Russian State Actors Are Compromising IP Cameras in Europe for Military Purposes

Intelligence from the Netherlands General Intelligence and Security Service AIVD and the Netherlands Defence Intelligence and Security Service MIVD - the Dutch services - illustrates that Russian state actors are systematically conducting digital espionage operations via IP cameras cameras with...

Specter 2.0

Specter turns your Flipper Zero into a pocket counter-surveillance bug-sweep for active 13.56 MHz NFC readers - a hidden card skimmer slipped into a payment terminal, a covert reader behind a door panel, a rogue logger taped under a desk. It passively senses the RF carrier that any powered-on...

CryptanalysisBench: Can LLMs Do Cryptanalysis?

Cryptanalysis - the task of finding attacks against cryptographic schemes - sits at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest. Cryptanalysis represents both a clean testbed for frontier reasoning as practical attacks can be...

RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning

Edge Artificial Intelligence of Things AIoT systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory RRAM is an attractive substrate for efficient AIoT thanks to its multi-bit storage and compute-in-memory CiM capabilities, while its...

Towards an Automated Test of LLM Security Knowledge

Large language models LLMs are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM performance on security tasks is an active area of measurement and research, often with a focus on identifying areas in which LLM security "knowledge'' may be...

tcpreplay 4.5.3

tcpreplay is a BSD-style licensed tool to replay saved tcpdump files at arbitrary speeds. It provides a variety of features for replaying traffic for both passive sniffer devices as well as inline devices such as routers, firewalls, and intrusion detection systems. Many NIDSs fare poorly when...

Hybrid Latent-Structural Fusion (HLSF) for Cyber Anomaly Detection

Malicious anomalous activity detection is a fundamental challenge for cyber security systems. Both tensor decomposition under statistical framework with CANDECOMP-PARAFAC alternating Poisson regression CP-APR and normalizing flows have proven to be powerful unsupervised machine learning methods...

Nimux 1.0.2

Nimux is a native command surface for authorized security assessments. It combines network enumeration, credential validation, Active Directory operations, Kerberos workflows, remote execution, file movement, secrets collection, DCSync, GPO operations, database clients, and SOCKS routing into one...

Stegano 3.0.0

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...

Residual Observability and Attack Detectability in Encrypted OPC UA Traffic

OPC Unified Architecture OPC UA encryption conceals application-layer semantics and restricts intrusion detection to residual communication structure. Although machine learning-based intrusion detection systems IDSs can detect attacks in encrypted OPC UA traffic, the relationship between residual...

(A)ISpy: Parasitic Trojans for Machine Learning Infrastructure

Modern machine learning ML pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables acti...

RECEIPT: Deterministic, Reward-Hacking-Resistant Verification for White-Box Agentic XSS Discovery

Cross-Site Scripting XSS remains one of the most prevalent and damaging classes of web vulnerabilities. LLM-based coding agents offer a promising approach to XSS discovery by combining source-code reasoning with interactive testing against a running application. However, a coding agent's claims...

Chiral Analysis of Smart Contracts: Detecting Vulnerabilities from Relational Inconsistencies across Business Paths

Smart-contract vulnerabilities often arise from inconsistencies between business paths that should correspond to one another, such as single and batch entry points, direct and adapter-based flows, quote and execution paths, or inverse operations such as buy and sell. Existing analyzers are...

Insecure Coding Preferences in Long-Term Memory: Security Risks for LLM-Based Code Generation

LLM-based systems increasingly incorporate long-term memory to improve cross-session continuity. However, once insecure coding preferences are stored, they may silently influence security-critical decisions in subsequent generations. In this study, we conduct the first systematic empirical study ...

Salience Induction against Multi-Hop RAG Agents: Threat and Defense

Agentic retrieval-augmented generation RAG systems increasingly retrieve external evidence and orchestrate tools for knowledge-intensive applications. In Multi-Hop question answering, agents chain facts across documents. Existing defenses focus on content poisoning, which injects false facts, and...

Shared Vulnerabilities in Robustness-Optimized Defenses: One Breach Exposes the Family

Adversarial robustness optimization aims to preserve correct prediction under adversarial perturbations, and has produced substantial robustness gains through methods such as adversarial training and adversarial purification. However, we identify a new security risk: these gains can create shared...

Measuring and Evaluating the Performance of Generative AI Models for Scam Detection

Online scams continue to cause substantial financial and personal harm. As a result, detection systems based on Large Language Models LLMs have been integrated into security products ranging from email gateways and browser extensions to fraud-monitoring dashboards. As this adoption accelerates, a...

Isolation Failure from Shared Storage: Characterizing and Exploiting Page-Cache SCA Leakage across Containers and VMs

Modern cloud platforms increasingly combine strong software isolation mechanisms with shared hardware resources to improve performance and resource efficiency. Conventional containers do this by sharing the host kernel directly, whereas sandboxed runtimes e.g., gVisor and VM-based runtimes e.g.,...

Between Safe Boundaries: Exploiting Temporal Consistency for Jailbreaking Text-To-Video Generation Models

Recently, text-to-video T2V models have been widely deployed, sparking growing concerns over their robustness against jailbreak attacks. Existing jailbreak methods, mostly adapted from text-to-image attacks, suffer notable drawbacks when applied to T2V systems. They fail to fully leverage tempora...

A Multi-Model Hybrid Defense Approach against White-Box Adversarial Attacks in Computer Network Traffic

It is crucial to safeguard computer networks from evolving network security threats and unknown cyberattacks. An essential tool for protecting computer networks against unknown cyber threats is Network Intrusion Detection System NIDS. However, NIDS faces a major security concern due to its...

The Finite Key Effect of Side-Channel-Secure Quantum Key Distribution beyond Post-Selection Technique

By applying the framework of entropic uncertainty relation EUR and the Quantum Leftover Hash Lemma QLHL, we introduce a security-proof method for variable-length side-channel-secure SCS quantum key distribution QKD against coherent attacks. This method reframes composable security as a statistica...

ShadowPickle: Evading Machine Learning Model Scanners Via Stealthy Pickle Deserialization Attacks

Model hosting hubs e.g., Hugging Face are vulnerable to supply chain attacks that enable remote code execution on trusted user environments. Attackers often distribute malicious Pre-trained ML models PTMs via model hubs. In this paper, we present novel attacks against PTMs and model hubs called...

How Jailbreak Attacks Inform Safety Alignment: A Defender-Centric, Shapley-Based Evaluation of Jailbreak Contributions

Jailbreak attacks on large language models are usually evaluated by attacker-centric metrics such as attack success rate ASR, yet an attack that breaks a model is not necessarily useful for improving its safety. We propose a defender-centric view of jailbreak evaluation, where attacks are evaluat...

DSA Nonce Vulnerabilities: An Interactive Analysis

Digital signatures are fundamental to identity authentication and data integrity in cybersecurity, and the NIST-standardized Digital Signature Algorithm DSA frequently appears in the cryptography track of CTF competitions. However, DSA relies on number theory, modular arithmetic, and large-intege...

Adaptive Incident Prioritization for Security Operations at Scale

Large security operations centers SOCs often face hundreds of active incidents per day, creating substantial cognitive and operational demands for analysts. Analysts must quickly decide which incidents deserve attention within long, constantly changing queues, yet incidents are commonly ordered b...

Federated Lightweight Intrusion Detection in Drone Swarms with Knowledge Distillation

Drone swarms are increasingly deployed in critical applications such as surveillance, disaster response, and infrastructure monitoring. However, their reliance on open communication channels and their limited computational resources make them vulnerable to a wide range of cyber-threats. There is ...

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...

How Do You Choose Your AI Component? an Interview Study of Secure AI Integration in Practice

The increasing adoption of Large Language Models LLMs as AI components in modern software systems introduces distinct security risks to the software supply chain. While many considerations and safety mechanisms are in place for components of the traditional software supply chain, the recent rapid...

Federated Learning and LLM-Driven Threat Intelligence for Zero Trust IoT Architecture

While the Internet of Things IoT has become essential, they introduced serious security and privacy challenges, especially for mission-critical environments. Legacy devices are vulnerable to viruses, data breaches, and unauthorized access, and updating these devices would be infeasibly costly. As...

Code-Poisoning Property Inference Attacks

The flourishing code hosting platforms and coding agents enable even beginners with private data to build tailored Machine Learning ML models using available code quickly. The training data for ML models, often regarded as private property e.g., clinical records, transaction information, is at...

Towards Secure and Trustworthy DAOs for Cross-Chain Governance

Cross-chain DAOs face unique security challenges that go beyond traditional single-chain vulnerabilities. This paper identifies and categorizes four critical attack vectors in cross-chain DAO governance: bribery attacks, token control exploits, human-computer interaction deceptions, and protocol...

Converging Safety and Security: IO-Link Wireless and OPC UA over 5G under PrEN 50742

The integration of wireless communication technologies in industrial automation offers greater flexibility, but also exposes safety systems to a broader threat vector. Emerging regulations, such as the draft standard prEN 50742, mandate the convergence of functional safety and cybersecurity by...

AI Watermark Evidence Fails Forensic Readiness: An Empirical Evaluation

Governments are increasingly mandating that LLM-generated content carry watermarks. The EU AI Act calls for markings that are "sufficiently reliable and robust." California's SB 942 requires disclosure that is "permanent or extraordinarily difficult to remove." Both mandates rest on an untested...

DoSQ: A Cross-Layer Denial of Service Quality Attack by Exploiting Side Channels in 5G NR

The 3rd Generation Partnership Project 3GPP's Fifth Generation New Radio 5G NR is critical to supporting mission-critical services. However, 5G systems are vulnerable to smart jamming attacks that can propagate to applications running on top of these networks i.e., cross-layer. The 5G gNB...

DICOMHawk: A Cyber Deception Framework for Medical Imaging Infrastructure

Cyber-attacks against exposed healthcare infrastructure threaten sensitive patient data and clinical operations, yet existing defensive tools for DICOM-based medical imaging systems provide limited interaction and are easily fingerprinted. We introduce DICOMHawk, a cyber-deception framework that...

Natural Backdoor Attacks on Speech Recognition Models

With the rapid development of deep learning, its vulnerability has gradually emerged in recent years. This work focuses on backdoor attacks on speech recognition systems. We adopt sounds that are ordinary in nature or in our daily life as triggers for natural backdoor attacks. We conduct...

Vogls: A Fast Interactive Full-Timing Simulator for Pre-Silicon Power Side-Channel Analysis

Designing hardware circuits resistant to side-channel attacks increasingly relies on simulation to predict device leakage before fabrication. Current functional verification simulators are designed for extended correctness-checking runs and are ill-suited for producing large numbers of short trac...

The Language of Security: How Prompt Syntax Shapes Secure Code Generation in Open LLMs

Large Language Models LLMs are increasingly used for source code generation despite their outputs often exhibiting security vulnerabilities. Prior work shows that prompt engineering can mitigate such risks, yet 1 they focused on high-level prompting strategies, neglecting recent evidence that...

TaintRadar: Semantic-Aware Taint-Style Vulnerability Detection Via Augmented Code Property Graphs

Despite significant advances, static vulnerability analysis suffers from three critical limitations: coarse sanitization modeling, which treats validation as a binary barrier; database blindness, which breaks taint tracking across persistence layers; and shallow object-oriented analysis, which...

Nimux 1.0.1

Nimux is a native command surface for authorized security assessments. It combines network enumeration, credential validation, Active Directory operations, Kerberos workflows, remote execution, file movement, secrets collection, DCSync, GPO operations, database clients, and SOCKS routing into one...

Signal-Based Model Access Risk Analysis for AI System Operations Security

Artificial intelligence AI systems are now ubiquitous across domains such as security, finance, healthcare, consumer technology, and large-scale cloud services, where they process massive volumes of data and make consequential decisions daily. This widespread adoption has created a broad attack...

Reliable Remediation Impact Prediction for Black-Box Security Ratings

Security rating platforms summarize externally observable cyber exposure and are expected to help organizations prioritize remediation. A platform may want to tell an organization how a candidate remediation action would affect its score, but repeatedly exposing exact score responses can reveal...

Revisiting Data-Driven Dynamic Security Assessment with a Tabular Foundation Model

Data-driven pre-fault dynamic security assessment DSA rapidly evaluates the dynamic risk of credible contingencies on a power system using machine learning. Existing approaches face two limitations. First, they require a large labelled database for training, with a separate model trained, tuned,...

Evaluating Open-Weight LLMs for Generating Structured Threat Information for Autonomous Vehicle Vulnerabilities

Connected and Autonomous Vehicles CAVs rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and telematics units, where vulnerabilities can compromise assets, users, and vehicle operations. These vulnerabilities are...

A Control-Driven Framework for Secure SaaS Onboarding in Regulated Enterprises

As enterprises increasingly adopt Software-as-a-Service SaaS platforms for mission-critical functions, onboarding these services has emerged as a complex challenge extending well beyond procurement and basic security review. In regulated environments, SaaS onboarding must address multiple...

Fuzz'EMup: Leveraging EM Side-Channel Emanation to Guide Black-Box Embedded Firmware Fuzzing

As IoT and embedded devices proliferate across various domains, securing their firmware has become critical. Fuzzing offers a systematic approach to uncovering vulnerabilities in firmware, and coverage feedback can improve its effectiveness by guiding exploration. However, many devices make...

Enhanced Multi-Class DDoS Attack Identification Using a Meta-Learning Ensemble

Distributed Denial of Service DDoS attacks continue to pose significant threats to network availability and security. While many detection systems focus on binary classification attack vs. benign, effective mitigation often requires identifying the specific type of DDoS attack. This paper...

Routing Ceilings Are Domain-Independent: Structural Prior Injection in Code Security Vulnerability Detection

Large language models LLMs exhibit a well-documented gap between latent capability and consistent activation: the router hypothesis posits that models possess the knowledge to solve a task but lack reliable internal routing to activate it. Prior work in formal mathematical reasoning SAIR, C�zares...

SQUIRO: A Framework for Security-Aware Quantum-Classical Scheduling on Kubernetes

Distributed infrastructure schedulers traditionally optimise capacity, locality, and cost, but provide limited support for security posture and emerging quantum-classical workloads. As hybrid quantum-classical computing becomes increasingly practical and post-quantum security requirements begin t...

CodeQL 2.26.1

Discover vulnerabilities across a codebase with CodeQL, an industry-leading semantic code analysis engine. CodeQL lets you query code as though it were data. Write a query to find all variants of a vulnerability, eradicating it forever. Then share your query to help others do the same...