Vulnerability Management
Unified intelligence for today’s blended threats
Rocketgraph detects current vulnerabilities and helps you decide which ones to patch first, before they become someone else’s assets.
Vulnerability Management
Unified intelligence for today’s blended threats
Rocketgraph detects current vulnerabilities and helps you decide which ones to patch first, before they become someone else’s assets.
Connected Fraud & Threat Intelligence
Today’s attackers exploit vulnerabilities, then use stolen accounts, devices, and identities to move money, exfiltrate data, or stay hidden inside a network.
The Rocketgraph + Threatworx solution unifies these worlds. Threatworx delivers real-time threat intelligence on vulnerabilities, exploits, and active campaigns. Rocketgraph maps that intelligence across transactions, identities, and behaviors at enterprise scale. Together, they expose the hidden web of fraud, exploits, and adversary tactics that other tools miss.
From patch lists to pattern recognition
By combining Rocketgraph’s graph analytics with Threatworx’s live threat feeds, organizations can move from isolated alerts to connected insights.
Insights include:
- Fraudulent activity mapped to systems running known exploited CVEs
- Shared devices or credentials linked to adversary infrastructure
- End-to-end attack chains spanning fraud, cyber exploits, and insider misuse
Query Speed is King
Other graph solutions can visualize portions of these networks, but they slow to a standstill after the dataset reaches a certain size.
Detect cross-domain attacks before damage multiplies
Legacy fraud detection alone can’t see exploited vulnerabilities. Traditional threat intel feeds can’t map fraud flows across accounts. Together, Rocketgraph + Threatworx close the gap.
Solutions for scale
Rocketgraph scales to billions of transactions and events in real time
Observation around the clock
Threatworx continuously injects live intel on adversaries, CVEs, and exploits
Forensic Cybersecurity
Analysts can pinpoint the bad actor already inside the system and shut it down before losses mount
Eliminate Blind Spots
Rocketgraph + Threatworx delivers:
- Unified fraud + threat detection connecting financial flows, exploits, and adversary tactics.
- Real-time intelligence feeds ensuring your defenses adapt as new vulnerabilities emerge.
- Cross-domain visibility linking fraud events to exploited CVEs and known attacker infrastructure.
- Actionable speed finding hidden risks across billions of data points before damage multiplies.
Bottom line:
Rocketgraph + Threatworx turn fragmented alerts into a single, connected defense, eliminating blind spots between fraud detection and cyber threat intelligence.
FAQ
Rocketgraph lets analysts search the entire enterprise graph for multi-hop attacker patterns (including MITRE ATT&CK-style motifs), not just single events. Our natural-language interface turns plain-English intents into executable graph queries and visual paths, so teams can surface unknown routes, pivot quickly, and map the impact of a zero-day across systems.
Rocketgraph is built on an HPC graph engine (xGT) that keeps data in memory and scans in parallel on a single, scale-up node. The design target is billion-scale nodes/edges with materially lower latency than traditional, scale-out graph databases reducing multi-day graph jobs from days to mere hours. Your results may vary depending on data volume, hardware, and query complexity.
Rocketgraph uses a property-graph model and emphasizes zero-ETL ingestion with a “Mission Control” UI for exploration. That reduces upfront pipeline work and helps you start hunting sooner. Connector coverage and throughput vary by source; ask us to confirm your specific platforms and data rates.
No. A GenAI-assisted workflow lets analysts express hunts and ATT&CK techniques in natural language. Rocketgraph then proposes executable graph queries and iterates with the analyst, providing explanations and visualizations to keep the process transparent.
Rocketgraph lets you search the entire enterprise graph for multi-hop patterns and build “blast-radius” views (e.g., which assets a zero-day could traverse to reach critical systems). Analysts can express hunts in plain English and get executable graph queries plus path visualizations. This shifts triage from “highest CVSS first” to “vulns sitting on exploitable paths to crown jewels,” so you focus on the issues that actually enable lateral movement.
FAQ
Rocketgraph lets analysts search the entire enterprise graph for multi-hop attacker patterns (including MITRE ATT&CK-style motifs), not just single events. Our natural-language interface turns plain-English intents into executable graph queries and visual paths, so teams can surface unknown routes, pivot quickly, and map the impact of a zero-day across systems.
Rocketgraph is built on an HPC graph engine (xGT) that keeps data in memory and scans in parallel on a single, scale-up node. The design target is billion-scale nodes/edges with materially lower latency than traditional, scale-out graph databases reducing multi-day graph jobs from days to mere hours. Your results may vary depending on data volume, hardware, and query complexity.
Rocketgraph uses a property-graph model and emphasizes zero-ETL ingestion with a “Mission Control” UI for exploration. That reduces upfront pipeline work and helps you start hunting sooner. Connector coverage and throughput vary by source; ask us to confirm your specific platforms and data rates.
No. A GenAI-assisted workflow lets analysts express hunts and ATT&CK techniques in natural language. Rocketgraph then proposes executable graph queries and iterates with the analyst, providing explanations and visualizations to keep the process transparent.
Rocketgraph lets you search the entire enterprise graph for multi-hop patterns and build “blast-radius” views (e.g., which assets a zero-day could traverse to reach critical systems). Analysts can express hunts in plain English and get executable graph queries plus path visualizations. This shifts triage from “highest CVSS first” to “vulns sitting on exploitable paths to crown jewels,” so you focus on the issues that actually enable lateral movement.
