Identity-driven detection and response

Your company is under attack, but you can’t see who’s responsible. Traditional security tools fragment visibility across environments, leaving security teams blind to the actual identities behind malicious activity. When credentials are stolen from developer laptops, third-party vendors are compromised, or insiders misuse access, organizations struggle to answer the fundamental question: "Who did this? Traditional solutions focus on finding "bad things" - malicious IPs, domains, and signatures - but adversaries simply buy these same tools and ensure they don't trigger alerts.

By the time you detect the adversary, the damage is done. The adversary operates at unprecedented speed, alongside infrastructure spinning up and down in seconds. Traditional polling and scanning approaches that check every few hours or days are fundamentally incompatible with this reality. Adversaries achieve their mission between scans, moving laterally with stolen credentials or using compromised service accounts. The industry's focus on traditional endpoint agents and manual SIEM correlation creates a massive detection gap in serverless and containerized environments where traditional agents can't be deployed.

You need an army of experts just to understand what happened. Modern breaches require correlating activity across multiple tools, accounts, regions, and services. Security teams must manually piece together CloudTrail logs, attempt to map service accounts to human users, and understand complex permission chains across AWS, GitHub, and container environments. When an incident occurs, teams spend hours or days just trying to establish basic facts about what happened, who was involved, and what systems were affected - all while the adversary continues operating.