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
Progress
Progress Telerik Report Server contains an authorization bypass by spoofing vulnerability that allows an attacker to obtain unauthorized access.
Microsoft
Microsoft Windows Error Reporting Service contains an improper privilege management vulnerability that allows a local attacker with user permissions to gain SYSTEM privileges.
Android
Android Pixel contains an unspecified vulnerability in the firmware that allows for privilege escalation.
PHP Group
PHP, specifically Windows-based PHP used in CGI mode, contains an OS command injection vulnerability that allows for arbitrary code execution. This vulnerability is a patch bypass for CVE-2012-1823.
Arm
Arm Bifrost and Valhall GPU kernel drivers contain a use-after-free vulnerability that allows a local, non-privileged user to make improper GPU memory processing operations to gain access to already freed memory.
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.
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.