Indicators that arrive from breach investigations, external attack-surface monitoring and credential exposure work, matched against the malware, infrastructure and IOC data already in the platform -- plus the feeds and OSINT sources that data is built from.
Indicators from breach investigations, external attack-surface monitoring, dark web threat intelligence, credential exposure investigations, and other security intelligence sources are regularly sent to security teams.
By comparing supported indications found through those workflows with available malware, infrastructure, IOC, and threat intelligence data, ThreatFusionAI can assist analysts in their investigation.
This means an indicator discovered through a dark-web investigation can become a starting point for broader technical analysis rather than remaining an isolated finding.
The subscriber corpus behind the phone and email lookups is dark web sourced data held on the platform; broader dark-web monitoring beyond that corpus is delivered as an analyst-led engagement rather than as a standing feed.
Exposure lookups are self-serve; investigations are not. The phone and email lookups search the dark web subscriber corpus directly. Every plan can confirm whether an identifier appears and see a masked result; full unmasked records require an Enterprise plan. Analyst-led dark web investigation scoped to your organisation remains a separate engagement.
ThreatFusionAI combines multiple forms of security intelligence rather than relying on a single feed. Information can include:
Public threat intelligence sources, folded into the wider investigation workflow rather than presented as a standalone list.
Malware and file reputation intelligence drawn from multiple detection engines.
Observed malware behaviour and the indicators extracted from detonation.
The public catalogue of attacker tactics and techniques, used as the common vocabulary across investigations.
Our own analysis at Craw Security, across the samples already processed by the platform.
The relationship map we build ourselves by extracting indicators from every sample and linking them back to the corpus.
For teams comparing the best threat intelligence feeds, the important question is not simply how many indicators a feed contains. The more useful question is: Can those indicators be connected with malware, behavior, infrastructure, and attacker activity? That correlation is where ThreatFusionAI focuses.
OSINT remains an important part of modern cybersecurity investigations. ThreatFusionAI incorporates open-source intelligence into a broader investigation workflow, making it useful for teams looking for an open source threat intelligence platform approach combined with malware analysis, IOC correlation, and ATT&CK mapping.