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
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