Topic
43 articles
Engineering
Learn how Abnormal’s AI Detection Agents analyze customer-reported attacks, identify behavioral patterns, and iteratively generate detectors that generalize beyond static indicators.
How Abnormal engineered a resilient, self-healing AI detection platform that maintains high precision even when dependencies fail.
Explore how Abnormal AI rapidly engineered AI Phishing Coach, a hyper-personalized training platform, by leveraging GenAI, internal developer tools, and an AI-first build process designed for speed and scale.
At Abnormal AI, detecting malicious behavior at scale means aggregating vast volumes of signals in realtime and batch. This post breaks down how we implemented the Signals DAG across both systems to achieve consistency, speed, and detection accuracy at scale.
Explore how Abnormal's engineering team advances internal development with an AI-driven platform that standardizes infrastructure, reduces setup time, and enables both engineers and AI agents to build and deploy services more efficiently.
Discover how Abnormal AI leverages AI tools like Cursor and Model Context Protocol (MCP) in production to accelerate development.
Discover how Abnormal AI accelerates developer velocity with its secure, in-house Model Context Protocol (MCP), integrating tools like GitHub and Jira directly into local environments to streamline workflows without compromising security.
Learn how Abnormal has employed Cursor to optimize our enterprise codebase for LLMs, automate project rules, and build a security-first AI dev culture.
Learn how Abnormal Security minimizes false positives and false negatives with a multi-layered approach to cyberattack detection and email security.
See how behavioral AI detects attacks that legacy defenses miss.
