Threat Surface Pulse
Real-time snapshots from CISA KEV and other signals. Highlights exposed risk and trending CVEs.
- Recent KEV additions
- Exec-ready talking points
Microsoft
Microsoft Windows SmartScreen contains a security feature bypass vulnerability that allows an attacker to bypass the SmartScreen user experience and inject code to potentially gain code execution, which could lead to some data exposure, lack of system availability, or both.
Roundcube
Roundcube Webmail contains a persistent cross-site scripting (XSS) vulnerability that can lead to information disclosure via malicious link references in plain/text messages.
Fortinet
Fortinet FortiOS contains an out-of-bound write vulnerability that allows a remote unauthenticated attacker to execute code or commands via specially crafted HTTP requests.
Google Chromium V8 contains a type confusion vulnerability that allows a remote attacker to execute code via a crafted HTML page. This vulnerability could affect multiple web browsers that utilize Chromium, including, but not limited to, Google Chrome, Microsoft Edge, and Opera.
Apple
Apple iOS, iPadOS, macOS, tvOS, and watchOS contain a time-of-check/time-of-use (TOCTOU) memory corruption vulnerability that allows an attacker with read and write capabilities to bypass Pointer Authentication.
AI/ML Signal Tracker
Tracks model releases, repos, and outages; summarizes impact for platform roadmaps.
- Top moving repos
- Signal strength
RepiFahmiSidiq/Onchain-Security-Suite
🛡️ Strengthen Web3 security with our AI-driven token auditor and reputation engine, ensuring safer transactions and reliable smart contracts.
mikehubers/Awesome-AI-For-Security
🛡️ Discover essential tools and resources that leverage AI for enhancing cybersecurity, focusing on modern technologies and their applications in security operations.
MUKUL-TIWARI/CyberShield-Security-Suite
AI-powered phishing, email, and vishing detection system.
zimingttkx/Network-Security-Based-On-ML
🛡️ 基于机器学习的网络安全威胁检测系统 | 完整的端到端ML项目，包含数据处理、模型训练、Web界面和API服务 | 适合初学者学习的实战项目 | Python + FastAPI + Scikit-learn + XGBoost
Western-OC2-Lab/AutoML-and-Adversarial-Attack-Defense-for-Zero-Touch-Network-Security
This repository includes code for the AutoML-based IDS and adversarial attack defense case studies presented in the paper "Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis" published in IEEE Transactions on Network and Service Management.
prashantshukla01/Network_Security
This project aims to detect malicious network activity using Machine Learning-based Intrusion Detection. It focuses on analyzing network traffic data to classify whether behavior is normal or attack-related, helping organizations strengthen their cybersecurity posture.