Clover Security embeds AI agents into the design and architecture phase to catch business logic and architecture risks that traditional downstream AppSec tooling misses. The platform’s Memory Agent, Feature Context Graph, and agent fleet automate design reviews, detect implementation drift and AI-generated code risks, and have delivered measurable coverage and speed gains for customers. #CloverSecurity #Neo4j
Keypoints
- Clover shifts AppSec upstream by embedding AI-driven security reviews into the design and architecture phase.
- The Memory Agent and Feature Context Graph give agents organizational and feature-specific context for precise, actionable findings.
- An agent fleet including Design Review, Developer Guidance, MCP, and Vibe Coding Agents detects business logic flaws, drift, and AI-generated code issues.
- An observability dashboard reveals which LLMs and coding agents are in use, enabling policy enforcement and visibility across development.
- Early customers like Neo4j, Lemonade, and Virgin Money report dramatically higher review coverage and much faster, more consistent design reviews.
Read More: https://www.cybersecuritypulse.net/p/the-appsec-model-was-built-for-a