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
Juniper
Juniper Junos OS contains an improper isolation or compartmentalization vulnerability. This vulnerability could allows a local attacker with high privileges to inject arbitrary code.
Apple
Apple iOS, iPadOS, macOS, and other Apple products contain an out-of-bounds write vulnerability in WebKit that may allow maliciously crafted web content to break out of Web Content sandbox. This vulnerability could impact HTML parsers that use WebKit, including but not limited to Apple Safari and non-Apple products which rely on WebKit for HTML processing.
Microsoft
Microsoft Windows New Technology File System (NTFS) contains a heap-based buffer overflow vulnerability that allows an unauthorized attacker to execute code locally.
Microsoft
Microsoft Windows New Technology File System (NTFS) contains an out-of-bounds read vulnerability that allows an authorized attacker to disclose information locally.
Microsoft
Microsoft Windows Fast FAT File System Driver contains an integer overflow or wraparound vulnerability that allows an unauthorized attacker to execute code locally.
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.
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)"