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
Palo Alto Networks
Palo Alto Networks Expedition contains an OS command injection vulnerability that allows an unauthenticated attacker to run arbitrary OS commands as root in Expedition, resulting in disclosure of usernames, cleartext passwords, device configurations, and device API keys of PAN-OS firewalls.
Atlassian
Atlassian Jira Server and Data Center contain a path traversal vulnerability that allows a remote attacker to read particular files in the /WEB-INF/web.xml endpoint.
Cisco
Cisco Adaptive Security Appliance (ASA) contains a cross-site scripting (XSS) vulnerability in the WebVPN login page. This vulnerability allows remote attackers to inject arbitrary web script or HTML via an unspecified parameter.
Metabase
Metabase contains a local file inclusion vulnerability in the custom map support in the API to read GeoJSON formatted data.
Microsoft
Microsoft Windows contains an NTLMv2 hash spoofing vulnerability that could result in disclosing a user's NTLMv2 hash to an attacker via a file open operation. The attacker could then leverage this hash to impersonate that user.
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
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)"