Zk-SNARK for String Match

We present a secure and efficient string-matching platform leveraging zk-SNARKs Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge to address the challenge of detecting sensitive information leakage while preserving data privacy. Our solution enables organizations to verify whether...

Training-Free Watermarking for Autoregressive Image Generation

Invisible image watermarking can protect image ownership and prevent malicious misuse of visual generative models. However, existing generative watermarking methods are mainly designed for diffusion models while watermarking for autoregressive image generation models remains largely underexplored...

CRYPTONITE: Scalable Accelerator Design for Cryptographic Primitives and Algorithms

Cryptographic primitives, consisting of repetitive operations with different inputs, are typically implemented using straight-line C code due to traditional execution on CPUs. Computing these primitives is necessary for secure communication; thus, dedicated hardware accelerators are required in...

Neuromorphic Mimicry Attacks Exploiting Brain-Inspired Computing for Covert Cyber Intrusions

Neuromorphic computing, inspired by the human brain's neural architecture, is revolutionizing artificial intelligence and edge computing with its low-power, adaptive, and event-driven designs. However, these unique characteristics introduce novel cybersecurity risks. This paper proposes...

Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking

Logit-based LLM watermarking traces and verifies AI-generated content by maintaining green and red token lists and increasing the likelihood of green tokens during generation. However, it fails in low-entropy scenarios, where predictable outputs make green token selection difficult without...

On the (In)Security of Proofs-Of-Space Based Longest-Chain Blockchains

The Nakamoto consensus protocol underlying the Bitcoin blockchain uses proof of work as a voting mechanism. Honest miners who contribute hashing power towards securing the chain try to extend the longest chain they are aware of. Despite its simplicity, Nakamoto consensus achieves meaningful...

Efficient Privacy-Preserving Cross-Silo Federated Learning with Multi-Key Homomorphic Encryption

Federated Learning FL is susceptible to privacy attacks, such as data reconstruction attacks, in which a semi-honest server or a malicious client infers information about other clients' datasets from their model updates or gradients. To enhance the privacy of FL, recent studies combined Multi-Key...

Streamlining HTTP Flooding Attack Detection through Incremental Feature Selection

Applications over the Web primarily rely on the HTTP protocol to transmit web pages to and from systems. There are a variety of application layer protocols, but among all, HTTP is the most targeted because of its versatility and ease of integration with online services. The attackers leverage the...

Relational Hoare Logic for Realistically Modelled Machine Code

Many security- and performance-critical domains, such as cryptography, rely on low-level verification to minimize the trusted computing surface and allow code to be written directly in assembly. However, verifying assembly code against a realistic machine model is a challenging task. Furthermore,...

From Nuclear Safety to LLM Security: Applying Non-Probabilistic Risk Management Strategies to Build Safe and Secure LLM-Powered Systems

Large language models LLMs offer unprecedented and growing capabilities, but also introduce complex safety and security challenges that resist conventional risk management. While conventional probabilistic risk analysis PRA requires exhaustive risk enumeration and quantification, the novelty and...

Towards Verifiability of Total Value Locked (TVL) in Decentralized Finance

Total Value Locked TVL aims to measure the aggregate value of cryptoassets deposited in Decentralized Finance DeFi protocols. Although blockchain data is public, the way TVL is computed is not well understood. In practice, its calculation on major TVL aggregators relies on self-reports from...

PsyScam: a Benchmark for Psychological Techniques in Real-World Scams

Online scams have become increasingly prevalent, with scammers using psychological techniques PTs to manipulate victims. While existing research has developed benchmarks to study scammer behaviors, these benchmarks do not adequately reflect the PTs observed in real-world scams. To fill this gap, ...

Lessons from Defending Gemini against Indirect Prompt Injections

Gemini is increasingly used to perform tasks on behalf of users, where function-calling and tool-use capabilities enable the model to access user data. Some tools, however, require access to untrusted data introducing risk. Adversaries can embed malicious instructions in untrusted data which caus...

On the Day They Experience: Awakening Self-Sovereign Experiential AI Agents

Drawing on Andrew Parker's "Light Switch" theory-which posits that the emergence of vision ignited a Cambrian explosion of life by driving the evolution of hard parts necessary for survival and fueling an evolutionary arms race between predators and prey-this essay speculates on an analogous...

From Assistants to Adversaries: Exploring the Security Risks of Mobile LLM Agents

The growing adoption of large language models LLMs has led to a new paradigm in mobile computing--LLM-powered mobile AI agents--capable of decomposing and automating complex tasks directly on smartphones. However, the security implications of these agents remain largely unexplored. In this paper,...

Is Your Prompt Safe? Investigating Prompt Injection Attacks against Open-Source LLMs

Whitepaper called Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs...

Sei Giga

We introduce the Sei Giga, a multi-concurrent producer parallelized execution EVM layer one blockchain. In an internal testnet Giga has achieved 5 gigagas/sec throughput and sub 400ms finality. Giga uses Autobahn for consensus with separate DA and consensus layers requiring f+1 votes for a PoA on...

Topology-Aware Detection and Localization of Distributed Denial-Of-Service Attacks in Network-On-Chips

Network-on-Chip NoC enables on-chip communication between diverse cores in modern System-on-Chip SoC designs. With its shared communication fabric, NoC has become a focal point for various security threats, especially in heterogeneous and high-performance computing platforms. Among these attacks,...

An Empirical Analysis of EOS Blockchain: Architecture, Contract, and Security

With the rapid development of blockchain technology, various blockchain systems are exhibiting vitality and potential. As a representative of Blockchain 3.0, the EOS blockchain has been regarded as a strong competitor to Ethereum. Nevertheless, compared with Bitcoin and Ethereum, academic researc...

CSAGC-IDS: a Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data

As computer networks proliferate, the gravity of network intrusions has escalated, emphasizing the criticality of network intrusion detection systems for safeguarding security. While deep learning models have exhibited promising results in intrusion detection, they face challenges in managing...

Agency Problems and Adversarial Bilevel Optimization under Uncertainty and Cyber Threats

We study an agency problem between a holding company and its subsidiary, exposed to cyber threats that affect the overall value of the subsidiary. The holding company seeks to design an optimal incentive scheme to mitigate these losses. In response, the subsidiary selects an optimal cybersecurity...

WordPress PSW Front-end Login Registration 1.12 User Registration

WordPress PSW Front-end Login Registration plugin versions 1.12 and below suffers from a vulnerability that allows an unauthenticated attacker to register new user accounts via an exposed AJAX action without proper validation or restrictions...

Faraday 5.14.0

Faraday is a tool that introduces a new concept called IPE, or Integrated Penetration-Test Environment. It is a multiuser penetration test IDE designed for distribution, indexation and analysis of the generated data during the process of a security audit. The main purpose of Faraday is to re-use...

Can Large Language Models Really Recognize Your Name?

Large language models LLMs are increasingly being used to protect sensitive user data. However, current LLM-based privacy solutions assume that these models can reliably detect personally identifiable information PII, particularly named entities. In this paper, we challenge that assumption by...

Vulnerability of Transfer-Learned Neural Networks to Data Reconstruction Attacks in Small-Data Regime

Training data reconstruction attacks enable adversaries to recover portions of a released model's training data. We consider the attacks where a reconstructor neural network learns to invert the random mapping between training data and model weights. Prior work has shown that an informed adversar...

Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the Edge

Artificial neural network pruning is a method in which artificial neural network sizes can be reduced while attempting to preserve the predicting capabilities of the network. This is done to make the model smaller or faster during inference time. In this work we analyze the ability of a selection...

Moneros Decentralized P2P Exchanges: Functionality, Adoption, and Privacy Risks

Privacy-focused cryptocurrencies like Monero remain popular, despite increasing regulatory scrutiny that has led to their delisting from major centralized exchanges. The latter also explains the recent popularity of decentralized exchanges DEXs with no centralized ownership structures. These...

In Search of Lost Data: a Study of Flash Sanitization Practices

To avoid the disclosure of personal or corporate data, sanitization of storage devices is an important issue when such devices are to be reused. While poor sanitization practices have been reported for second-hand hard disk drives, it has been reported that data has been found on original storage...

iOS 18.3 Beta / 18.2.1 Audio File Buffer Overflow

A critical vulnerability exists in AudioConverterService on iOS 18.3 Beta and also affects iOS 18.2.1 that allows a remote attacker to exploit a buffer overflow vulnerability via a malicious audio file sent through iMessage or SMS...

A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input

We study the problem of differentially private second moment estimation and present a new algorithm that achieve strong privacy-utility trade-offs even for worst-case inputs under subsamplability assumptions on the data. We call an input $m,α,β$-subsamplable if a random subsample of size $m$ or...

Trustworthy Reputation Games and Applications to Proof-Of-Reputation Blockchains

Reputation systems play an essential role in the Internet era, as they enable people to decide whom to trust, by collecting and aggregating data about users' behavior. Recently, several works proposed the use of reputation for the design and scalability improvement of decentralized blockchain...

Robust and Efficient AI-Based Attack Recovery in Autonomous Drones

We introduce an autonomous attack recovery architecture to add common sense reasoning to plan a recovery action after an attack is detected. We outline use-cases of our architecture using drones, and then discuss how to implement this architecture efficiently and securely in edge devices...

Beyond Text: Unveiling Privacy Vulnerabilities in Multi-Modal Retrieval-Augmented Generation

Multimodal Retrieval-Augmented Generation MRAG systems enhance LMMs by integrating external multimodal databases, but introduce unexplored privacy vulnerabilities. While text-based RAG privacy risks have been studied, multimodal data presents unique challenges. We provide the first systematic...

Prink: $K_s$-Anonymization for Streaming Data in Apache Flink

In this paper, we present Prink, a novel and practically applicable concept and fully implemented prototype for ks-anonymizing data streams in real-world application architectures. Building upon the pre-existing, yet rudimentary CASTLE scheme, Prink for the first time introduces semantics-aware...

Apple Security Advisory 05-12-2025-3

Apple Security Advisory 05-12-2025-3 - macOS Sequoia 15.5 addresses bypass, code execution, double free, information leakage, integer overflow, out of bounds read, and use-after-free vulnerabilities...

Quantum Opacity, Classical Clarity: a Hybrid Approach to Quantum Circuit Obfuscation

Quantum computing leverages quantum mechanics to achieve computational advantages over classical hardware, but the use of third-party quantum compilers in the Noisy Intermediate-Scale Quantum NISQ era introduces risks of intellectual property IP exposure. We address this by proposing a novel...

BeamClean: Language Aware Embedding Reconstruction

In this work, we consider an inversion attack on the obfuscated input embeddings sent to a language model on a server, where the adversary has no access to the language model or the obfuscation mechanism and sees only the obfuscated embeddings along with the model's embedding table. We propose...

Multiple Proposer Transaction Fee Mechanism Design: Robust Incentives against Censorship and Bribery

Censorship resistance is one of the core value proposition of blockchains. A recurring design pattern aimed at providing censorship resistance is enabling multiple proposers to contribute inputs into block construction. Notably, Fork-Choice Enforced Inclusion Lists FOCIL is proposed to be include...

Malware Families Discovery Via Open-Set Recognition on Android Manifest Permissions

Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their respective families is essential for building effective defenses against cyber threats. Machine learning models have ...

Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy

Federated Learning with client-level differential privacy DP provides a promising framework for collaboratively training models while rigorously protecting clients' privacy. However, classic approaches like DP-FedAvg struggle when clients have heterogeneous privacy requirements, as they must...

When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based RowHammer Mitigations

Per Row Activation Counting PRAC has emerged as a robust framework for mitigating RowHammer RH vulnerabilities in modern DRAM systems. However, we uncover a critical vulnerability: a timing channel introduced by the Alert Back-Off ABO protocol and Refresh Management RFM commands. We present...

Traceable Black-Box Watermarks for Federated Learning

Whitepaper called Traceable Black-Box Watermarks For Federated Learning...

Recommender Systems for Democracy: toward Adversarial Robustness in Voting Advice Applications

Voting advice applications VAAs help millions of voters understand which political parties or candidates best align with their views. This paper explores the potential risks these applications pose to the democratic process when targeted by adversarial entities. In particular, we expose 11...

VulCPE: Context-Aware Cybersecurity Vulnerability Retrieval and Management

The dynamic landscape of cybersecurity demands precise and scalable solutions for vulnerability management in heterogeneous systems, where configuration-specific vulnerabilities are often misidentified due to inconsistent data in databases like the National Vulnerability Database NVD. Inaccurate...

Provable Execution in Real-Time Embedded Systems

Embedded devices are increasingly ubiquitous and vital, often supporting safety-critical functions. However, due to strict cost and energy constraints, they are typically implemented with Micro-Controller Units MCUs that lack advanced architectural security features. Within this space, recent...

The Hidden Dangers of Browsing AI Agents

Autonomous browsing agents powered by large language models LLMs are increasingly used to automate web-based tasks. However, their reliance on dynamic content, tool execution, and user-provided data exposes them to a broad attack surface. This paper presents a comprehensive security evaluation of...

An Automated Blackbox Noncompliance Checker for QUIC Server Implementations

We develop QUICtester, an automated approach for uncovering non-compliant behaviors in the ratified QUIC protocol implementations RFC 9000/9001. QUICtester leverages active automata learning to abstract the behavior of a QUIC implementation into a finite state machine FSM representation. Unlike...

One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems

Large Language Models LLMs enhanced with Retrieval-Augmented Generation RAG have shown improved performance in generating accurate responses. However, the dependence on external knowledge bases introduces potential security vulnerabilities, particularly when these knowledge bases are publicly...

Security Degradation in Iterative AI Code Generation -- a Systematic Analysis of the Paradox

The rapid adoption of Large Language ModelsLLMs for code generation has transformed software development, yet little attention has been given to how security vulnerabilities evolve through iterative LLM feedback. This paper analyzes security degradation in AI-generated code through a controlled...

Apple Security Advisory 05-12-2025-1

Apple Security Advisory 05-12-2025-1 - iOS 18.5 and iPadOS 18.5 addresses code execution, double free, integer overflow, out of bounds read, spoofing, and use-after-free vulnerabilities...