GreyNoise
'Anti-threat-intelligence' vendor that fingerprints internet-wide scanning traffic to help analysts filter out background internet noise from genuinely targeted attacks.
Visit Website ↗Overview
GreyNoise, founded by Andrew Morris in September 2017 and headquartered in Washington, D.C., addresses a specific and underappreciated analyst problem: the vast majority of internet scanning traffic hitting any given organization is background noise — research scanners, botnets doing indiscriminate mass-scanning, and misconfigured devices — rather than targeted activity aimed specifically at that organization. Without a way to filter this noise, security analysts waste significant time investigating alerts that are not actually targeted.
GreyNoise operates a large network of internet sensors to observe and fingerprint mass-scanning behavior at internet scale, then makes that data queryable so analysts can quickly check whether a given IP address is part of known background noise or represents genuinely novel, targeted activity. This “anti-threat-intelligence” framing — telling analysts what to ignore, not just what to flag — is a structurally different value proposition than most threat-intel feeds, which are built to surface indicators rather than suppress false positives.
The company has attracted investment from In-Q-Tel, the CIA-affiliated strategic investment arm, alongside CRV, Inner Loop Capital, Paladin Capital Group, and Radian Capital, with disclosed funding of roughly $21 million-plus across seed and Series A/B rounds.
Innovation Matrix Assessment
Continued expansion of its sensor network and API/data products, alongside In-Q-Tel's strategic investment, indicates sustained development momentum.
Directly reduces alert fatigue by filtering internet background noise, a well-documented and persistent SOC pain point.
In-Q-Tel's investment is a notable, independently verifiable credibility signal, though disclosed funding (~$21M+) is modest relative to larger threat-intel peers.
Its 'anti-threat-intelligence' model — telling analysts what to deprioritize rather than adding more indicators to investigate — inverts the typical threat-feed value proposition.
In-Q-Tel's backing and continued adoption by SOC teams suggest real operational value, though independent quantitative efficacy studies were not located in this research.
As internet-wide scanning and automated exploitation attempts increase in volume, noise-filtering becomes more, not less, valuable to alert-fatigued SOC teams.
Why CISOs Should Care
GreyNoise cuts SOC investigation time by telling analysts which scanning traffic is indiscriminate internet background noise versus genuinely targeted reconnaissance, directly reducing false-positive alert fatigue.
What Makes It Different
Rather than adding more indicators for analysts to investigate, it inverts the typical threat-intelligence model by telling teams what they can safely deprioritize, based on internet-scale sensor fingerprinting.
The Matrix Verdict
70/100 — MEANINGFUL INNOVATOR
A small but technically distinctive vendor solving a real and underserved SOC problem, with credible strategic backing from In-Q-Tel; genuinely disruptive in framing even if its funding scale remains modest.
Editorial Note: Claims vs. Verified Findings
In-Q-Tel's investment and the company's seed/Series A funding are corroborated by independent press coverage (SecurityWeek); operational-impact claims are largely vendor- and customer-testimonial-sourced.
Sources
Alternatives to GreyNoise
Unknown Cyber Inc.
Malware genomics platform using automated deep static analysis and code-lineage comparison to identify unseen malware, variants, and supply-chain…
Horizon3.ai
Autonomous penetration testing company whose NodeZero platform self-attacks networks without persistent agents, aiming to replace annual manual pentests…
Pentera
Automated security validation platform that safely runs real attack techniques against production environments to prove which exposures are…
CrowdStrike
Publicly traded endpoint and cloud security leader whose Falcon Exposure Management module extends its platform into AI-driven vulnerability…
Reality Defender
Deepfake and synthetic media detection company offering real-time detection across voice, video, image, and text for enterprises and…
Recorded Future
Threat intelligence platform aggregating open, dark web, and technical sources into real-time risk scoring; acquired by Mastercard in…