessment is therefore required to determine whether such known vulnerabilities remain practically exploitable in real applications...

Enhancing REST API Fuzzing with Access Policy Violation Checks and Injection Attacks

Due to their widespread use in industry, several techniques have been proposed in the literature to fuzz REST APIs. Existing fuzzers for REST APIs have been focusing on detecting crashes e.g., 500 HTTP server error status code. However, security vulnerabilities can have major drastic consequences...

When Safe Models Merge into Danger: Exploiting Latent Vulnerabilities in LLM Fusion

Model merging has emerged as a powerful technique for combining specialized capabilities from multiple fine-tuned LLMs without additional training costs. However, the security implications of this widely-adopted practice remain critically underexplored. In this work, we reveal that model merging...

Botan C++ Crypto Algorithms Library 3.11.1

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...

An Empirical Comparison of Security and Privacy Characteristics of Android Messaging Apps

Mobile messaging apps are a fundamental communication infrastructure, used by billions of people every day to share information, including sensitive data. Security and Privacy are thus critical concerns for such applications. Although the cryptographic protocols prevalent in messaging apps are...

When Labels Are Scarce: A Systematic Mapping of Label-Efficient Code Vulnerability Detection

Machine-learning-based code vulnerability detection CVD has progressed rapidly, from deep program representations to pretrained code models and LLM-centered pipelines. Yet dependable vulnerability labeling remains expensive, noisy, and uneven across projects, languages, and CWE types, motivating...

Terrapack TkWebCoreNG File Upload Endpoint Audit Tool

This Python script is a simple security audit tool designed to test the file upload interface of applications using TkWebCoreNG. It does not actual exploit anything...

On the Necessity of Pre-Agreed Secrets for Thwarting Last-Minute Coercion: Vulnerabilities and Lessons from the Loki E-Voting Protocol

Coercion-resistance CR is a crucial security property in e-voting systems. It ensures that an attacker cannot compel a voter to vote in a specific way by using threats or rewards. The Loki e-voting protocol, proposed by Giustolisi \emphet al. at IEEE S&P 2024, introduces a novel design that...

5G Puppeteer: Chaining Hidden Command and Control Channels in 5G Core Networks

Mobile networks are essential for modern societies. The most recent generation of mobile networks will be even more ubiquitous than previous ones. Therefore, the security of these networks as part of the critical infrastructure with essential communication services is of the uttermost importance...

Cybercrime As a Service: A Scoping Review

Cloud computing has drastically altered the ways in which it is possible to deliver information technologies in a service-led structure, however, this has also been reflected in the cybercrime domain. Cybercrime as a Service is an economic model where a technically skilled actor offers a given...

The Manipulate-And-Observe Attack on Quantum Key Distribution

Quantum key distribution is often regarded as an unconditionally secure method to exchange a secret key by harnessing fundamental aspects of quantum mechanics. Despite the robustness of key exchange, classical post-processing reveals vulnerabilities that an eavesdropper could target. In particula...

Architecting Secure AI Agents: Perspectives on System-Level Defenses against Indirect Prompt Injection Attacks

AI agents, predominantly powered by large language models LLMs, are vulnerable to indirect prompt injection, in which malicious instructions embedded in untrusted data can trigger dangerous agent actions. This position paper discusses our vision for system-level defenses against indirect prompt...

Security and Privacy in Virtual and Robotic Assistive Systems: A Comparative Framework

Assistive technologies increasingly support independence, accessibility, and safety for older adults, people with disabilities, and individuals requiring continuous care. Two major categories are virtual assistive systems and robotic assistive systems operating in physical environments. Although...

Efficient Software Vulnerability Detection Using Transformer-Based Models

Detecting software vulnerabilities is critical to ensuring the security and reliability of modern computer systems. Deep neural networks have shown promising results on vulnerability detection, but they lack the capability to capture global contextual information on vulnerable code. To address th...

OX Dovecot Pro Denial of Service / SQL Injection

A dozen vulnerabilities have been addressed in varying versions of OX Dovecot Pro and CE. Issues include resource consumption, input validation, path traversal, SQL injection, LDAP injection, authentication bypass, and improper authentication...

VulnScout-C: A Lightweight Transformer for C Code Vulnerability Detection

Vulnerability detection in C programs is a critical challenge in software security. Although large language models LLMs achieve strong detection performance, their multi-billion-parameter scale makes them impractical for integration into development workflows requiring low latency and continuous...