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
Microsoft
Microsoft Windows Kernel contains a time-of-check to time-of-use (TOCTOU) race condition vulnerability that could allow for privilege escalation.
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.
Ivanti
Ivanti Cloud Services Appliance (CSA) contains a SQL injection vulnerability in the admin web console in versions prior to 5.0.2, which can allow a remote attacker authenticated as administrator to run arbitrary SQL statements.
Fortinet
Fortinet FortiOS, FortiPAM, FortiProxy, and FortiWeb contain a format string vulnerability that allows a remote, unauthenticated attacker to execute arbitrary code or commands via specially crafted requests.
Microsoft
Microsoft Windows MSHTML Platform contains an unspecified spoofing vulnerability which can lead to a loss of confidentiality.
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.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)"