Every CTI tool tells you what threats exist. Black Swarm tells you who they matter to. When a zero-day drops, the system instantly maps relevance across all monitored organizations — by industry, tech stack, geography, and exposure surface. The question shifts from “is this threat important?” to “who should I care about right now?”
For each organization monitored, Black Swarm maintains a continuously evolving digital twin — a persistent model of their technology stack, business exposure, regulatory posture, and threat surface. Auto-discovered from Shodan, DNS, certificates, and enriched over time. No competitor does this today.
Every AI-generated claim links to traceable evidence, standardized MITRE ATT&CK tags, and confidence scores. The system proposes; the analyst decides. Hallucination is treated as an engineering problem, not a marketing footnote — with RAG grounding targeting <2% unsubstantiated claims.
Black Swarm operates a continuous 6-layer pipeline. Sources are discovered, validated, and collected from across the open web, social platforms, and dark web. Raw evidence is sanitized, enriched by hybrid LLM inference, synthesized into analyst-ready intelligence, and presented through three distinct axes.
Black Swarm reshapes the analyst's workflow from reactive alert triage to proactive, evidence-backed investigation.
Open the dashboard to the Global Intelligence View. The overnight intelligence feed shows synthesized threat cards — each grounded in evidence from OSINT, social, and dark web sources. The weekly threat briefing summarizes the landscape. Threat Pulse KPIs surface severity distribution at a glance.
A critical zero-day drops. Black Swarm auto-maps it against every customer digital twin in real time. The Customer Intelligence view lights up: “3 of your 47 customers are exposed.” Click to see which ones, why, and what their specific exposure vectors are — tech stack, geography, and attack surface overlap.
Drill into the most-affected customer. Pivot through the Neo4j relationship graph — actors, campaigns, infrastructure linkage. Build a hypothesis in the investigation workspace. Query evidence via natural language. Generate an evidence-grounded report with MITRE ATT&CK mapping and export as STIX 2.1.
Black Swarm runs on purpose-built infrastructure with dedicated trust zones, persistent storage, and multi-model LLM inference. Every component is designed for persistence, auditability, and controlled autonomy.
Stateful agent orchestration with persistent checkpointing. Investigations survive restarts, shift changes, and infrastructure events.
The right model for the right task — from Qwen2.5-14B for high-volume triage, through Llama 3.1 70B for synthesis, to Claude Opus 4.7 for deep reasoning. Continuous quality monitoring across all models.
Relationship graph of actors, campaigns, TTPs, and infrastructure. Cypher-powered pivot and hunt across entity relationships.
High-dimensional embeddings for evidence similarity. Powers semantic clustering, deduplication, and RAG retrieval at synthesis time.
Multi-pass content sanitization on all raw evidence. Pattern-based and semantic filtering with escalated scrutiny for hostile-zone content.
Full LLM trace logging, cost tracking, and quality metrics. Grafana dashboards and Prometheus alerting for platform health.
Temporal knowledge graph for tracking how threat actor relationships and campaign patterns evolve over time.