Threat Hunting

Needle in the haystack. Found

Quickly identify anomalous behavior and catch targeted threats

Overview

Effective threat hunting isn't just about finding more data, it’s about finding the right data. GreyNoise empowers your hunt team to adopt the PEAK Framework by correlating your internal traffic against our real-time map of internet-wide mass scanning.

By using GreyNoise to filter out opportunistic probes, benign scanners, and botnet noise, you reveal the statistically significant anomalies that represent targeted attacks. Stop chasing false positives and focus on the signals that actually threaten your perimeter.

How GreyNoise
Helps You Hunt Smarter

Focus effort on highest risks

Eliminate time-consuming research of benign and opportunistic scanning, allowing hunters to focus on infrastructure actually used by threat actors.

Supports threat research and hypothesis development

Hunters can use GreyNoise to conduct threat research, validate assumptions, and explore attack vectors in order to develop hypotheses.

Correlate isolated incidents

GreyNoise helps threat hunters link isolated incidents to larger campaigns by mapping attacker infrastructure and patterns, connecting logged IPs to those exploiting relevant vulnerabilities.

How GreyNoise Maps to the PEAK Hunting Framework

Explore Available Fields

Filter by category & search available IP fields and their uses with GreyNoise.
Categories
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NAME
Description & Use
Slug
Short identifier for the tag. Useful in queries and API lookups.
Tag Information
Source Bytes
Number of bytes sent from source IP. Useful for traffic analysis.
Observed Request Data
Source Country
Country where the IP is registered. Provides attacker infrastructure location context.
IP Address Metadata
Source Country Code
ISO country code for the IP’s registration country.
IP Address Metadata
Source Country Count
Count of IPs originating from each country. Useful for geo-distribution of attacks.
Stats & Aggregates
Source Latitude
Latitude of IP’s registered location. Useful for geo-mapping.
IP Address Metadata
Source Longitude
Longitude of IP’s registered location. Useful for geo-mapping.
IP Address Metadata
Spoofable
Shows whether the IP completed a valid TCP handshake. If false, traffic may be spoofed or fake.
Classification
Spoofable Count
Count of spoofable vs. non-spoofable IPs. Highlights volume of potentially fake traffic.
Stats & Aggregates
TLS Cipher
TLS cipher suites used. Adds context for attacker SSL/TLS configurations.
Protocol Data
TLS JA4
JA4 TLS fingerprint values. Useful for higher-fidelity TLS fingerprinting.
Protocol Data
Tags Count
Count of IPs associated with specific tags. Helps identify common behaviors at scale.
Stats & Aggregates
Timeline
Key timeline details about when the CVE was published, updated, and added to CISA (https://www.cisa.gov/known-exploited-vulnerabilities-catalog). Useful for understanding how long the issue has been known.
Timeline & Lifecycle
Timeline CISA KEV Date Added
Date the vulnerability was added to CISA’s Known Exploited Vulnerabilities (KEV) catalog. Vulnerabilities in KEV should be prioritized for remediation per federal guidance.
Timeline & Lifecycle
Timeline CVE Last Updated Date
The last date the CVE entry was updated in the database. Useful for tracking changes in severity, affected products, or exploit status.
Timeline & Lifecycle
Timeline CVE Published Date
The date the CVE was first published. Helps determine how long attackers have potentially been aware of the vulnerability.
Timeline & Lifecycle
HTTP Method
HTTP methods used (e.g., GET, POST). Provides context on attacker request.
Protocol Data
HTTP Path
Web paths targeted during scanning (e.g., /robots.txt, /admin). Reveals reconnaissance goals.
Protocol Data
HTTP Request Authorization
Authorization headers observed in HTTP requests. May reveal brute-force attempts.
Protocol Data
HTTP Request Cookies
Cookies included in HTTP requests. Adds context on reconnaissance or exploit attempts.
Protocol Data
HTTP Request Headers
Headers used in HTTP requests. Useful for tool fingerprinting.
Protocol Data
HTTP Request Origin
Origin IPs or addresses set in HTTP headers. May indicate spoofing.
Protocol Data
HTTP Useragent
User-Agent strings observed. Useful for identifying attacker tools or crawlers.
Protocol Data
Hassh Fingerprint
Fingerprint hash of SSH client behavior. Helps identify SSH attack tools.
Protocol Data
Hassh Port
Port associated with observed SSH behavior. Adds protocol context.
Protocol Data
ID
Unique tag identifier.
Tag Information
ID
Unique identifier for the record. Used to track and reference the vulnerability consistently across systems and reports.
Identification & Details
IP
The observed IP address itself. Primary entity to investigate or correlate across alerts.
Identity & Ownership
Intention
Tag’s intent classification: benign, malicious, suspicious, or unknown. Adds risk context.
Tag Information
JA3 Fingerprint
JA3 TLS fingerprint of client behavior. Useful for identifying attack tools, actors, botnets, and campaigns.
Protocol Data
JA3 Port
Port associated with observed JA3 TLS activity.
Protocol Data
Last Seen
Last date the IP was observed by GreyNoise sensors. Indicates recency of activity.
Activity Timeline

Find your needle.