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
Adobe
Adobe Flash Player contains an incorrect default permissions vulnerability in the Firefox sandbox that allows a remote attacker to execute arbitrary code via crafted SWF content.
Adobe
Adobe Flash Player contains an integer underflow vulnerability that allows a remote attacker to execute arbitrary code.
Progress
Progress WhatsUp Gold contains a SQL injection vulnerability that allows an unauthenticated attacker to retrieve the user's encrypted password if the application is configured with only a single user.
Microsoft
Microsoft Windows MSHTML Platform contains a user interface (UI) misrepresentation of critical information vulnerability that allows an attacker to spoof a web page. This vulnerability was exploited in conjunction with CVE-2024-38112.
Ivanti
Ivanti Cloud Services Appliance (CSA) contains an OS command injection vulnerability in the administrative console which can allow an authenticated attacker with application admin privileges to pass commands to the underlying OS.
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.AWS
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)"