zirgen

Zirgen Circuit Compiler Zirgen is a compiler for a domain-specific language, also called "zirgen", which creates arithmetic circuits for the RISC Zero proof system. For the most part, users of RISC Zero should be writing their zkApps in Rust and using our RISC-V zkVM rather than building them...

dcsgonebadge

DEF CON Singapore One Badge This project manages the hardware design of the Circuit Crafters first project, an electronic hardware badge intended for distribution at the DEF CON Singapore 2026 security conference at the Marina Bay Sands Expo and Convention Centre. License This project is licensed...

Verifiable Quantum Advantage Based on Polynomials with Planted Structures

A central question in the theory of quantum advantage is whether there are quantum advantage protocols with similar resource requirements as random circuit sampling that are also verifiable just from the classical outputs of the quantum computation. Here, we develop the idea of simulation secrets...

The Cost of Stability: Deanonymizing Onion Services Long-Lived Introduction Circuits

Tor is a widely used anonymity network that provides network privacy by routing client communications through a sequence of relays to their destinations. An adversary observing a single Tor relay cannot readily link clients to their destinations, as doing so requires identifying the other relays...

HarmQ: Harmonic Backdoor Attacks against Quantum Neural Networks

Quantum Neural Networks QNNs have emerged as a promising paradigm for quantum machine learning in the Noisy Intermediate-Scale Quantum NISQ era, leveraging quantum phenomena such as superposition and entanglement to process information in exponentially large Hilbert spaces. However, QNNs inherit...

midnight-ownpublickey-attack

Bounty 295: Why ownPublicKey Can't Be Trusted for Access...

Backdoor Threats in Variational Quantum Circuits: Taxonomy, Attacks, and Defenses

Variational quantum algorithms VQAs are a central paradigm for noisy intermediate-scale NISQ quantum computing, yet their reliance on predesigned and pretrained variational quantum circuits VQCs introduces critical security vulnerabilities, particularly backdoor attacks. These attacks embed hidde...

Hardware-Efficient Compound IC Protection with Lightweight Cryptography

Over the years, many techniques have been introduced to protect integrated circuits ICs from hardware security threats that emerged in the globalized IC manufacturing supply chain, such as overproduction and piracy. However, most of these techniques have been rendered inefficient since they do no...

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

The increasing number of cyber threats and rapidly evolving tactics, as well as the high volume of data in recent years, have caused classical machine learning, rules, and signature-based defence strategies to fail, rendering them unable to keep up. An alternative, Quantum Machine Learning QML, h...

Cybersecurity AI: The World's Top AI Agent for Security Capture-The-Flag (CTF)

Are Capture-the-Flag competitions obsolete? In 2025, Cybersecurity AI CAI systematically conquered some of the world's most prestigious hacking competitions, achieving Rank 1 at multiple events and consistently outperforming thousands of human teams. Across five major circuits-HTB's AI vs Humans,...

EUVD-2006-3406

Malware in sbrugna...

EUVD-2024-1535

Malicious code in bioql PyPI...

Malware in kreme-circuits

Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be rotated immediately from a different computer. The package should be removed, but as full control of the computer may have been given to an outsid...

Malicious code in kreme-circuits (npm)

The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 115a80b8aadb1029e4fdf7ec27a30991a73af718770b70a89211f740bbad9c40 Any computer that has this package installed or running should be considered...

MAL-2025-47403 Malicious code in kreme-circuits (npm)

The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 115a80b8aadb1029e4fdf7ec27a30991a73af718770b70a89211f740bbad9c40 Any computer that has this package installed or running should be considered...

Quantum AI Algorithm Development for Enhanced Cybersecurity: a Hybrid Approach to Malware Detection

This study explores the application of quantum machine learning QML algorithms to enhance cybersecurity threat detection, particularly in the classification of malware and intrusion detection within high-dimensional datasets. Classical machine learning approaches encounter limitations when dealin...

Evaluating Security Properties in the Execution of Quantum Circuits

Quantum computing is a disruptive technology that is expected to offer significant advantages in many critical fields e.g. drug discovery and cryptography. The security of information processed by such machines is therefore paramount. Currently, modest Noisy Intermediate-Scale Quantum NISQ device...

Ransomware Negotiation: Dynamics and Privacy-Preserving Mechanism Design

Ransomware attacks have become a pervasive and costly form of cybercrime, causing tens of millions of dollars in losses as organizations increasingly pay ransoms to mitigate operational disruptions and financial risks. While prior research has largely focused on proactive defenses, the...

Designing with Deception: ML- and Covert Gate-Enhanced Camouflaging to Thwart IC Reverse Engineering

Integrated circuits ICs are essential to modern electronic systems, yet they face significant risks from physical reverse engineering RE attacks that compromise intellectual property IP and overall system security. While IC camouflage techniques have emerged to mitigate these risks, existing...

Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy

This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks QNNs in the Noisy Intermediate-Scale Quantum NISQ era. In this paper, we present an integrated framework that leverages and combines existing approaches to enhance...