CVE-2026-10803

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

CVE-2026-10803

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

CVE-2026-10803 MLflow Dataset Digest Computation digest_utils.py mlflow.data.digest_utils weak hash

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

CVE-2026-10803 MLflow Dataset Digest Computation digest_utils.py mlflow.data.digest_utils weak hash

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

EUVD-2026-34245

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

CVE-2026-10803

MLflow up to 3.10.0 contains a flaw in mlflow.data.digest_utils (Digest Computation) where manipulation leads to use of a weak hash. This affects the Digest Utils function in the Dataset Digest Computation component and enables a local attack. The reported exploitability is high in complexity wit...

GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

Rule-based Intrusion Detection and Prevention Systems IDPS offer precise attack detection as well as mitigation, however their manually crafted, signature-driven rules limit adaptability to emerging and zero-day threats. Additionally, existing public datasets e.g., CICIDS2017, UNSW-NB15 focus on...

An Improved CNN-LSTM Based Intrusion Detection System for IoT Networks

With the rapid proliferation of IoT devices, security concerns have dramatically escalated and intrusion detection systems have become critical for protecting networked environments. This paper presents an improved CNN-LSTM based intrusion detection model that combines multi-class classification,...

PT-2026-46317

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. In versions 4.9.0 through 5.0.0, an authenticated user with project-editor permissions can store arbitrary HTML/JavaScript in the ChartDatasetConfig.legend field. The...

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

The increasing penetrations of the critical infrastructure sector in the United States with intelligent digital technologies have greatly increased exposure to advanced cyber adversaries and operational vulnerabilities. AI-powered governance and automated decision-making systems are becoming a ke...

CVE-2026-10803: Use of Weak Hash

A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digestutils of the file mlflow/data/digestutils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is...

MLflow 安全漏洞

MLflow is an open-source platform that simplifies machine learning development. It includes features like tracking experiments, packaging code for reproducible runs, and sharing and deploying models. Versions of MLflow 3.10.0 and earlier contain security vulnerabilities. These vulnerabilities ste...

PT-2026-46189

Name of the Vulnerable Software and Affected Versions MLflow versions prior to 3.10.1 Description A flaw in the Dataset Digest Computation component allows the use of a weak hash. This issue occurs within the mlflow.data.digest utils function located in the mlflow/data/digest utils.py file. An...

mlrun: DataFrame hash collisions can cause dataset artifact path conflicts and silent data corruption

A vulnerability has been found in mlrun up to 1.12.0-rc3. This impacts the function mlrun.utils.helpers.calculatedataframehash of the file mlrun/utils/helpers.py of the component DataFrame Hash Handler. The manipulation leads to use of weak hash. The attack can only be performed from a local...

TeleHunt: A Framework and Tool for Efficient Cybercriminal Community Discovery on Telegram

This paper presents TeleHunt, a framework and tool for evaluating the effectiveness of different strategies to discover cybercriminal communities on Telegram. TeleHunt employs a set of reference-driven snowballing strategies, integrating message-level classification, contextual filtering, and...

Bastet: A Fine-Grained Expert-Labeled Dataset for DeFi Smart Contract Vulnerability Detection

Smart contract vulnerabilities in Decentralized Finance DeFi protocols resulted in over 1.49 billion USD in confirmed losses in 2024 alone, across 192 incidents 1. As LLM-based vulnerability detection emerges as a promising approach to address these threats, the quality of evaluation datasets has...

A Hybrid Approach for Malware Classification Using Secondary Features Fusion

The number of malware either variant or novel is rapidly increasing, making malware detection and mitigation a complex problem. One approach to improving malware mitigation is automatic detection and malware family classification. However, traditional malware detection methods cannot classify...

High-Precision APT Malware Attribution with Out-Of-Scope Resilience

Early attribution of Advanced Persistent Threat APT activity can help defenders prioritise investigation, select countermeasures, and reduce the impact of an intrusion. Malware provides useful attribution evidence, but automated APT malware attribution remains difficult in practice. Existing...

The Role of Domain-Specific Features in Malware Detection: A MacOS Case Study

Despite the growing popularity of macOS among end users and enterprise systems, malware research has primarily focused on Windows and Android operating systems, leaving the problem of macOS malware detection relatively unexplored. Indeed, the specificity of the operating system and the unique...

Operationalizing Cyber Attack Prediction: A Gap-Prioritized Framework with Dataset and Model Selection Guidelines

While AI and machine learning for cyber attack prediction have advanced, a critical gap persists between theoretical research and practical operational deployment. Building on Ankalaki et al. 2025, this paper provides a comprehensive analysis of 150+ benchmark datasets and 200+ studies to identif...