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
An elevation of privilege vulnerability exists in the way that the Windows Kernel handles objects in memory. An attacker who successfully exploited the vulnerability could execute code with elevated permissions.
Microsoft
Microsoft Update Notification Manager contains an unspecified vulnerability that allows for privilege escalation.
Apple
Apple iOS, macOS, watchOS, and tvOS contain a memory corruption vulnerability that could allow for privilege escalation.
Apple
Apple iOS contains a memory corruption vulnerability which could allow an attacker to perform remote code execution.
Microsoft
An information disclosure vulnerability exists when Internet Explorer improperly handles objects in memory. An attacker who successfully exploited this vulnerability could test for the presence of files on disk.
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
raghavpoonia/ai-security-mastery
Complete 90-day learning path for AI security: ML fundamentals → LLM internals → AI threats → Detection engineering. Built from first principles with NumPy implementations, Jupyter notebooks, and production-ready detection systems.
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.