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
Zyxel
Multiple Zyxel DSL CPE devices contain a post-authentication command injection vulnerability in the CGI program that could allow an authenticated attacker to execute OS commands via a crafted HTTP request.
Microsoft
Microsoft Windows Ancillary Function Driver for WinSock contains a heap-based buffer overflow vulnerability that allows for privilege escalation, enabling a local attacker to gain SYSTEM privileges.
Microsoft
Microsoft Windows Storage contains a link following vulnerability that could allow for privilege escalation. This vulnerability could allow an attacker to delete data including data that results in the service being unavailable.
Trimble
Trimble Cityworks contains a deserialization vulnerability. This could allow an authenticated user to perform a remote code execution attack against a customer's Microsoft Internet Information Services (IIS) web server.
Sophos
Sophos XG Firewall contains a buffer overflow vulnerability that allows for remote code execution via the "HTTP/S bookmark" feature.
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)"