3136 matches found
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 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...
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...
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
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 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-2026-3920
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...
Machine-Learning-Web-Apps 代码注入漏洞
Machine-Learning-Web-Apps is a machine learning web application development framework developed by JCharis Jesse. There is a code injection vulnerability in Machine-Learning-Web-Apps, which stems from an incorrect operation on the rendertemplate function in the Jinja2 Template Handler component o...
PT-2026-24891
A vulnerability was identified in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. The impacted element is the function render template of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template...
CVE-2026-0847
A vulnerability in NLTK versions up to and including 3.9.2 allows arbitrary file read via path traversal in multiple CorpusReader classes, including WordListCorpusReader, TaggedCorpusReader, and BracketParseCorpusReader. These classes fail to properly sanitize or validate file paths, enabling...
CVE-2026-0847
A vulnerability in NLTK versions up to and including 3.9.2 allows arbitrary file read via path traversal in multiple CorpusReader classes, including WordListCorpusReader, TaggedCorpusReader, and BracketParseCorpusReader. These classes fail to properly sanitize or validate file paths, enabling...
Gravity Falls: A Comparative Analysis of Domain-Generation Algorithm (DGA) Detection Methods for Mobile Device Spearphishing
Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing smishing links that leverage Domain Generation Algorithms DGA to rotate hostile infrastructure. Despite this, DGA research and evaluation largely emphasize malware C2 and email phishing datasets, leaving limited...
AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning
Machine learning based network intrusion detection systems are vulnerable to adversarial attacks that degrade classification performance under both gradient-based and distribution shift threat models. Existing defenses typically apply uniform detection strategies, which may not account for...
SafePickle: Robust and Generic ML Detection of Malicious Pickle-Based ML Models
Model repositories such as Hugging Face increasingly distribute machine learning artifacts serialized with Python's pickle format, exposing users to remote code execution RCE risks during model loading. Recent defenses, such as PickleBall, rely on per-library policy synthesis that requires comple...