Ten detailed agent workflows for proactive threat hunting, malware infrastructure mapping, C2 domain detection, threat actor attribution, dark web monitoring, exploit kit tracking, APT campaign analysis, vulnerability exploitation detection, threat feed enrichment, and predictive threat modeling — powered by domain intelligence for preemptive network defense.
AI agent maps the complete infrastructure of active malware campaigns — C2 servers, download stages, exfiltration endpoints, and backup domains — using domain intelligence correlation.
AI agent detects and predicts DGA domains by analyzing entropy patterns, registration timing, and domain intelligence signals to block botnet C2 channels before activation.
AI agent attributes advanced persistent threat campaigns to threat actor groups by analyzing infrastructure patterns, domain registration tradecraft, and operational security indicators through domain intelligence.
AI agent tracks exploit kit infrastructure — landing pages, payload servers, and traffic distribution systems — using domain intelligence to block exploitation chains before they reach subscribers.
AI agent fingerprints phishing kit deployments across domains, tracking the same kit redeployed on multiple domains to identify campaign operators and predict next deployments.
AI agent enriches external threat feeds with domain intelligence, validating IOCs, removing false positives, and adding context to raw threat indicators.
AI agent detects browser-based and network-level cryptojacking by identifying mining pool domains, WebAssembly mining scripts, and abnormal resource consumption patterns.
AI agent correlates dark web activity with surface web domain intelligence — matching leaked credential databases, stolen data offerings, and threat actor communications with ISP subscriber domains.
AI agent detects active exploitation of known vulnerabilities by monitoring for domains hosting exploit payloads, scanning tools, and vulnerability disclosure sites that indicate imminent attacks.
AI agent builds predictive threat models using domain intelligence time-series data — forecasting emerging threats, predicting campaign timelines, and identifying pre-attack infrastructure staging.
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