Explainable PQC: A Layered Interpretive Framework for Post-Quantum Cryptographic Security Assumptions

This paper studies how post-quantum cryptographic PQC security assumptions can be represented and communicated through a structured, layered framework that is useful for technical interpretation but does not replace formal cryptographic proofs. We propose "Explainable PQC,'' an interdisciplinary...

ML Defender (ARGus NDR): An Open-Source Embedded ML NIDS for Botnet and Anomalous Traffic Detection in Resource-Constrained Organizations

Ransomware and DDoS attacks disproportionately impact hospitals, schools, and small organizations that cannot afford enterprise security solutions. We present ML Defender aRGus NDR, an open-source network intrusion detection system built in C++20, deployable on commodity hardware at approximately...

CVE-2026-34445

Open Neural Network Exchange ONNX is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr function to load metadata like file paths or data lengths directly from an ONNX model file. It didn’t check if the...

Quantum Bit Error Rate Analysis in BB84 Quantum Key Distribution: Measurement, Statistical Estimation, and Eavesdropping Detection

Quantum Key Distribution QKD provides information-theoretic security by exploiting the principles of quantum mechanics. Among QKD protocols, the BB84 scheme remains the most widely adopted for both theoretical research and practical implementation. A critical parameter determining the reliability...

Context-Aware Phishing Email Detection Using Machine Learning and NLP

Phishing attacks remain among the most prevalent cybersecurity threats, causing significant financial losses for individuals and organizations worldwide. This paper presents a machine learning-based phishing email detection system that analyzes email body content using natural language processing...

CVE-2026-3962

A vulnerability was identified in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. The impacted element is the function rendertemplate of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template...

Machine Learning Operations: Yesterday, Today, and Tomorrow

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Walma: Learning to See Memory Corruption in WebAssembly

WebAssembly's Wasm monolithic linear memory model facilitates memory corruption attacks that can escalate to cross-site scripting in browsers or go undetected when a malicious host tampers with a module's state. Existing defenses rely on invasive binary instrumentation or custom runtimes, and do...

Toward a Multi-Layer ML-Based Security Framework for Industrial IoT

The Industrial Internet of Things IIoT introduces significant security challenges as resource-constrained devices become increasingly integrated into critical industrial processes. Existing security approaches typically address threats at a single network layer, often relying on expensive hardwar...

UBUNTU-CVE-2026-3503

Protection mechanism failure in wolfCrypt post-quantum implementations ML-KEM and ML-DSA in wolfSSL on ARM Cortex-M microcontrollers allows a physical attacker to compromise key material and/or cryptographic outcomes via induced transient faults that corrupt or redirect seed/pointer values during...

CVE-2026-3503

CVE-2026-3503 involves a protection mechanism failure in wolfSSL’s wolfCrypt post-quantum implementations (ML-KEM and ML-DSA) on ARM Cortex-M devices. The root cause is exposed as transient fault injections that can corrupt or redirect seed/pointer values during Keccak-based expansion, potentiall...

CVE-2026-3503

Protection mechanism failure in wolfCrypt post-quantum implementations ML-KEM and ML-DSA in wolfSSL on ARM Cortex-M microcontrollers allows a physical attacker to compromise key material and/or cryptographic outcomes via induced transient faults that corrupt or redirect seed/pointer values during...

CVE-2026-3503 Fault injection attack with ML-DSA and ML-KEM on ARM

Protection mechanism failure in wolfCrypt post-quantum implementations ML-KEM and ML-DSA in wolfSSL on ARM Cortex-M microcontrollers allows a physical attacker to compromise key material and/or cryptographic outcomes via induced transient faults that corrupt or redirect seed/pointer values during...

EUVD-2025-208848

A vulnerability in MLflow's pyfunc extraction process allows for arbitrary file writes due to improper handling of tar archive entries. Specifically, the use of tarfile.extractall without path validation enables crafted tar.gz files containing .. or absolute paths to escape the intended extractio...

Benchmarking Post-Quantum Cryptography on Resource-Constrained IoT Devices: ML-KEM and ML-DSA on ARM Cortex-M0+

The migration to post-quantum cryptography is urgent for Internet of Things devices with 10-20 year lifespans, yet no systematic benchmarks exist for the finalised NIST standards on the most constrained 32-bit processor class. This paper presents the first isolated algorithm-level benchmarks of...

CVE-2026-28500

Open Neural Network Exchange ONNX is an open standard for machine learning interoperability. In versions up to and including 1.20.1, a security control bypass exists in onnx.hub.load due to improper logic in the repository trust verification mechanism. While the function is designed to warn users...

CVE-2026-3962 Jcharis Machine-Learning-Web-Apps Jinja2 Template app.py render_template cross site scripting

A vulnerability was identified in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. The impacted element is the function rendertemplate of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template...

CVE-2026-3962

The CVE-2026-3962 entry affects Jcharis Machine-Learning-Web-Apps (up to a6996b634d98ccec4701ac8934016e8175b60eb5) where the render_template function in Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py under the Jinja2 Template Handler is vulnerable to cross-site...

CVE-2026-3962

A vulnerability was identified in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. The impacted element is the function rendertemplate of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template...

CVE-2026-3920

Out of bounds memory access in WebML in Google Chrome prior to 146.0.7680.71 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page. Chromium security severity: High...