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
Use-after-free vulnerability in Microsoft Internet Explorer allows remote attackers to execute remote code via a crafted web site that triggers access to a deleted object.
Oracle
Unspecified vulnerability in the Java Runtime Environment (JRE) component in Oracle Java SE allows remote attackers to affect confidentiality, integrity, and availability via Unknown vectors related to 2D
Mozilla
Mozilla Firefox and Thunderbird do not properly handle onreadystatechange events in conjunction with page reloading, which allows remote attackers to cause a denial-of-service (DoS) or possibly execute malicious code via a crafted web site.
Oracle
The default Java security properties configuration did not restrict access to the com.sun.org.glassfish.external and com.sun.org.glassfish.gmbal packages. An untrusted Java application or applet could use these flaws to bypass Java sandbox restrictions.
Microsoft
Microsoft Word allows attackers to execute remote code or cause a denial-of-service (DoS) via crafted RTF data.
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.
XSource-Sec/awesome-ai-security
A curated list of AI security resources, tools, research papers, and more