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 SmartScreen Prompt contains a security feature bypass vulnerability that allows an attacker to bypass the Mark of the Web (MotW) feature. This vulnerability can be chained with CVE-2023-38831 and CVE-2024-21412 to execute a malicious file.
CrushFTP
CrushFTP contains an unspecified sandbox escape vulnerability that allows a remote attacker to escape the CrushFTP virtual file system (VFS).
Cisco
Cisco Adaptive Security Appliance (ASA) and Firepower Threat Defense (FTD) contain a privilege escalation vulnerability that can allow local privilege escalation from Administrator to root.
Cisco
Cisco Adaptive Security Appliance (ASA) and Firepower Threat Defense (FTD) contain an infinite loop vulnerability that can lead to remote denial of service condition.
Microsoft
Microsoft Windows Print Spooler service contains a privilege escalation vulnerability. An attacker may modify a JavaScript constraints file and execute it with SYSTEM-level permissions.
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.