GreyNoise is a real‑time cybersecurity analytics platform that distinguishes benign internet background scanning from targeted threats. Leveraging a global sensor network, it classifies billions of IP addresses daily, enriches security logs, and integrates seamlessly with SIEM, SOAR, and TIP tools. With advanced features like GNQL-powered search, IP timeline visualizations, tag-based threat trends, and comprehensive API access—including a Python SDK—security teams can filter false positives, prioritize real vulnerabilities, and streamline incident response and vulnerability management. Ideal for SOC, threat hunting, and vulnerability management teams, GreyNoise reduces alert fatigue, accelerates triage, and enables smarter, data‑driven decisions. Keywords: internet background noise, threat intelligence, IP classification, GNQL, SOC efficiency.

Features

• Global sensor network and real‑time telemetry that captures unsolicited scan traffic across the internet
• IP classification and tagging assigns metadata (benign, malicious, tool, actor) to observed IPs with related CVEs and intent labels
• Search via GNQL or IP lookup enables stream‑oriented queries, bulk analysis, and custom query language for targeted threat discovery
• IP Timeline visualization shows historical activity patterns over 90 days for deeper context on suspicious IP behavior
• Trends and tag analytics track exploit campaigns, tool usage, and attacker infrastructure over time
• Extensive API integration and SDK support for seamless use in SIEM, SOAR, TIP, vulnerability management, and custom scripts
• Bulk IP analysis and enrichment capabilities support high‑volume workflows and automated alert triage
• Enterprise‑grade reliability and context with real‑time feeds, low‑latency updates, and verifiable intelligence for high‑stakes environments