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
Google Chrome Blink contains a heap use-after-free vulnerability that allows an attacker to potentially perform out of bounds memory access via a crafted HTML page.
Microsoft
An information disclosure vulnerability exists in the way that the Windows SMB Server handles certain requests, which could lead to information disclosure from the server.
Microsoft
A local elevation of privilege vulnerability exists in how splwow64.exe handles certain calls. An attacker who successfully exploited the vulnerability could elevate privileges on an affected system from low-integrity to medium-integrity.
Google Chrome WebAudio contains a use-after-free vulnerability that allows a remote attacker to potentially exploit heap corruption via a crafted HTML page.
Mozilla
Mozilla Firefox and Thunderbird contain a type confusion vulnerability that can occur when manipulating JavaScript objects due to issues in Array.pop, allowing for an exploitable crash.
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
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.