CVE-2022-35939

TensorFlow is an open source platform for machine learning. The ScatterNd function takes an input argument that determines the indices of of the output tensor. An input index greater than the output tensor or less than zero will either write content at the wrong index or trigger a crash. We have...

CVE-2022-35938

TensorFlow is an open source platform for machine learning. The GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. This issue has been...

CVE-2025-13628

CVE-2025-13628 affects Tutor LMS – eLearning and online course solution (WordPress) up to version 3.9.3. The vulnerability results from missing capability checks in bulk_action_handler and coupon_permanent_delete, allowing authenticated users with subscriber-level access or higher to delete, acti...

JupyterHub LTI13Authenticator RCE

The vulnerability of the LTI13Authenticator function of the JupyterHub jupyterhub-ltiauthenticator component is related to errors in verifying the cryptographic signature. Exploiting this vulnerability could allow an attacker to influence the confidentiality, integrity, and accessibility of the...

Unified Framework for Qualifying Security Boundary of PUFs against Machine Learning Attacks

Physical Unclonable Functions PUFs serve as lightweight, hardware-intrinsic entropy sources widely deployed in IoT security applications. However, delay-based PUFs are vulnerable to Machine Learning Attacks MLAs, undermining their assumed unclonability. There are no valid metrics for evaluating P...

CVE-2025-14802

The LearnPress – WordPress LMS Plugin for WordPress is vulnerable to unauthorized file deletion in versions up to, and including, 4.3.2.2 via the /wp-json/lp/v1/material/fileid REST API endpoint. This is due to a parameter mismatch between the DELETE operation and authorization check, where the...

How Cisco Talos powers the solutions protecting your organization

Cisco Talos is Cisco's threat intelligence and security research organization that powers Cisco's product portfolio with that intelligence. While we are well known for the security research in our blog, vulnerability discoveries, and our open-source software, you may not be aware of exactly how o...

CVE-2019-12834

In HT2 Labs Learning Locker 3.15.1, it's possible to inject malicious HTML and JavaScript code into the DOM of the website via the PATHINFO to the dashboards/ URI...

Exploit for Off-by-one Error in Sudo_Project Sudo

ExploitForge - AI-Powered Automatic Exploit Generation !Pyt...

Few-Shot Learning for Security Bug Report Identification

Security bug reports require prompt identification to minimize the window of vulnerability in software systems. Traditional machine learning ML techniques for classifying bug reports to identify security bug reports rely heavily on large amounts of labeled data. However, datasets for security bug...

PT-2026-1425

Name of the Vulnerable Software and Affected Versions LearnPress – WordPress LMS Plugin versions up to and including 4.3.2 Description The LearnPress – WordPress LMS Plugin for WordPress is susceptible to unauthorized data modification. This is due to a missing capability check within the catch l...

Quantum AI for Cybersecurity: A Hybrid Quantum-Classical Models for Attack Path Analysis

Modern cyberattacks are increasingly complex, posing significant challenges to classical machine learning methods, particularly when labeled data is limited and feature interactions are highly non-linear. In this study we investigates the potential of hybrid quantum-classical learning to enhance...

Threat Detection in Social Media Networks Using Machine Learning Based Network Analysis

The accelerated development of social media websites has posed intricate security issues in cyberspace, where these sites have increasingly become victims of criminal activities including attempts to intrude into them, abnormal traffic patterns, and organized attacks. The conventional rule-based...

Integrating Multi-Agent Simulation, Behavioral Forensics, and Trust-Aware Machine Learning for Adaptive Insider Threat Detection

We present a hybrid framework for adaptive insider-threat detection that tightly integrates multi-agent simulation MAS, layered Security Information and Event Management SIEM correlation, behavioral and communication forensics, trust-aware machine learning, and Theory-of-Mind ToM reasoning...

AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization

Cybersecurity poses considerable problems to Cloud Computing CC, especially regarding Intrusion Detection Systems IDSs, facing difficulties with skewed datasets and suboptimal classification model performance. This study presents the Hybrid Intrusion Detection System HyIDS, an innovative IDS that...

PT-2026-1142

Name of the Vulnerable Software and Affected Versions Cloudflare affected versions not specified Description A buffer overflow exists in a simulated API. The issue is identified with a hypothetical identifier. The risk assessment is medium overall, and mitigation is suggested with patches. The...

Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-Based LLM Systems

Low-Rank Adaptation LoRA has become a popular solution for fine-tuning large language models LLMs in federated settings, dramatically reducing update costs by introducing trainable low-rank matrices. However, when integrated with frameworks like FedIT, LoRA introduces a critical vulnerability:...

CVE-2025-68982

Missing Authorization vulnerability in designthemes DesignThemes LMS Addon designthemes-lms-addon allows Exploiting Incorrectly Configured Access Control Security Levels.This issue affects DesignThemes LMS Addon: from n/a through = 2.6...

VULNEXPO

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Towards Eco Friendly Cybersecurity: Machine Learning Based Anomaly Detection with Carbon and Energy Metrics

The rising energy footprint of artificial intelligence has become a measurable component of US data center emissions, yet cybersecurity research seldom considers its environmental cost. This study introduces an eco aware anomaly detection framework that unifies machine learning based network...