Hunt against internet-scale data.
Threat hunting runs on hypotheses tested against data. Threat Hunting runs hypotheses against the indexed dataset that drives the rest of the platform: 400M+ domains, 2B+ subdomains, 200B+ DNS records, 30B+ SSL certificates, plus the full CVE corpus enriched with EPSS and CISA KEV signal.
Hypothesis-driven hunting against the data layer underneath.
SOC analysts, threat-hunting teams, and CTI functions run this workflow. The question they answer: starting from a hypothesis (this actor group is targeting our sector, this vulnerability class is being weaponized, this domain pattern correlates with attack infrastructure), what does the data say? Pre-Deepinfo, hunters stitch evidence from multiple OSINT and threat-intel tools. Post-Deepinfo, hunters query one dataset.
Hunting workflows include actor-driven (start from a Threat Actor Intelligence profile, pivot through the actor's known infrastructure), indicator-driven (start from an IOC, pivot through Domain Search reverse lookups to find connected infrastructure), and pattern-driven (start from an aggregate-analytics observation, drill down to the specific domains driving the pattern).
Outcomes: hunting hypotheses test faster against richer data; evidence-of-absence has confidence backing because the corpus coverage is internet-scale; novel attack patterns surface earlier because the aggregate analytics show shifts in the dataset.
IOC feeds, intelligence, and the data layer.
IOC Feeds for indicator-driven hunting. Threat Actor Intelligence for actor-driven hypotheses. Domain Search and Vulnerability Search for pivot. Domain Intelligence and Vulnerability Intelligence for aggregate analytics.
IOC Feeds.
Curated streams of malicious domains, phishing infrastructure, C2 endpoints, malware-distribution IPs, and actor-attributed IOC packages. STIX/TAXII for threat-intel platforms; JSON/CSV for SIEM ingestion.
Threat Actor Intelligence.
Actor profiles with TTPs mapped to MITRE ATT&CK, infrastructure indicators, recent campaigns, and pivots from any indicator back to actor and campaign context.
Domain and Vulnerability Search.
Reverse-IP, reverse-MX, sametime-registered, and other pivot queries across the domain corpus. Filter-based CVE search across the enriched vulnerability corpus.
Aggregate intelligence.
Domain Intelligence and Vulnerability Intelligence for structural questions. Pattern queries surface registration trends, TLD distributions, EPSS history per CVE class, CWE timelines.
Customers using threat-hunting workflows at real depth.
A cybersecurity ratings provider
Sourcing internet-scale data through Deepinfo APIs to power external scoring across millions of organizations.
Read the storyThreat intelligence operations
Equip your security teams with dark web search, threat actor profiling, and IOC feeds.
Read the use caseDomain intelligence and research
Search, investigate, and analyze domain ownership, infrastructure, and history at scale.
Read the use case“Hypothesis-driven hunting against an internet-scale dataset is what we'd been missing. We now run hunts against historical DNS and SSL data that were impossible to query at this scale before.”
Related use cases.
Operational threat intelligence, not just feed subscriptions.
Threat intelligence is useful when it lands in the systems analysts already operate, not when it sits in a portal nobody opens.
See use case USE CASEInvestigate incidents using the data layer underneath.
Incident response runs on time.
See use case USE CASESee your data in the underground before customers see it on the news.
Brand mentions, credential dumps, and infrastructure references in dark-web channels typically precede public news by weeks.
See use caseTest a threat-hunting hypothesis against the dataset.
Book a demo. We'll walk through actor-driven, indicator-driven, and pattern-driven hunting workflows against scenarios you bring.