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
Sophos
Sophos Web Appliance contains a command injection vulnerability in the warn-proceed handler that allows for remote code execution.
Oracle
Oracle Fusion Middleware contains an unspecified vulnerability in the WLS Core Components that allows an unauthenticated attacker with network access via IIOP to compromise the WebLogic Server.
Microsoft
Microsoft Windows Desktop Window Manager (DWM) Core Library contains an unspecified vulnerability that allows for privilege escalation.
Microsoft
Microsoft Windows SmartScreen contains a security feature bypass vulnerability that could allow an attacker to bypass Windows Defender SmartScreen checks and their associated prompts.
Microsoft
Microsoft Windows Cloud Files Mini Filter Driver contains a privilege escalation vulnerability that could allow an attacker to gain SYSTEM privileges.
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.