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
Cisco
A vulnerability in the web interface of the Cisco VPN Routers could allow an unauthenticated, remote attacker to execute arbitrary code as root and gain full control of an affected system.
NETGEAR
dnslookup.cgi on NETGEAR DGN2200 devices with firmware through 10.0.0.50 allows remote authenticated users to execute arbitrary OS commands
Citrix
A vulnerability has been identified in the management interface of Citrix NetScaler SD-WAN Enterprise and Standard Edition and Citrix CloudBridge Virtual WAN Edition that could result in an unauthenticated, remote attacker being able to execute arbitrary code as a root user. This vulnerability also affects XenMobile Server.
Cisco
A vulnerability in the Cisco Cluster Management Protocol (CMP) processing code in Cisco IOS and Cisco IOS XE Software could allow an unauthenticated, remote attacker to cause a reload of an affected device or remotely execute code with elevated privileges.
Apache
When running Apache Tomcat, it is possible to upload a JSP file to the server via a specially crafted request. This JSP could then be requested and any code it contained would be executed by the server.
AI/ML Signal Tracker
Tracks model releases, repos, and outages; summarizes impact for platform roadmaps.
- Top moving repos
- Signal strength
Rizwan723/MCP-Security-Proxy
🔒 Implement a security proxy for Model Context Protocol using ensemble anomaly detection to classify requests as benign or attack for enhanced safety.
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检测系统 | 集成Kitsune/LUCID算法 | 支持ML/DL/RL模型 | 99.58%攻击检测准确率 | 19913 QPS | Docker/K8s部署
hmshujaatzaheer/federated-scion-security-framework
Formally Verified Federated Learning Framework for Privacy-Preserving Anomaly Detection in Path-Aware Networks (PhD Research)
Mohamed-Tamer-Nassr/Network-Security-Model
A machine-learning–based phishing detection system that analyzes URL and network features to identify malicious sites, built with Python, FastAPI, Scikit-Learn, MongoDB, and Docker.