Securing Transformer-Based AI Execution Via Unified TEEs and Crypto-Protected Accelerators

Recent advances in Transformer models, e.g., large language models LLMs, have brought tremendous breakthroughs in various artificial intelligence AI tasks, leading to their wide applications in many security-critical domains. Due to their unprecedented scale and prohibitively high development cos...

LLMalMorph: on the Feasibility of Generating Variant Malware Using Large-Language-Models

Large Language Models LLMs have transformed software development and automated code generation. Motivated by these advancements, this paper explores the feasibility of LLMs in modifying malware source code to generate variants. We introduce LLMalMorph, a semi-automated framework that leverages...

Backscatter Device-Aided Integrated Sensing and Communication: a Pareto Optimization Framework

Integrated sensing and communication ISAC systems potentially encounter significant performance degradation in densely obstructed urban and non-line-of-sight scenarios, thus limiting their effectiveness in practical deployments. To deal with these challenges, this paper proposes a backscatter...

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...

SmartphoneDemocracy: Privacy-Preserving E-Voting on Decentralized Infrastructure Using Novel European Identity

The digitization of democratic processes promises greater accessibility but presents challenges in terms of security, privacy, and verifiability. Existing electronic voting systems often rely on centralized architectures, creating single points of failure and forcing too much trust in authorities...

User-To-PC Authentication through Confirmation on Mobile Devices: on Usability and Performance

Protecting personal computers PCs from unauthorized access typically relies on password authentication, which is know to suffer from cognitive burden and weak credentials. As many users nowadays carry mobile devices with advanced security features throughout their day, there is an opportunity to...

CLIProv: a Contrastive Log-To-Intelligence Multimodal Approach for Threat Detection and Provenance Analysis

With the increasing complexity of cyberattacks, the proactive and forward-looking nature of threat intelligence has become more crucial for threat detection and provenance analysis. However, translating high-level attack patterns described in Tactics, Techniques, and Procedures TTP intelligence...

Confidential Wrapped Ethereum

Transparency is one of the key benefits of public blockchains. However, the public visibility of transactions potentially compromises users' privacy. The fundamental challenge is to balance the intrinsic benefits of blockchain openness with the vital need for individual confidentiality. The...

Characterizing Security and Privacy Teaching Standards for Schools in the United States

Increasingly, students begin learning aspects of security and privacy during their primary and secondary education grades K-12 in the United States. Individual U.S. states and some national organizations publish teaching standards -- guidance that outlines expectations for what students should...

When and Where Do Data Poisons Attack Textual Inversion?

Poisoning attacks pose significant challenges to the robustness of diffusion models DMs. In this paper, we systematically analyze when and where poisoning attacks textual inversion TI, a widely used personalization technique for DMs. We first introduce Semantic Sensitivity Maps, a novel method fo...

Breaking a 5-Bit Elliptic Curve Key Using a 133-Qubit Quantum Computer

This experiment breaks a 5-bit elliptic curve cryptographic key using a Shor-style quantum attack. Executed on IBM's 133-qubit ibmtorino with Qiskit Runtime 2.0, a 15-qubit circuit, comprised of 10 logical qubits and 5 ancilla, interferes over an order-32 elliptic curve subgroup to extract the...

Qualcomm Trusted Application Emulation for Fuzzing Testing

In recent years, the increasing awareness of cybersecurity has led to a heightened focus on information security within hardware devices and products. Incorporating Trusted Execution Environments TEEs into product designs has become a standard practice for safeguarding sensitive user information...

CovertAuth: Joint Covert Communication and Authentication in MmWave Systems

Beam alignment BA is a crucial process in millimeter-wave mmWave communications, enabling precise directional transmission and efficient link establishment. However, due to characteristics like omnidirectional exposure and the broadcast nature of the BA phase, it is particularly vulnerable to...

Quantum-Resilient Privacy Ledger (QRPL): a Sovereign Digital Currency for the Post-Quantum Era

The emergence of quantum computing presents profound challenges to existing cryptographic infrastructures, whilst the development of central bank digital currencies CBDCs has raised concerns regarding privacy preservation and excessive centralisation in digital payment systems. This paper propose...

ADAPT: a Pseudo-Labeling Approach to Combat Concept Drift in Malware Detection

Whitepaper called ADAPT: A Pseudo-Labeling Approach To Combat Concept Drift In Malware Detection...

ARPaCCino: an Agentic-RAG for Policy As Code Compliance

Policy as Code PaC is a paradigm that encodes security and compliance policies into machine-readable formats, enabling automated enforcement in Infrastructure as Code IaC environments. However, its adoption is hindered by the complexity of policy languages and the risk of misconfigurations. In th...

Never Trust the Manufacturer, Never Trust the Client: a Novel Method for Streaming STL Files for Secure Additive Manufacturing

While additive manufacturing has opened interesting avenues to reimagine manufacturing as a service MaaS platform, transmission of design files from client to manufacturer over networks opens up many cybersecurity challenges. Securing client's intellectual property IP especially from cyber-attack...

Exploiting Leaderboards for Large-Scale Distribution of Malicious Models

While poisoning attacks on machine learning models have been extensively studied, the mechanisms by which adversaries can distribute poisoned models at scale remain largely unexplored. In this paper, we shed light on how model leaderboards -- ranked platforms for model discovery and evaluation --...

The Dark Side of LLMs Agent-Based Attacks for Complete Computer Takeover

The rapid adoption of Large Language Model LLM agents and multi-agent systems enables unprecedented capabilities in natural language processing and generation. However, these systems have introduced unprecedented security vulnerabilities that extend beyond traditional prompt injection attacks. Th...

Evaluating Post-Quantum Cryptographic Algorithms on Resource-Constrained Devices

Whitepaper called Evaluating Post-Quantum Cryptographic Algorithms On Resource-Constrained Devices...

FortiWeb SQL Injection / Remote Code Execution

This script attempts to detect if FortiWeb is vulnerable to CVE-2025-25257, a SQL injection vulnerability that can be leveraged for remote code execution...

Favicon Trojans: Executable Steganography Via Ico Alpha Channel Exploitation

This paper presents a novel method of executable steganography using the alpha transparency layer of ICO image files to embed and deliver self-decompressing JavaScript payloads within web browsers. By targeting the least significant bit LSB of non-transparent alpha layer image values, the propose...

White-Basilisk: a Hybrid Model for Code Vulnerability Detection

The proliferation of software vulnerabilities presents a significant challenge to cybersecurity, necessitating more effective detection methodologies. We introduce White-Basilisk, a novel approach to vulnerability detection that demonstrates superior performance while challenging prevailing...

SSH-Passkeys: Leveraging Web Authentication for Passwordless SSH

We propose a method for using Web Authentication APIs for SSH authentication, enabling passwordless remote server login with passkeys. These are credentials that are managed throughout the key lifecycle by an authenticator on behalf of the user and offer strong security guarantees. Passwords rema...

Microsoft Windows 11 CVE-2025-49744 Checker

This archive contains a PowerShell script to validate whether a Microsoft Windows 11 system is vulnerable to CVE-2025-49744, a critical local privilege escalation vulnerability involving the gdi32.dll and win32kfull.sys system components. It does not actively exploit anything...

MH-FSF: a Unified Framework for Overcoming Benchmarking and Reproducibility Limitations in Feature Selection Evaluation

Feature selection is vital for building effective predictive models, as it reduces dimensionality and emphasizes key features. However, current research often suffers from limited benchmarking and reliance on proprietary datasets. This severely hinders reproducibility and can negatively impact...

Entangled Threats: a Unified Kill Chain Model for Quantum Machine Learning Security

Quantum Machine Learning QML systems inherit vulnerabilities from classical machine learning while introducing new attack surfaces rooted in the physical and algorithmic layers of quantum computing. Despite a growing body of research on individual attack vectors - ranging from adversarial poisoni...

Kernel Live Patch Security Notice LSN-0113-1

Several security issues were fixed in the kernel relating to out of bounds access and use-after-free vulnerabilities...

Microsoft Office Outlook Code Execution

This proof-of-concept exploit demonstrates a code execution vulnerability in Microsoft Outlook. It injects a crafted mail item into Outlook containing a malicious sync path that triggers an action during scanning...

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks

This paper presents a novel approach to intrusion detection by integrating traditional signature-based methods with the contextual understanding capabilities of the GPT-2 Large Language Model LLM. As cyber threats become increasingly sophisticated, particularly in distributed, heterogeneous, and...

Defending against Prompt Injection with a Few DefensiveTokens

When large language model LLM systems interact with external data to perform complex tasks, a new attack, namely prompt injection, becomes a significant threat. By injecting instructions into the data accessed by the system, the attacker is able to override the initial user task with an arbitrary...

RADAR: a Radio-Based Analytics for Dynamic Association and Recognition of Pseudonyms in VANETs

This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems C-ITS that exploits multiple radio signals emitted by a modern vehicle to break privacy-preserving pseudonym schemes deployed in VANETs. This study shows that by combining...

The Trust Fabric: Decentralized Interoperability and Economic Coordination for the Agentic Web

The fragmentation of AI agent ecosystems has created urgent demands for interoperability, trust, and economic coordination that current protocols -- including MCP Hou et al., 2025, A2A Habler et al., 2025, ACP Liu et al., 2025, and Cisco's AGP Edwards, 2025 -- cannot address at scale. We present...

Phishing Detection in the Gen-AI Era: Quantized LLMs Vs Classical Models

Phishing attacks are becoming increasingly sophisticated, underscoring the need for detection systems that strike a balance between high accuracy and computational efficiency. This paper presents a comparative evaluation of traditional Machine Learning ML, Deep Learning DL, and quantized...

Can Large Language Models Improve Phishing Defense? A Large-Scale Controlled Experiment on Warning Dialogue Explanations

Phishing has become a prominent risk in modern cybersecurity, often used to bypass technological defences by exploiting predictable human behaviour. Warning dialogues are a standard mitigation measure, but the lack of explanatory clarity and static content limits their effectiveness. In this pape...

Giving AI Agents Access to Cryptocurrency and Smart Contracts Creates New Vectors of AI Harm

There is growing interest in giving AI agents access to cryptocurrencies as well as to the smart contracts that transact them. But doing so, this position paper argues, could lead to formidable new vectors of AI harm. To support this argument, we first examine the unique properties of...

LINE: Public-Key Encryption

We propose a public key encryption cryptosystem based on solutions of linear equation systems with predefinition of input parameters through shared secret computation for factorizable substitutions. The existence of multiple equivalent solutions for an underdetermined system of linear equations...

Supporting Intel(R) SGX on Multi-Package Platforms

Intelr Software Guard Extensions SGX was originally released on client platforms and later extended to single socket server platforms. As developers have become familiar with the capabilities of the technology, the applicability of this capability in the cloud has been tested. Various Cloud Servi...

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,...

May I Have Your Attention? Breaking Fine-Tuning Based Prompt Injection Defenses Using Architecture-Aware Attacks

A popular class of defenses against prompt injection attacks on large language models LLMs relies on fine-tuning the model to separate instructions and data, so that the LLM does not follow instructions that might be present with data. There are several academic systems and production-level...

Rainbow Artifacts from Electromagnetic Signal Injection Attacks on Image Sensors

Image sensors are integral to a wide range of safety- and security-critical systems, including surveillance infrastructure, autonomous vehicles, and industrial automation. These systems rely on the integrity of visual data to make decisions. In this work, we investigate a novel class of...

A Formal Rebuttal of "The Blockchain Trilemma: a Formal Proof of the Inherent Trade-Offs among Decentralization, Security, and Scalability"

This paper presents a comprehensive refutation of the so-called "blockchain trilemma," a widely cited but formally ungrounded claim asserting an inherent trade-off between decentralisation, security, and scalability in blockchain protocols. Through formal analysis, empirical evidence, and detaile...

TruChain: a Multi-Layer Architecture for Trusted, Verifiable, and Immutable Open Banking Data

Open banking framework enables third party providers to access financial data across banking institutions, leading to unprecedented innovations in the financial sector. However, some open banking standards remain susceptible to severe technological risks, including unverified data sources,...

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,...

GuardVal: Dynamic Large Language Model Jailbreak Evaluation for Comprehensive Safety Testing

Jailbreak attacks reveal critical vulnerabilities in Large Language Models LLMs by causing them to generate harmful or unethical content. Evaluating these threats is particularly challenging due to the evolving nature of LLMs and the sophistication required in effectively probing their...

Beyond the Worst Case: Extending Differential Privacy Guarantees to Realistic Adversaries

Differential Privacy DP is a family of definitions that bound the worst-case privacy leakage of a mechanism. One important feature of the worst-case DP guarantee is it naturally implies protections against adversaries with less prior information, more sophisticated attack goals, and complex...

Hedge Funds on a Swamp: Analyzing Patterns, Vulnerabilities, and Defense Measures in Blockchain Bridges [Experiment, Analysis and Benchmark]

Blockchain bridges have become essential infrastructure for enabling interoperability across different blockchain networks, with more than $24B monthly bridge transaction volume. However, their growing adoption has been accompanied by a disproportionate rise in security breaches, making them the...

WinRAR Directory Traversal

WinRAR suffers from a directory traversal vulnerability that allows an attacker to place files outside the intended extraction directory when a user extracts a specially crafted .rar archive. Versions prior to 7.12 are affected...

Towards Privacy-Preserving and Personalized Smart Homes Via Tailored Small Language Models

Large Language Models LLMs have showcased remarkable generalizability in language comprehension and hold significant potential to revolutionize human-computer interaction in smart homes. Existing LLM-based smart home assistants typically transmit user commands, along with user profiles and home...

Invariant-Based Robust Weights Watermark for Large Language Models

Watermarking technology has gained significant attention due to the increasing importance of intellectual property IP rights, particularly with the growing deployment of large language models LLMs on billions resource-constrained edge devices. To counter the potential threats of IP theft by...