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InsightIDR
Additional Info
| Company | Rapid7 |
| Website | https://www.rapid7.com/products/insightidr/ |
| Company size (employees) | 1,000 to 4,999 |
Overview
Two decades ago, SIEMs were born from the need to manage and analyze all of the rich data coming from infrastructure and centralized servers. However, intelligently correlating this data to proactively detect compromised and risky behavior has been an afterthought. InsightIDR was built hand-in-hand with infosec teams to unify security data across endpoint, network, and cloud to provide visibility across your ecosystem.
InsightIDR detects the threats other tools miss through a combination of User Behavior Analytics (UBA), deception technology, and native EDR agents. Security teams no longer need to write & tune rules or hire certified data splunkers to get the answers hidden across users, log files and endpoints. Customers report 20 times faster investigations now that real-time log search, user activity and endpoint data are in a single solution.
Unlike other SIEMs, user behavior analytics (UBA) and endpoint detection and response (EDR) are core components of InsightIDR. From its inception, InsightIDR was built on elastic compute and big data technologies, so customers are getting up and running in hours—without the worries of scaling or data management.
How we are different
InsightIDR is purpose-built for Incident Detection & Response (IDR), backed by our continuous research into the attacker. Our intelligent, patented detections are a result of collaboration with the Metasploit project, our elite red teams, and our Security Operations Centers. Most importantly, no more prolonged deployments, consulting, and support—you can identify compromise and check the box for compliance without it becoming a second full-time job.
Unify your data: Centralize, search, and visualize all of your logs—no data degree required.
Intelligent incident detection: Pre-built detections alert you of intruder presence at each step of the attack chain.
Prioritize your search: Automatically identify risky users and misconfigurations after adding in data sources.
