CVE-2026-12480

Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the H5IOStore.verifydataset and fileeditor.py methods, which fail to check the dataset.isvirtual property of HDF5 datasets. This allows ...

CVE-2026-12480

Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the H5IOStore.verifydataset and fileeditor.py methods, which fail to check the dataset.isvirtual property of HDF5 datasets. This allows ...

EUVD-2026-41090

Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the H5IOStore.verifydataset and fileeditor.py methods, which fail to check the dataset.isvirtual property of HDF5 datasets. This allows ...

PT-2026-54620

Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the H5IOStore. verify dataset and file editor.py methods, which fail to check the dataset.is virtual property of HDF5 datasets. This...

PYSEC-2026-291 Backpropagate: backprop ui --auth and backprop ui --share do not enforce authentication

Summary In backpropagate = 1.1.0, the optional Reflex web UI pip install backpropagateui, launched via backprop ui exposes a training control plane: dataset upload, model load, training start/stop, multi-run orchestration, GGUF export, and HuggingFace Hub push. The CLI accepts two operator-facing...

CVE-2026-10804

A flaw was found in Streamlit, within its Palette Handler component. This vulnerability stems from the use of a weak hashing algorithm. A local attacker could exploit this flaw, though it requires a high level of technical complexity. Successful exploitation may lead to a low impact on the...

EUVD-2026-39562

The qrscp application's C-STORE handler uses a specific instance from attacker-supplied DICOM datasets directly in os.path.join without sanitization, allowing file writes to arbitrary paths...

CVE-2026-48797

Backpropagate is a Python library for fine-tuning large language models on a single GPU. In versions 1.1.0 and 1.1.1, the optional Reflex web UI exposes a training control plane without authentication: dataset upload, model load, training start/stop, multi-run orchestration, GGUF export, and...

Turn specs into evals for any agent with ASSERT

Today, we’re releasing Adaptive Spec-driven Scoring for Evaluation and Regression Testing ASSERT, an open-source framework for turning natural-language behavior specifications into executable evaluations. Every team building an AI system starts with a clear intention for the behaviors they want t...

NCMD: Benign-Anchored Feature Selection for Imbalanced Network Intrusion Detection

Feature selection is critical for network intrusion detection systems NIDS operating under high-dimensional, highly imbalanced traffic, as found in operational and defense networks. Traditional filter methods rank features using global statistics computed symmetrically across classes and thus fai...

CVE-2026-40904

Chartbrew is an open-source web application that can connect directly to databases and APIs and use the data to create charts. In version 4.9.0, Chartbrew exposes multiple dataset and dataRequest endpoints that authorize low-privileged project members at the team level instead of binding the...

FDM: A Framework for Decision-Making to Build ML-Based Malware Detection Systems

Selecting appropriate machine learning ML configurations for malware detection is a complex, multi-criteria problem. Model choice, feature engineering, and update mechanisms must jointly satisfy operational constraints that vary across deployment contexts. This paper proposes the Framework for...

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...

AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security

Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhile, advanced frontier AI models drastically lower attack barriers, rendering current agent alignment frameworks inadequate for real-world...

Introducing EvidenceForge: Synthetic security logs that don’t look (as) fake

Security teams need high-quality, labeled datasets to train threat hunters and incident responders, validate detection logic, and develop robust analytic models. EvidenceForge helps teams overcome the limitations of anonymized or stale public datasets, while avoiding the cost and complexity of...

The Fault in Our Drafts: Vulnerabilities in RPKI Specification and Software

The Resource Public Key Infrastructure RPKI secures the Internet's routing system by defining a complex trust and validation framework for certificates, Route Origin Authorizations ROAs, manifests, and Certificate Revocation Lists CRLs. These mechanisms are specified across dozens of RFCs. This...

Cybersecurity of Electric Vehicle Charging Infrastructure: Recent Advances, Open Challenges, and Future Directions

Electric Vehicles EVs have emerged as significant disruptors in the transportation sector over the past decade. Their growing popularity and adoption are accompanied by capital expenditures to deploy charging infrastructure. EV charging infrastructure sits at the intersection of the power grid, t...

UNAD+: An Explainable Hybrid Framework for Unknown Network Attack Detection

The detection of previously unseen network attacks remains a major challenge for intrusion detection systems. Although supervised learning methods often perform well on known attack classes, they are limited when new attack types are not represented in the training data. Unsupervised methods are...

TriSweep: A Four-Drone Swarm Framework for Electromagnetic Side-Channel Analysis

Electromagnetic EM side-channel analysis traditionally assumes a stationary, close-proximity probe - a threat model that underestimates aerial adversaries. TriSweep is a simulation framework that designs and evaluates a four-drone swarm architecture for autonomous standoff EM-SCA of embedded...

Federated Naive Bayes with Real Mixture of Gaussians and Institutional Governance Regularization for Network Intrusion Detection

Federated learning for intrusion detection rests on a flawed premise: that every participating institution contributes equally to the shared model. In practice, a financial institution with mature security controls and low vulnerability exposure produces fundamentally different data than a...