GreyNoise Intelligence is a threat data solution that collects and analyzes internet-wide scanning activity to differentiate between opportunistic background noise and targeted threats. Utilizing a distributed network of sensors and honeypots, the system monitors for mass scanning and active vulnerability exploitation. It provides contextual data on IP addresses, classifying their intent as benign, malicious, suspicious, or unknown, and also identifies known business services. This classification enables security teams to filter out irrelevant alerts generated by benign scanners and internet-wide background activity, allowing them to focus resources on statistically significant anomalies.
The product supplies detailed metadata for observed IP addresses, including actor attribution, spoofability, and the specific Common Vulnerabilities and Exposures (CVEs) being exploited, which facilitates vulnerability prioritization based on active exploitation. Organizations can access the dataset through a REST API, a Python SDK, and direct integrations with SIEM and SOAR platforms. These access methods support single IP lookups, bulk queries for up to 10,000 IPs, and advanced historical queries using the GreyNoise Query Language (GNQL). The data is used to enrich logs, automate investigative workflows, and suppress noisy alerts.
