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 Common Log File System (CLFS) driver contains a heap-based buffer overflow vulnerability that allows a local attacker to escalate privileges.
CyberPersons
CyberPanel contains an incorrect default permissions vulnerability that allows for authentication bypass and the execution of arbitrary commands using shell metacharacters in the statusfile property.
Zyxel
Multiple Zyxel firewalls contain a path traversal vulnerability in the web management interface that could allow an attacker to download or upload files via a crafted URL.
ProjectSend
ProjectSend contains an improper authentication vulnerability that allows a remote, unauthenticated attacker to enable unauthorized modification of the application's configuration via crafted HTTP requests to options.php. Successful exploitation allows attackers to create accounts, upload webshells, and embed malicious JavaScript.
North Grid
North Grid Proself Enterprise/Standard, Gateway, and Mail Sanitize contain an improper restriction of XML External Entity (XXE) reference vulnerability, which could allow a remote, unauthenticated attacker to conduct an XXE attack.
AI/ML Signal Tracker
Tracks model releases, repos, and outages; summarizes impact for platform roadmaps.
- Top moving repos
- Signal strength
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.
RepiFahmiSidiq/Onchain-Security-Suite
🛡️ Strengthen Web3 security with our AI-driven token auditor and reputation engine, ensuring safer transactions and reliable smart contracts.
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.
PeterHovng/HUTECH_DACN.CyberSecurity
Đồ án chuyên ngành - ngành An ninh mạng "Hệ thống phát hiện tấn công mạng trên AWS bằng Machine Learning (Network Intrusion Detection System - NIDS)"