Piggybacking on Perception: Stealthy Concurrent Audio Prompt Injections against Multimodal LLM Agents

Large Language Model LLM-driven multimodal agents are increasingly deployed to execute autonomous tasks via continuous audio interaction. While this paradigm enhances interaction naturalness, it introduces a critical yet under-explored attack surface, as audio inputs inevitably contain...

Statistically Secure Uncloneable Encryption of Arbitrary Messages

Unconditional uncloneable encryption of a single bit with efficient encryption and decryption is now possible. However, whether the extension to messages of arbitrary length achieves statistical security remains to be known. Using the fact that the encoding bases for the single-bit scheme known t...

CHARGE: Leveraging CWE Hierarchies for Hardware Security SystemVerilog Assertion Generation

This paper presents CHARGE, an automated framework for generating security properties for unverified RTL modules using CWEs and large language models LLMs. The hallmark is a reasoning process that leverages the hierarchical nature of CWE entries to improve accuracy when identifying...

FreeBSD Security Advisory - FreeBSD-SA-26:53.ktrace

FreeBSD Security Advisory - As an inadvertent side effect of an unrelated code change, PRIVKTRACE was always denied to a jailed root user. Tracing configured by a jailed root user was therefore not flagged as privileged...

FreeBSD Security Advisory - FreeBSD-SA-26:50.kqueue

FreeBSD Security Advisory - While the kernel was copying knotes during fork, a knote with a timer-based filter could fire and be enqueued on the kqueue's active list before the copy was complete. The copy routine did not account for this and could enqueue the new knote a second time, corrupting t...

A Structuration Approach to Theorizing Cybersecurity Practice: The STARC Model

The problem: Cybersecurity practice runs simultaneously across analysts, teams, organizations, sectors, and regulators, co-evolves with adversaries, and increasingly blends human and algorithmic decision-making. The theories applied to it operate at single organizational levels and cannot explain...

C-RE-ACT: Causal RE-ACTing Agent for O-RAN Forensic Triage

The shift to O-RAN architectures marks a turning point in cellular security, where increased openness and modularity directly translate into a broader attack surface. Among the security threats cataloged by the O-RAN Alliance Working Group 11, performance-degradation attacks constitute the larges...

Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion

We present a reproducible pipeline for mapping Common Vulnerabilities and Exposures CVEs to MITRE ATT&CK Enterprise techniques from free-text vulnerability descriptions. Rather than relying on the CWE-CAPEC-ATT&CK derivation chain, whose table-expansion artifacts we quantify, we train a multi-lab...

Network Reciprocity Shapes Evolutionary Cybersecurity Dynamics

AI-assisted cybersecurity systems are characterised by continuous adaptation between attackers and defenders, making evolutionary game theory a natural framework for studying their long-term behaviour. However, existing evolutionary cybersecurity models have primarily focused on homogeneous...

On the Use of Synthetic Data for Threshold Calibration in Face Recognition: Performance and Security Implications for Border Control Systems

The recently deployed Entry/Exit System EES introduces large-scale biometric verification into European border control, requiring face recognition systems to operate at extremely low false match rates FMR. While regulatory frameworks define performance targets at the EES Central System level, the...

Synology Man-In-The-Middle

Synology stale DNS allows practical interception of traffic from vulnerable DSM clients, making older vulnerabilities more practical to exploit...

A Non-Intrusive Traffic Analysis Framework for Authorization Risk Detection and Coordinated Response in Web Applications

Authorization violations under valid Web sessions are difficult to identify and handle in real time from traffic because they depend strongly on business semantics and exhibit few distinctive protocol-level features. This paper proposes a non-intrusive traffic analysis framework for authorization...

Towards Quantum Machine Learning for Assessing the Resilience of Post-Quantum Cryptography

The potential capabilities of quantum computers motivated the development of cryptographic protocols suitable for securing communication against adversaries with access to large fault-tolerant quantum computers. However, even though current quantum computers are limited in terms of size and...

Security Evaluation of Quantum Distance-Bounding Protocols Via Semidefinite Programming

Quantum distance-bounding QDB protocols let a verifier check that a prover is both genuine and physically nearby. During a timed fast phase of quantum communication, the verifier measures round-trip times to obtain an upper bound on the prover's distance. For a uniform comparison, we isolate the...

Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation

Reusable skills are becoming a fundamental building block of Large Language Model LLM agents, enabling capabilities to be packaged, shared, and reused across diverse applications. However, existing security research primarily focuses on prompt injection and runtime execution, leaving security ris...

Rethinking Penetration Testing for AI-Enabled Systems: From Resource Compromise to Behavioral Objective Violation

Penetration testing traditionally evaluates whether adversaries can exploit weaknesses in software, infrastructure, configurations, or operational controls to achieve security-relevant compromise. This paradigm remains necessary for AI-enabled systems, but it is no longer sufficient. In such...

BARS: Benign-Anchored Ranking and Selection for False Alarm Reduction in Network Intrusion Detection

False alarms remain a major barrier to deploying network intrusion detection systems NIDS. In high-volume environments, even a sub-1% false positive rate can generate tens of thousands of daily alerts. Filter-based feature selection is attractive because it operates upstream of the classifier and...

Evaluating Frontier AI Agents As Autonomous Clinical Security Auditors

Clinical AI models can expose patients to harm when adversarial vulnerabilities go undetected, yet formal security auditing requires statistical expertise, specialized tools, and significant time. We present an open evaluation task, built on METR Task Standard v0.3.0, that tests whether frontier ...

When Binaries Talk Back: Representation-Confusion Attacks on LLM-Assisted Reverse Engineering

LLM-assisted reverse-engineering RE systems analyze strings, decompiler output, and tool reports derived from ttacker-controlled binaries. A binary can make data look like instructions or records from one origin look like independent evidence. We call such failures Representation-Confusion Attack...

Trust but Verify? Uncovering the Security Debt of Autonomous Coding Agents

The increasing adoption of autonomous coding agents accelerates software development but also introduces scoped security risks within high-impact file paths that can outpace traditional human review capacity. While prior research has primarily evaluated these systems in terms of functional...

SA-DRL: Security-Aware Deep Reinforcement Learning for Ransomware Detection with Asymmetric Reward Design

Ransomware detection is a security-critical task in which false negatives and false positives have unequal operational consequences. Conventional machine learning detectors often use symmetric objectives that penalize missed ransomware detections and benign false alarms equally, although a false...

Whistleblowersoftware.com Confidentiality Fail

The anonymous reporting flow on whistleblowersoftware.com encrypts report text end-to-end in the browser but does not extend the same guarantee to attachments and exposes the reporter's network identity and timing to a US-based third party. Together these weaken the confidentiality and anonymity...

Nebula AI-Powered Penetration Testing 2.0.0b31

Nebula is an advanced, AI-powered penetration testing open-source tool that revolutionizes penetration testing by integrating state-of-the-art AI models into your command-line interface. Designed for cybersecurity professionals, ethical hackers, and developers, Nebula automates vulnerability...

Asterisk 22.10.1 Security Release

The Asterisk Development Team would like to announce security release Asterisk 22.10.1. It addresses 20 security issues...

Apache .htaccess Persistence

This Metasploit module writes a persistence payload into an Apache .htaccess file using modcgi. The .htaccess file itself acts as a CGI shell, executing commands passed via the query string. Inspired by the htshells project by wireghoul...

IPv6 Extension Header Testing and Network Stress Utility Using Scapy

This Python script combines network validation, protocol behavior testing, and packet-generation capabilities focused on IPv4 and IPv6 traffic analysis using Scapy...

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

The rapid growth of publicly available digital information has rendered manual open-source intelligence OSINT analysis insufficient for modern intelligence, cybersecurity, and cyber investigation. Large language models LLMs and agentic AI systems, capable of tool use, multi-step reasoning, and...

IPv4/IPv6 Connectivity Validator

This Python script is a network validation utility built with Scapy that performs basic reachability testing for both IPv4 and IPv6 targets using ICMP echo requests...

Knowledge over Parameters: Evolving Smart Contract Vulnerability Detection

Smart contract vulnerabilities are predominantly logic bugs whose detection requires structured, step-by-step procedural knowledge of attack patterns and contract semantics. Existing LLM-based methods struggle to generate this knowledge automatically: prompt-based methods rely on manually crafted...

Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware

LLM coding agents increasingly rely on third-party agent skills from public marketplaces, which execute with the agent's privileges and create a software supply-chain attack surface: a malicious skill can steal credentials, exfiltrate source code, or install backdoors. Existing defenses use stati...

Understanding Build Reproducibility in the F-Droid Ecosystem

The security of open source applications benefits considerably from the possibility of rebuilding their source and verifying the output. F-Droid, a prominent distribution for open source Android applications, systematically rebuilds them from source and tests their bitwise reproducibility at app...

Trust Boundary Semantic Gaps: A Multi-Dimensional Analysis and Mitigation for Security-By-Design

Modern systems use format-, protocol-, and signature-based mechanisms before accepting artifacts across trust boundaries. These mechanisms are necessary: they show that an artifact is well formed, protocol-compliant, or properly authenticated. They do not, however, show that the artifact satisfie...

Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond

The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this imperative, this paper presents an overview of AI risk assessment identification and analysis and management methodologies...

Cognitive Firewall: A Proactive, Zero-Trust, Multi-Gate Framework for LLM Safety

Large language models LLMs can be induced to produce harmful content through multi turn strategies in which no single user message appears clearly unsafe. Existing runtime safeguards commonly evaluate prompts or responses as isolated messages, which limits their ability to recover ac-cumulated...

Hybrid Topological Data Analysis and LSTM Networks for Enhanced Network Intrusion Detection Using CIC-IDS2017 Dataset

Network intrusion detection systems NIDS are crucial in cybersecurity infrastructure, needing advanced techniques to detect hostile activity in network traffic. This research introduces a hybrid approach that combines Topological Data Analysis TDA with Long Short-Term Memory LSTM networks to...

Beyond Wireless Security: Covert Communications in Large Language Model-Enabled Edge Networks

Large language model LLM-enabled edge networks LLMENs offer mobile users high-quality and low-latency AI-generated content services in the 6G era. However, unlike typical edge networks, LLMENs present unique security challenges due to the inherent complexity of LLMs, their high computational...

Security--Fidelity Tradeoffs: The Hidden Cost of Prompt Injection Defense

We identify a security-fidelity tradeoff in defending LLMs against indirect prompt injection: defenses resist injected instructions largely by suppressing untrusted text, which corrupts tasks that must preserve it, such as translation and document editing. Attack-success metrics cannot see this,...

TOR Virtual Network Tunneling Tool 0.4.9.11

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...

Continuous-Variable Source-Independent Quantum Random Number Generation with General POVMs

Continuous-variable source-independent quantum random number generators offer the highest generation rates among semi-device-independent protocols. In reality, the protocol design is limited due to permissible measurement configurations. In this work, we propose a rigorous security proof framewor...

RedAmon 5.1.0

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

Flounder 0.1.1

Flounder turns modern coding agents into an end-to-end security audit system. Give it an authorized target boundary - a repository, source tree, package, deployed clue, or prior run - and the agent can prepare the workspace, read the code and supporting material, map the attack surface, dig into...

CVE MCP Server 0.2.0

CVE MCP Server is a production-grade Model Context Protocol MCP server that turns Claude into a full-spectrum security analyst. Instead of juggling 15+ browser tabs across NVD, EPSS, CISA KEV, Shodan, VirusTotal, and GreyNoise, ask Claude one question and get correlated intelligence in seconds...

Rising from the Ashes: How Agentic AI Is Unblocking Challenges in Cybersecurity

Security remains a high-cost challenge, with many problems historically deemed inefficient to address or effectively unsolvable. A significant number of these problems stem from labor-intensive tasks that create bottlenecks in defensive approaches. Agentic AI has the potential to alleviate these...

Maestro 0.17.1

Maestro is a cross-platform desktop app for orchestrating your fleet of AI agents and projects. It's a high-velocity solution for hackers who are juggling multiple projects in parallel. Designed for power users who live on the keyboard and rarely touch the mouse. Collaborate with AI to create...

Attacking Apple Display Co-Processor

While Apple's GPU architecture has received significant public scrutiny, the Display Co-Processor DCP remains a comparatively under-explored component despite its role in several high-profile iOS exploitation chains and jailbreaks. In this presentation, Ye Zhang examines the DCP from an attacker'...

FERRUM Windows Auditor

Ferrum is a Windows security research toolkit for local privilege escalation, persistence, COM hijacking, and attack surface enumeration. It is a Windows-first vulnerability research and security auditing framework written in Go. It is designed as a single binary, ferrum.exe, with modules...

Is It Real? Exploiting Virtual-Physical Discrimination Vulnerability in Mixed Reality

Consumer mixed reality MR headsets seamlessly blend virtual content into physical environments with sufficient fidelity that users may be unable to distinguish virtual objects from physical ones. We identify this virtual-physical discrimination vulnerability as an exploitable security primitive...

TGCM: Topic-Guided Generative Disentanglement of Interleaved APT Technique Sequences

In enterprise environments, multiple Advanced Persistent Threat APT campaigns often unfold concurrently, producing audit logs in which attack techniques across actors sources are interleaved over time. This setting naturally gives rise to an Unknown-K Interleaved Sequence Demixing UKISD problem:...

SNAS: A Multi-Layer Defense-In-Depth Architecture for Secure Egress in Sandboxed Workloads

Snowpark enables data engineering and AI/ML workloads in Snowflake by executing user-defined functions in secure sandboxes. Many of these workloads require external connectivity to access cloud APIs, external databases, or feature stores, creating a dependability challenge: how to provide...

Graph Neural Networks at War: Integrating Cybersecurity and Drone Intelligence in the Israeli-Iranian Conflict

Physical cyber systems have brought about new threats and challenges in detection and immediate response. This study examines how Graph Neural Networks GNNs can be used to aid cybersecurity and drone management in a physical cyber system comprising of cyber intrusions and unmanned aerial vehicles...