Compile-Time Fully Homomorphic Encryption of Vectors: Eliminating Online Encryption Via Algebraic Basis Synthesis

Whitepaper called Compile-Time Fully Homomorphic Encryption Of Vectors: Eliminating Online Encryption Via Algebraic Basis Synthesis...

GRAudit Grep Auditing Tool 3.9

Graudit is a simple script and signature sets that allows you to find potential security flaws in source code using the GNU utility, grep. It's comparable to other static analysis applications like RATS, SWAAT, and flaw-finder while keeping the technical requirements to a minimum and being very...

WordPress Madara 2.2.2 Local File Inclusion

WordPress Madara theme versions 2.2.2 and below suffer from a local file inclusion vulnerability...

OpenSSL Security Advisory 20250522

OpenSSL Security Advisory 20250522 - Use of -addreject option with the openssl x509 application adds a trusted use instead of a rejected use for a certificate...

ReCopilot: Reverse Engineering Copilot in Binary Analysis

Binary analysis plays a pivotal role in security domains such as malware detection and vulnerability discovery, yet it remains labor-intensive and heavily reliant on expert knowledge. General-purpose large language models LLMs perform well in programming analysis on source code, while...

SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches Via Super-Resolution GAN Models

As vision-based machine learning models are increasingly integrated into autonomous and cyber-physical systems, concerns about physical adversarial patch attacks are growing. While state-of-the-art defenses can achieve certified robustness with minimal impact on utility against highly-concentrate...

Harry Potter Is Still Here! Probing Knowledge Leakage in Targeted Unlearned Large Language Models Via Automated Adversarial Prompting

This work presents LURK Latent UnleaRned Knowledge, a novel framework that probes for hidden retained knowledge in unlearned LLMs through adversarial suffix prompting. LURK automatically generates adversarial prompt suffixes designed to elicit residual knowledge about the Harry Potter domain, a...

CAIN: Hijacking LLM-Humans Conversations Via a Two-Stage Malicious System Prompt Generation and Refining Framework

Large language models LLMs have advanced many applications, but are also known to be vulnerable to adversarial attacks. In this work, we introduce a novel security threat: hijacking AI-human conversations by manipulating LLMs' system prompts to produce malicious answers only to specific targeted...

Verifying Differentially Private Median Estimation

Differential Privacy DP is a robust privacy guarantee that is widely employed in private data analysis today, finding broad application in domains such as statistical query release and machine learning. However, DP achieves privacy by introducing noise into data or query answers, which malicious...

An End-To-End Model for Logits Based Large Language Models Watermarking

The rise of LLMs has increased concerns over source tracing and copyright protection for AIGC, highlighting the need for advanced detection technologies. Passive detection methods usually face high false positives, while active watermarking techniques using logits or sampling manipulation offer...

Privacy-Aware Cyberterrorism Network Analysis Using Graph Neural Networks and Federated Learning

Cyberterrorism poses a formidable threat to digital infrastructures, with increasing reliance on encrypted, decentralized platforms that obscure threat actor activity. To address the challenge of analyzing such adversarial networks while preserving the privacy of distributed intelligence data, we...

Poster: Towards an Automated Security Testing Framework for Industrial UEs

With the ongoing adoption of 5G for communication in industrial systems and critical infrastructure, the security of industrial UEs such as 5G-enabled industrial robots becomes an increasingly important topic. Most notably, to meet the stringent security requirements of industrial deployments,...

Can ChatGPT Perform Image Splicing Detection? A Preliminary Study

Multimodal Large Language Models MLLMs like GPT-4V are capable of reasoning across text and image modalities, showing promise in a variety of complex vision-language tasks. In this preliminary study, we investigate the out-of-the-box capabilities of GPT-4V in the domain of image forensics,...

Advancing Security with Digital Twins: a Comprehensive Survey

The proliferation of electronic devices has greatly transformed every aspect of human life, such as communication, healthcare, transportation, and energy. Unfortunately, the global electronics supply chain is vulnerable to various attacks, including piracy of intellectual properties, tampering,...

CoTSRF: Utilize Chain of Thought As Stealthy and Robust Fingerprint of Large Language Models

Despite providing superior performance, open-source large language models LLMs are vulnerable to abusive usage. To address this issue, recent works propose LLM fingerprinting methods to identify the specific source LLMs behind suspect applications. However, these methods fail to provide stealthy...

LogStamping: a Blockchain-Based Log Auditing Approach for Large-Scale Systems

Log management is crucial for ensuring the security, integrity, and compliance of modern information systems. Traditional log management solutions face challenges in achieving tamper-proofing, scalability, and real-time processing in distributed environments. This paper presents a blockchain-base...

Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models

Large Language Models LLMs are increasingly equipped with capabilities of real-time web search and integrated with protocols like Model Context Protocol MCP. This extension could introduce new security vulnerabilities. We present a systematic investigation of LLM vulnerabilities to hidden...

Timestamp Manipulation: Timestamp-Based Nakamoto-Style Blockchains Are Vulnerable

Nakamoto consensus are the most widely adopted decentralized consensus mechanism in cryptocurrency systems. Since it was proposed in 2008, many studies have focused on analyzing its security. Most of them focus on maximizing the profit of the adversary. Examples include the selfish mining attack ...

MTSA: Multi-Turn Safety Alignment for LLMs through Multi-Round Red-Teaming

Whitepaper called MTSA: Multi-Turn Safety Alignment For LLMs Through Multi-Round Red-Teaming...

A Scalable Hierarchical Intrusion Detection System for Internet of Vehicles

Due to its nature of dynamic, mobility, and wireless data transfer, the Internet of Vehicles IoV is prone to various cyber threats, ranging from spoofing and Distributed Denial of Services DDoS attacks to malware. To safeguard the IoV ecosystem from intrusions, malicious activities, policy...

Enhancing Meme Token Market Transparency: a Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation

Meme tokens represent a distinctive asset class within the cryptocurrency ecosystem, characterized by high community engagement, significant market volatility, and heightened vulnerability to market manipulation. This paper introduces an innovative approach to assessing liquidity risk in meme tok...

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance

Large language models LLMs are increasingly applied in fields such as finance, education, and governance due to their ability to generate human-like text and adapt to specialized tasks. However, their widespread adoption raises critical concerns about data privacy and security, including the risk...

TP-Link Archer AX50 Buffer Overflow

The TP-Link Archer AX50 router is vulnerable to a stack-based buffer overflow on its firmware version 1.0.14 Build 20240108 rel.426554555, leading to remote code execution both in the LAN and in the WAN side. This vulnerability is the same as CVE-2020-10881, found by the Flashback team and largel...

Secure Parsing and Serializing with Separation Logic Applied to CBOR, CDDL, and COSE

Incorrect handling of security-critical data formats, particularly in low-level languages, are the root cause of many security vulnerabilities. Provably correct parsing and serialization tools that target languages like C can help. Towards this end, we present PulseParse, a library of verified...

Zero-Trust Mobility-Aware Authentication Framework for Secure Vehicular Fog Computing Networks

Vehicular Fog Computing VFC is a promising paradigm to meet the low-latency and high-bandwidth demands of Intelligent Transportation Systems ITS. However, dynamic vehicle mobility and diverse trust boundaries introduce critical security challenges. This paper presents a novel Zero-Trust...

AI-Driven Dynamic Firewall Optimization Using Reinforcement Learning for Anomaly Detection and Prevention

The growing complexity of cyber threats has rendered static firewalls increasingly ineffective for dynamic, real-time intrusion prevention. This paper proposes a novel AI-driven dynamic firewall optimization framework that leverages deep reinforcement learning DRL to autonomously adapt and update...

Versatile Quantum-Safe Hybrid Key Exchange and Its Application to MACsec

Advancements in quantum computing pose a significant threat to most of the cryptography currently deployed. Fortunately, cryptographic building blocks to mitigate the threat are already available; mostly based on post-quantum and quantum cryptography, but also on symmetric cryptography techniques...

Quantum-Resilient Blockchain for Secure Transactions in UAV-Assisted Smart Agriculture Networks

The integration of unmanned aerial vehicles UAVs into smart agriculture has enabled real-time monitoring, data collection, and automated farming operations. However, the high mobility, decentralized nature, and low-power communication of UAVs pose significant security challenges, particularly in...

CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Execution

Large Language Model LLM agents can automate cybersecurity tasks and can adapt to the evolving cybersecurity landscape without re-engineering. While LLM agents have demonstrated cybersecurity capabilities on Capture-The-Flag CTF competitions, they have two key limitations: accessing latest...

An Efficient Private GPT Never Autoregressively Decodes

The wide deployment of the generative pre-trained transformer GPT has raised privacy concerns for both clients and servers. While cryptographic primitives can be employed for secure GPT inference to protect the privacy of both parties, they introduce considerable performance overhead.To accelerat...

Privacy-Preserving Socialized Recommendation Based on Multi-View Clustering in a Cloud Environment

Recommendation as a service has improved the quality of our lives and plays a significant role in variant aspects. However, the preference of users may reveal some sensitive information, so that the protection of privacy is required. In this paper, we propose a privacy-preserving, socialized,...

Blind Spot Navigation: Evolutionary Discovery of Sensitive Semantic Concepts for LVLMs

Whitepaper called Blind Spot Navigation: Evolutionary Discovery Of Sensitive Semantic Concepts For LVLMs...

Federated Learning-Enhanced Blockchain Framework for Privacy-Preserving Intrusion Detection in Industrial IoT

Industrial Internet of Things IIoT systems have become integral to smart manufacturing, yet their growing connectivity has also exposed them to significant cybersecurity threats. Traditional intrusion detection systems IDS often rely on centralized architectures that raise concerns over data...

Pura: an Efficient Privacy-Preserving Solution for Face Recognition

Face recognition is an effective technology for identifying a target person by facial images. However, sensitive facial images raises privacy concerns. Although privacy-preserving face recognition is one of potential solutions, this solution neither fully addresses the privacy concerns nor is...

Model Checking the Security of the Lightning Network

Payment channel networks are an approach to improve the scalability of blockchain-based cryptocurrencies. The Lightning Network is a payment channel network built for Bitcoin that is already used in practice. Because the Lightning Network is used for transfer of financial value, its security in t...

FragFake: a Dataset for Fine-Grained Detection of Edited Images with Vision Language Models

Fine-grained edited image detection of localized edits in images is crucial for assessing content authenticity, especially given that modern diffusion models and image editing methods can produce highly realistic manipulations. However, this domain faces three challenges: 1 Binary classifiers yie...

Scalable Defense against In-The-Wild Jailbreaking Attacks with Safety Context Retrieval

Large Language Models LLMs are known to be vulnerable to jailbreaking attacks, wherein adversaries exploit carefully engineered prompts to induce harmful or unethical responses. Such threats have raised critical concerns about the safety and reliability of LLMs in real-world deployment. While...

VoteMate: a Decentralized Application for Scalable Electronic Voting on EVM-Based Blockchain

Voting is a cornerstone of democracy, allowing citizens to express their will and make collective decisions. With advancing technology, online voting is gaining popularity as it enables voting from anywhere with Internet access, eliminating the need for printed ballots or polling stations. Howeve...

Quantum Steganography Using Catalytic and Entanglement-Assisted Quantum Codes

Steganography is the technique for transmitting a secret message by employing subterfuge to conceal it in innocent-looking data, rather than by overt security measures as in cryptography. Typically, non-degenerate quantum error-correcting codes QECCs are used as the cover medium, with the stego...

Defining Atomicity (And Integrity) for Snapshots of Storage in Forensic Computing

The acquisition of data from main memory or from hard disk storage is usually one of the first steps in a forensic investigation. We revisit the discussion on quality criteria for "forensically sound" acquisition of such storage and propose a new way to capture the intent to acquire an...

Integrating Robotic Navigation with Blockchain: a Novel PoS-Based Approach for Heterogeneous Robotic Teams

This work explores a novel integration of blockchain methodologies with Wide Area Visual Navigation WAVN to address challenges in visual navigation for a heterogeneous team of mobile robots deployed for unstructured applications in agriculture, forestry, etc. Focusing on overcoming challenges suc...

Outsourcing SAT-Based Verification Computations in Network Security

The emergence of cloud computing gives huge impact on large computations. Cloud computing platforms offer servers with large computation power to be available for customers. These servers can be used efficiently to solve problems that are complex by nature, for example, satisfiability SAT problem...

Dynamic Spectrum Sharing Based on the Rentable NFT Standard ERC4907

Centralized Dynamic Spectrum Sharing DSS faces challenges like data security, high management costs, and limited scalability. To address these issues, a blockchain-based DSS scheme has been proposed in this paper. First, we utilize the ERC4907 standard to mint Non-Fungible Spectrum Tokens NFSTs...

GDPRShield: AI-Powered GDPR Support for Software Developers in Small and Medium-Sized Enterprises

With the rapid increase in privacy violations in modern software development, regulatory frameworks such as the General Data Protection Regulation GDPR have been established to enforce strict data protection practices. However, insufficient privacy awareness among SME software developers...

Securing RAG: a Risk Assessment and Mitigation Framework

Retrieval Augmented Generation RAG has emerged as the de facto industry standard for user-facing NLP applications, offering the ability to integrate data without re-training or fine-tuning Large Language Models LLMs. This capability enhances the quality and accuracy of responses but also introduc...

PRUNE: a Patching Based Repair Framework for Certifiable Unlearning of Neural Networks

It is often desirable to remove a.k.a. unlearn a specific part of the training data from a trained neural network model. A typical application scenario is to protect the data holder's right to be forgotten, which has been promoted by many recent regulation rules. Existing unlearning methods invol...

Reliable Disentanglement Multi-View Learning against View Adversarial Attacks

Trustworthy multi-view learning has attracted extensive attention because evidence learning can provide reliable uncertainty estimation to enhance the credibility of multi-view predictions. Existing trusted multi-view learning methods implicitly assume that multi-view data is secure. However, in...

Zeek 7.0.8

Zeek is a powerful network analysis framework that is much different from the typical IDS you may know. While focusing on network security monitoring, Zeek provides a comprehensive platform for more general network traffic analysis as well. Well grounded in more than 15 years of research, Zeek ha...

MAPS: a Multilingual Benchmark for Global Agent Performance and Security

Agentic AI systems, which build on Large Language Models LLMs and interact with tools and memory, have rapidly advanced in capability and scope. Yet, since LLMs have been shown to struggle in multilingual settings, typically resulting in lower performance and reduced safety, agentic systems risk...

Extensible Post Quantum Cryptography Based Authentication

Cryptography underpins the security of modern digital infrastructure, from cloud services to health data. However, many widely deployed systems will become vulnerable after the advent of scalable quantum computing. Although quantum-safe cryptographic primitives have been developed, such as...