Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts

Ethereum smart contracts operate in a concurrent environment where multiple transactions can be submitted simultaneously. However, the Ethereum Virtual Machine EVM enforces sequential execution of transactions within each block to prevent conflicts arising from concurrent access to the same state...

[SECURITY] Fedora 41 Update: trafficserver-9.2.11-1.fc41

Traffic Server is a high-performance building block for cloud services. It's more than just a caching proxy server; it also has support for plugins to build large scale web applications. Key features: Caching - Improve your response time, while reducing server load and bandwidth needs by caching...

[SECURITY] Fedora 42 Update: trafficserver-10.0.6-1.fc42

Traffic Server is a high-performance building block for cloud services. It's more than just a caching proxy server; it also has support for plugins to build large scale web applications. Key features: Caching - Improve your response time, while reducing server load and bandwidth needs by caching...

ZKPROV: a Zero-Knowledge Approach to Dataset Provenance for Large Language Models

As the deployment of large language models LLMs grows in sensitive domains, ensuring the integrity of their computational provenance becomes a critical challenge, particularly in regulated sectors such as healthcare, where strict requirements are applied in dataset usage. We introduce ZKPROV, a...

Yotta: a Large-Scale Trustless Data Trading Scheme for Blockchain System

Data trading is one of the key focuses of Web 3.0. However, all the current methods that rely on blockchain-based smart contracts for data exchange cannot support large-scale data trading while ensuring data security, which falls short of fulfilling the spirit of Web 3.0. Even worse, there is...

The Trip to ZigBee Backscatter across a Decade, a Systematic Review

The field of backscatter communication has undergone a profound transformation, evolving from a niche technology for radio-frequency identification RFID into a sophisticated paradigm poised to enable a truly battery-free Internet of Things IoT. This evolution is built upon a deepening understandi...

CVE-2025-48886

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...

CVE-2025-48886 hydra-node dangerously assumes L1 event finality and does not consider failed transactions

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...

CVE-2025-48886 hydra-node dangerously assumes L1 event finality and does not consider failed transactions

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...

CVE-2025-48886

Hydra, a Layer-2 scaling solution for Cardano, is affected by a vulnerability that arises from assuming L1 finality and neglecting failed transactions. Before version 0.22.0, Hydra treated certain L1 events as finalized as soon as recognized by node participants, making those transactions targets...

CVE-2025-48886 hydra-node dangerously assumes L1 event finality and does not consider failed transactions

Hydra is a layer-two scalability solution for Cardano. Prior to version 0.22.0, the process assumes L1 event finality and does not consider failed transactions. Currently, Cardano L1 is monitored for certain events which are necessary for state progression. At the moment, Hydra considers those...

PT-2025-26219 · Hydra · Hydra

Name of the Vulnerable Software and Affected Versions: Hydra versions prior to 0.22.0 Description: Hydra is a layer-two scalability solution for Cardano. The issue arises from the assumption of L1 event finality, where the system does not consider failed transactions on the Cardano L1. This makes...

Efficient Blockchain-Based Steganography Via Backcalculating Generative Adversarial Network

Blockchain-based steganography enables data hiding via encoding the covert data into a specific blockchain transaction field. However, previous works focus on the specific field-embedding methods while lacking a consideration on required field-generation embedding. In this paper, we propose a...

SoK: Machine Unlearning for Large Language Models

Large language model LLM unlearning has become a critical topic in machine learning, aiming to eliminate the influence of specific training data or knowledge without retraining the model from scratch. A variety of techniques have been proposed, including Gradient Ascent, model editing, and...

[SECURITY] Fedora 41 Update: fcgi-2.4.0-52.fc41

FastCGI is a language independent, scalable, open extension to CGI that provides high performance without the limitations of server specific APIs...

FedShield-LLM: a Secure and Scalable Federated Fine-Tuned Large Language Model

Federated Learning FL offers a decentralized framework for training and fine-tuning Large Language Models LLMs by leveraging computational resources across organizations while keeping sensitive data on local devices. It addresses privacy and security concerns while navigating challenges associate...

ReGA: Representation-Guided Abstraction for Model-Based Safeguarding of LLMs

Large Language Models LLMs have achieved significant success in various tasks, yet concerns about their safety and security have emerged. In particular, they pose risks in generating harmful content and vulnerability to jailbreaking attacks. To analyze and monitor machine learning models,...

PackHero: a Scalable Graph-Based Approach for Efficient Packer Identification

Anti-analysis techniques, particularly packing, challenge malware analysts, making packer identification fundamental. Existing packer identifiers have significant limitations: signature-based methods lack flexibility and struggle against dynamic evasion, while Machine Learning approaches require...

Efficient Preimage Approximation for Neural Network Certification

The growing reliance on artificial intelligence in safety- and security-critical applications demands effective neural network certification. A challenging real-world use case is certification against patch attacks'', where adversarial patches or lighting conditions obscure parts of images, for...

EarthOL: a Proof-Of-Human-Contribution Consensus Protocol -- Addressing Fundamental Challenges in Decentralized Value Assessment with Enhanced Verification and Security Mechanisms

This paper introduces EarthOL, a novel consensus protocol that attempts to replace computational waste in blockchain systems with verifiable human contributions within bounded domains. While recognizing the fundamental impossibility of universal value assessment, we propose a domain-restricted...