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
SonicWall
SonicWall SonicOS contains an improper authentication vulnerability in the SSLVPN authentication mechanism that allows a remote attacker to bypass authentication.
SimpleHelp
SimpleHelp remote support software contains multiple path traversal vulnerabilities that allow unauthenticated remote attackers to download arbitrary files from the SimpleHelp host via crafted HTTP requests. These files may include server configuration files and hashed user passwords.
Apple
Apple iOS and iPadOS contains an incorrect authorization vulnerability that allows a physical attacker to disable USB Restricted Mode on a locked device.
Mitel
Mitel 6800 Series, 6900 Series, and 6900w Series SIP Phones, including the 6970 Conference Unit, contain an argument injection vulnerability due to insufficient parameter sanitization during the boot process. Successful exploitation may allow an attacker to execute arbitrary commands within the context of the system.
Zyxel
Multiple Zyxel DSL CPE devices contain a post-authentication command injection vulnerability in the management commands that could allow an authenticated attacker to execute OS commands via Telnet.
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)"