Scout: Leveraging Large Language Models for Rapid Digital Evidence Discovery

Recent technological advancements and the prevalence of technology in day to day activities have caused a major increase in the likelihood of the involvement of digital evidence in more and more legal investigations. Consumer-grade hardware is growing more powerful, with expanding memory and...

CASCADE: LLM-Powered JavaScript Deobfuscator at Google

Software obfuscation, particularly prevalent in JavaScript, hinders code comprehension and analysis, posing significant challenges to software testing, static analysis, and malware detection. This paper introduces CASCADE, a novel hybrid approach that integrates the advanced coding capabilities o...

Development of a Standardized Testing Environment for QRNGs Based on Semiconductor Laser Phase Noise

Quantum random number generators QRNGs based on semiconductor laser phase noise are an inexpensive and efficient resource for true random numbers. Commercially available technology allows for designing QRNG setups tailored to specific use cases. However, it is important to constantly monitor...

Leveraging Trustworthy AI for Automotive Security in Multi-Domain Operations: Towards a Responsive Human-AI Multi-Domain Task Force for Cyber Social Security

Multi-Domain Operations MDOs emphasize cross-domain defense against complex and synergistic threats, with civilian infrastructures like smart cities and Connected Autonomous Vehicles CAVs emerging as primary targets. As dual-use assets, CAVs are vulnerable to Multi-Surface Threats MSTs,...

SynthCTI: LLM-Driven Synthetic CTI Generation to Enhance MITRE Technique Mapping

Cyber Threat Intelligence CTI mining involves extracting structured insights from unstructured threat data, enabling organizations to understand and respond to evolving adversarial behavior. A key task in CTI mining is mapping threat descriptions to MITRE ATT&CK techniques. However, this process...

SVAgent: AI Agent for Hardware Security Verification Assertion

Verification using SystemVerilog assertions SVA is one of the most popular methods for detecting circuit design vulnerabilities. However, with the globalization of integrated circuit design and the continuous upgrading of security requirements, the SVA development model has exposed major...

Quantum Skyshield: Quantum Key Distribution and Post-Quantum Authentication for Low-Altitude Wireless Networks in Adverse Skies

Recently, low-altitude wireless networks LAWNs have emerged as a critical backbone for supporting the low-altitude economy, particularly with the densification of unmanned aerial vehicles UAVs and high-altitude platforms HAPs. To meet growing data demands, some LAWN deployments incorporate...

LRCTI: a Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification

Verifying the credibility of Cyber Threat Intelligence CTI is essential for reliable cybersecurity defense. However, traditional approaches typically treat this task as a static classification problem, relying on handcrafted features or isolated deep learning models. These methods often lack the...

A Review of Privacy Metrics for Privacy-Preserving Synthetic Data Generation

Privacy Preserving Synthetic Data Generation PP-SDG has emerged to produce synthetic datasets from personal data while maintaining privacy and utility. Differential privacy DP is the property of a PP-SDG mechanism that establishes how protected individuals are when sharing their sensitive data. I...

Multi-Trigger Poisoning Amplifies Backdoor Vulnerabilities in LLMs

Recent studies have shown that Large Language Models LLMs are vulnerable to data poisoning attacks, where malicious training examples embed hidden behaviours triggered by specific input patterns. However, most existing works assume a phrase and focus on the attack's effectiveness, offering limite...

MalCodeAI: Autonomous Vulnerability Detection and Remediation Via Language Agnostic Code Reasoning

The growing complexity of cyber threats and the limitations of traditional vulnerability detection tools necessitate novel approaches for securing software systems. We introduce MalCodeAI, a language-agnostic, multi-stage AI pipeline for autonomous code security analysis and remediation. MalCodeA...

Crypto-Assisted Graph Degree Sequence Release under Local Differential Privacy

Whitepaper called Crypto-Assisted Graph Degree Sequence Release Under Local Differential Privacy...

DVFS: a Dynamic Verifiable Fuzzy Search Service for Encrypted Cloud Data

Cloud storage introduces critical privacy challenges for encrypted data retrieval, where fuzzy multi-keyword search enables approximate matching while preserving data confidentiality. Existing solutions face fundamental trade-offs between security and efficiency: linear-search mechanisms provide...

Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats

Protecting cyberspace requires not only advanced tools but also a shift in how we reason about threats, trust, and autonomy. Traditional cybersecurity methods rely on manual responses and brittle heuristics. To build proactive and intelligent defense systems, we need integrated theoretical...

When Developer Aid Becomes Security Debt: a Systematic Analysis of Insecure Behaviors in LLM Coding Agents

LLM-based coding agents are rapidly being deployed in software development, yet their security implications remain poorly understood. These agents, while capable of accelerating software development, may inadvertently introduce insecure practices. We conducted the first systematic security...

KeyDroid: a Large-Scale Analysis of Secure Key Storage in Android Apps

Most contemporary mobile devices offer hardware-backed storage for cryptographic keys, user data, and other sensitive credentials. Such hardware protects credentials from extraction by an adversary who has compromised the main operating system, such as a malicious third-party app. Since 2011,...

GPUHammer: Rowhammer Attacks on GPU Memories Are Practical

Rowhammer is a read disturbance vulnerability in modern DRAM that causes bit-flips, compromising security and reliability. While extensively studied on Intel and AMD CPUs with DDR and LPDDR memories, its impact on GPUs using GDDR memories, critical for emerging machine learning applications,...

RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation

Retrieval-Augmented Generation RAG enhances large language models LLMs by retrieving external data to mitigate hallucinations and outdated knowledge issues. Benefiting from the strong ability in facilitating diverse data sources and supporting faithful reasoning, knowledge graphs KGs have been...

Shuffling for Semantic Secrecy

Deep learning draws heavily on the latest progress in semantic communications. The present paper aims to examine the security aspect of this cutting-edge technique from a novel shuffling perspective. Our goal is to improve upon the conventional secure coding scheme to strike a desirable tradeoff...

Suricata IDPE 7.0.11

Suricata is a network intrusion detection and prevention engine developed by the Open Information Security Foundation and its supporting vendors. The engine is multi-threaded and has native IPv6 support. It's capable of loading existing Snort rules and signatures and supports the Barnyard and...

Model Inversion Attacks on Llama 3: Extracting PII from Large Language Models

Large language models LLMs have transformed natural language processing, but their ability to memorize training data poses significant privacy risks. This paper investigates model inversion attacks on the Llama 3.2 model, a multilingual LLM developed by Meta. By querying the model with carefully...

Adaptive Malware Detection Using Sequential Feature Selection: a Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification

Traditional malware detection methods exhibit computational inefficiency due to exhaustive feature extraction requirements, creating accuracy-efficiency trade-offs that limit real-time deployment. We formulate malware classification as a Markov Decision Process with episodic feature acquisition a...

Rethinking and Exploring String-Based Malware Family Classification in the Era of LLMs and RAG

Malware Family Classification MFC aims to identify the fine-grained family e.g., GuLoader or BitRAT to which a potential malware sample belongs, in contrast to malware detection or sample classification that predicts only an Yes/No. Accurate family identification can greatly facilitate automated...

S-Leak: Leakage-Abuse Attack against Efficient Conjunctive SSE Via S-Term Leakage

Conjunctive Searchable Symmetric Encryption CSSE enables secure conjunctive searches over encrypted data. While leakage-abuse attacks LAAs against single-keyword SSE have been extensively studied, their extension to conjunctive queries faces a critical challenge: the combinatorial explosion of...

Securing Mixed Rust with Hardware Capabilities

The Rust programming language enforces three basic Rust principles, namely ownership, borrowing, and AXM Aliasing Xor Mutability to prevent security bugs such as memory safety violations and data races. However, Rust projects often have mixed code, i.e., code that also uses unsafe Rust, FFI Forei...

WordPress Migration, Backup, Staging – WPvivid Backup and Migration 0.9.116 Shell Upload

WordPress Migration, Backup, Staging – WPvivid Backup and Migration plugin versions 0.9.116 and below are vulnerable to arbitrary file uploads due to missing file type validation in the wpvividuploadimportfiles function. This allows authenticated attackers Administrator-level and above to upload...

Holographic Projection and Cyber Attack Surface: a Physical Analogy for Digital Security

This article presents an in-depth exploration of the analogy between the Holographic Principle in theoretical physics and cyber attack surfaces in digital security. Building on concepts such as black hole entropy and AdS/CFT duality, it highlights how complex infrastructures project their...

Wing FTP Remote Code Execution

Wing FTP versions prior to 7.4.4 proof of concept remote code execution exploit...

OpenSSL Toolkit 3.2.5

OpenSSL is a robust, fully featured Open Source toolkit implementing the Secure Sockets Layer and Transport Layer Security protocols with full-strength cryptography world-wide. This is the 3.2 release supported until 23rd November 2025...

American Fuzzy Lop plus plus 4.33c

Google's American Fuzzy Lop is a brute-force fuzzer coupled with an exceedingly simple but rock-solid instrumentation-guided genetic algorithm. afl++ is a superior fork to Google's afl. It has more speed, more and better mutations, more and better instrumentation, custom module support, etc...

Linear Stability Analysis for a System of Singular Amplitude Equations Arising in Biomorphology

We study linear stability of exponential periodic solutions of a system of singular amplitude equations associated with convective Turing bifurcation in the presence of conservation laws, as arises in modern biomorphology models, binary fluids, and elsewhere. Consisting of a complex Ginzburg-Land...

Vite Arbitrary File Read

Vite suffers from an arbitrary file read vulnerability. Versions prior to 6.2.3, 6.1.2, 6.0.12, 5.4.15, and 4.5.10 are affected...

AppleAVD AV1_Syntax::f Out-Of-Bounds Read

There is an issue in AppleAVD kernel extension with decoding AV1 video files that could potentially be used to read out-of bound data or potentially cause a kernel crash when rendering a malformed video file. The issue was observed on macOS Sonoma 14.5...

Can One Safety Loop Guard Them All? Agentic Guard Rails for Federated Computing

We propose Guardian-FC, a novel two-layer framework for privacy preserving federated computing that unifies safety enforcement across diverse privacy preserving mechanisms, including cryptographic back-ends like fully homomorphic encryption FHE and multiparty computation MPC, as well as statistic...

The Impact of the Russia-Ukraine Conflict on the Cloud Computing Risk Landscape

The Russian invasion of Ukraine has fundamentally altered the information technology IT risk landscape, particularly in cloud computing environments. This paper examines how this geopolitical conflict has accelerated data sovereignty concerns, transformed cybersecurity paradigms, and reshaped clo...

WebGuard++: Interpretable Malicious URL Detection Via Bidirectional Fusion of HTML Subgraphs and Multi-Scale Convolutional BERT

URL+HTML feature fusion shows promise for robust malicious URL detection, since attacker artifacts persist in DOM structures. However, prior work suffers from four critical shortcomings: 1 incomplete URL modeling, failing to jointly capture lexical patterns and semantic context; 2 HTML graph...

Decompiling Smart Contracts with a Large Language Model

The widespread lack of broad source code verification on blockchain explorers such as Etherscan, where despite 78,047,845 smart contracts deployed on Ethereum as of May 26, 2025, a mere 767,520 1% are open source, presents a severe impediment to blockchain security. This opacity necessitates the...

Deep CNN Face Matchers Inherently Support Revocable Biometric Templates

One common critique of biometric authentication is that if an individual's biometric is compromised, then the individual has no recourse. The concept of revocable biometrics was developed to address this concern. A biometric scheme is revocable if an individual can have their current enrollment i...

Shrinking the Generation-Verification Gap with Weak Verifiers

Verifiers can improve language model capabilities by scoring and ranking responses from generated candidates. Currently, high-quality verifiers are either unscalable e.g., humans or limited in utility e.g., tools like Lean. While LM judges and reward models have become broadly useful as...

SmartHome-Bench: a Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language Models

Video anomaly detection VAD is essential for enhancing safety and security by identifying unusual events across different environments. Existing VAD benchmarks, however, are primarily designed for general-purpose scenarios, neglecting the specific characteristics of smart home applications. To...

InfoFlood: Jailbreaking Large Language Models with Information Overload

Large Language Models LLMs have demonstrated remarkable capabilities across various domains. However, their potential to generate harmful responses has raised significant societal and regulatory concerns, especially when manipulated by adversarial techniques known as "jailbreak" attacks. Existing...

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models

Vision-Language Models VLMs such as CLIP have demonstrated remarkable capabilities in understanding relationships between visual and textual data through joint embedding spaces. Despite their effectiveness, these models remain vulnerable to adversarial attacks, particularly in the image modality,...

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT

The rapid expansion of the Internet of Things IoT has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems IDS. Traditional IDS models often overlook the temporal characteristics of network traffic, limiting their effectiveness in early thre...

TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs

Chip manufacturing is a complex process, and to achieve a faster time to market, an increasing number of untrusted third-party tools and designs from around the world are being utilized. The use of these untrusted third party intellectual properties IPs and tools increases the risk of adversaries...

Watermarking Quantum Neural Networks Based on Sample Grouped and Paired Training

Quantum neural networks QNNs leverage quantum computing to create powerful and efficient artificial intelligence models capable of solving complex problems significantly faster than traditional computers. With the fast development of quantum hardware technology, such as superconducting qubits,...

Towards Reliable Forgetting: a Survey on Machine Unlearning Verification, Challenges, and Future Directions

With growing demands for privacy protection, security, and legal compliance e.g., GDPR, machine unlearning has emerged as a critical technique for ensuring the controllability and regulatory alignment of machine learning models. However, a fundamental challenge in this field lies in effectively...

Efficient Retail Video Annotation: a Robust Key Frame Generation Approach for Product and Customer Interaction Analysis

Accurate video annotation plays a vital role in modern retail applications, including customer behavior analysis, product interaction detection, and in-store activity recognition. However, conventional annotation methods heavily rely on time-consuming manual labeling by human annotators,...

Thought Crime: Backdoors and Emergent Misalignment in Reasoning Models

Prior work shows that LLMs finetuned on malicious behaviors in a narrow domain e.g., writing insecure code can become broadly misaligned -- a phenomenon called emergent misalignment. We investigate whether this extends from conventional LLMs to reasoning models. We finetune reasoning models on...

Screen Hijack: Visual Poisoning of VLM Agents in Mobile Environments

With the growing integration of vision-language models VLMs, mobile agents are now widely used for tasks like UI automation and camera-based user assistance. These agents are often fine-tuned on limited user-generated datasets, leaving them vulnerable to covert threats during the training process...

SoK: Stablecoin Designs, Risks, and the Stablecoin LEGO

Stablecoins have become significant assets in modern finance, with a market capitalization exceeding USD 246 billion May 2025. Yet, despite their systemic importance, a comprehensive and risk-oriented understanding of crucial aspects like their design trade-offs, security dynamics, and...