// solutions / threat_hunting

Intelligence for Threat Hunters

10,168 IOCs, 214 threat actors, and cross-correlation intelligence to fuel your hunts — from hypothesis to validation.

[ start_hunting ]
10,168
IOCs tracked
214
threat actors
465
MITRE techniques
10
correlation types
the problem

Hunting without intelligence is just searching

You can query your SIEM all day. Without the right intelligence behind the hypothesis, you're looking for a needle in a haystack the size of a continent.

[ / ] scattered_intel

Scattered Intelligence Sources

Actor intel lives in one feed. IOCs come from another. MITRE mappings are in a spreadsheet. CVE data is on yet another platform. Building a complete picture of a threat actor requires six browser tabs, three API calls, and an hour of manual correlation. By then, the hunt window has closed.

[ ? ] partial_profiles

Incomplete Actor Profiles

Your threat feed tells you APT29 is active. But what tools are they using this quarter? Which new infrastructure have they spun up? What techniques have they added to their playbook since the last advisory? Partial profiles lead to partial hypotheses, which lead to missed detections.

[ x ] no_correlation

No IOC Cross-Correlation

Two threat reports mention the same C2 IP, but they attribute it to different actors. Is it shared infrastructure? An operational relay? A compromised host reused by multiple groups? Without cross-correlation across your entire intelligence corpus, these connections remain invisible — and so do the operators behind them.

[ ~ ] manual_mitre

Manual MITRE Mapping

You read the report, identify the techniques, and manually map them to the MITRE framework. Then you compare against your detection coverage. Then you identify the gaps. Every step is manual, every step introduces error, and every step takes time you could spend actually hunting.

the solution

How Threadlinqs fuels your hunts

Unified intelligence with cross-correlation built in. Every data point connected to every other data point.

01

Enriched IOC Feeds with Cross-References

Every IOC in Threadlinqs is enriched with data from ThreatFox, MalwareBazaar, and AbuseIPDB. Network indicators include DNS resolution history, ASN ownership, geolocation, and hosting provider. File indicators include hashes across MD5, SHA-1, and SHA-256, plus associated malware families. Behavioral indicators are mapped to MITRE techniques with confidence scoring. When you search an IP, you don't get a reputation score — you get its entire operational history.

02

Actor Dossiers with Full TTP Profiles

The Actor Attribution Explorer provides complete dossiers for 214 tracked threat actors. Each profile includes known aliases, nation-state attribution, targeted sectors, associated campaigns, full MITRE technique coverage, IOC inventory, detection rules, and timeline of activity. The radial mind-map visualization shows relationships between an actor's tools, targets, infrastructure, and techniques — all interactive, all explorable.

03

Cross-Actor Correlation Engine

Threadlinqs runs 10 correlation types across the entire intelligence corpus: IP matching, tag overlap, actor tool sharing, watermark clustering, MITRE technique similarity, nation-state proximity, timeline proximity, domain matching, domain fronting detection, and behavioral fingerprinting. When two actors share infrastructure, the correlation engine surfaces it automatically — complete with confidence scores and evidence chains.

04

DNS Enrichment and Infrastructure Mapping

Submit any domain or IP to the DNS enrichment engine. Get full resolution history, associated domains, hosting provider changes over time, and connections to known threat infrastructure. The Wild C2 Intelligence Center tracks active command-and-control servers across frameworks — Cobalt Strike, Sliver, Havoc, Mythic, and more — with beacon configuration extraction and operator clustering.

actor intelligence

Deep actor profiles, not shallow summaries

Every actor dossier is a complete intelligence package. Here's what a single profile contains.

Lazarus Group
also: HIDDEN COBRA, Zinc, Labyrinth Chollima, APT38
DPRK critical severity T1566 Phishing T1059 Command & Scripting T1071 Application Layer Protocol supply-chain cryptocurrency financial
47
linked threats
312
IOCs
89
MITRE techniques
141
detections
workflow

The intelligence-driven hunt cycle

How threat hunters use Threadlinqs from hypothesis to validation.

01

Identify Actor

Browse the Actor Attribution Explorer. Filter by nation-state, severity, or sector targeting. Select an actor of interest based on relevance to your environment.

02

Review TTPs

Explore the actor's MITRE technique coverage. Identify techniques they favor — initial access vectors, persistence mechanisms, exfiltration methods. Understand the playbook.

03

Search IOCs

Pull the actor's IOC inventory. Cross-reference against your environment logs. Check for DNS resolution matches, file hash hits, and network connection overlaps.

04

Build Hypothesis

Combine TTP patterns with IOC hits to form a hunting hypothesis. Use the cross-correlation engine to find shared infrastructure with related actors.

05

Deploy Detection

Copy relevant SPL, KQL, or Sigma rules from the actor's detection set. Deploy as scheduled searches or real-time alerts in your SIEM.

06

Validate

Use attack simulations mapped to the actor's techniques. Confirm detections fire. Document findings and close the hunt loop with evidence.

intelligence sources

Cross-referenced from multiple feeds

Every indicator is enriched with data from trusted external sources, not just our own research.

ThreatFox / abuse.ch

Malware IOC Repository

Cross-referenced indicators with ThreatFox's community-sourced IOC database. Malware family classification, first-seen timestamps, and reporter confidence levels augment every matched indicator in the Threadlinqs feed.

network + file + behavioral indicators
MalwareBazaar / abuse.ch

Malware Sample Intelligence

File hash indicators are checked against MalwareBazaar's sample repository. Matching samples provide additional context: packer information, YARA rule matches, execution behavior, and associated campaigns from the broader research community.

file hashes + sample metadata
AbuseIPDB

IP Reputation and Abuse Reporting

Network indicators are enriched with AbuseIPDB reputation data including abuse confidence scores, report counts, ISP information, and usage type classification. High-confidence abusive IPs are flagged for immediate attention in hunt workflows.

IP reputation + geo + ASN data
Wild C2 Intelligence

Active C2 Infrastructure Tracking

The Wild C2 module continuously tracks command-and-control servers across Cobalt Strike, Sliver, Havoc, Mythic, and other frameworks. Beacon configurations are extracted and analyzed for watermark clustering and operator fingerprinting — connecting infrastructure to operators across campaigns.

7 C2 frameworks tracked in real-time
capabilities

Key features for threat hunters

Actor Attribution Explorer

214 actor profiles with radial mind-map visualization. Browse by nation-state, severity, or sector. Interactive branch expansion for MITRE, IOCs, tools, and targets.

IOC Search & Enrichment

10,168 indicators searchable by value, type, or associated actor. DNS resolution, ThreatFox cross-reference, and campaign context in every result.

Wild C2 Intelligence

Active C2 server tracking with beacon config extraction, watermark clustering, operator fingerprinting, and cross-campaign infrastructure correlation.

DNS Enrichment

Submit domains and IPs for live DNS resolution, hosting history, associated infrastructure, and connections to known threat actor networks.

Advanced Correlations

10 correlation types across 7 engines: MITRE heatmap, adversary infrastructure, IOC consensus, CVE velocity, attribution networks, detection debt, and enrichment overview.

related solutions

Solutions for your entire security team

// soc_teams

For SOC Teams

Real-time threat feeds, daily debriefs, and IOC context that accelerates alert triage and threat response across every shift.

// detection_engineers

For Detection Engineers

3,553 production-ready rules in SPL, KQL, and Sigma. Browse, filter, copy, and deploy to your SIEM in seconds.

Hunt with intelligence, not intuition

10,168 IOCs, 214 actors, and 10 correlation types — everything you need to build hypotheses that find adversaries.

[ start_hunting ]