David Wolf · Project Use Case
AI SECURITY · PRODUCT SECURITY · FORESCOUT
Forescout
Device Cloud Elastic/Kibana Analytics Platform
Large-scale connected-device analytics using Forescout Device Cloud, Elastic, Kibana, and security-research workflows to turn millions of device records...
Built and executed Elastic/Kibana-style analytics workflows over Forescout Device Cloud data to support security research, sector-specific report findings, connected-device risk analysis, rapid response investigations, and...
Client
Forescout
Engagement Type
Full-Time research contribution; exact title and dates should be confirmed from resume/Profile source
Period
2019–2020
Role
Security Research / Device Cloud Analytics / Kibana & Elastic Analyst Contributor
Focus Areas
Device Cloud Analytics, Elastic/Kibana Workflows, Connected Device Intelligence, Large-Scale Security Research
The Research Narrative
Strategic Problem
The research problem was not simply collecting data. It was extracting defensible security signal from millions of records: which devices existed, where they lived, what they ran, what they exposed, what they...
What David Did
David used Elastic/Kibana-style workflows to support Device Cloud research across healthcare, financial services, OT, IoT, connected medical devices, and rapid-response analyses. The work...
What Became Clearer
The result was an evidence-generation capability behind multiple Forescout research narratives. The same pattern now underpins David's AI-security work: telemetry, normalization, analysis,...
Consulting Proof
This is evidence of turning messy security telemetry into explainable dashboards, alert-quality improvements, and executive-ready operating views.
The Context
Forescout Device Cloud gave researchers a rare view into real connected-device environments. The data spanned sectors, networks, device types, operating systems, protocols, services, and unmanaged assets that ordinary endpoint tools often missed.
The Challenge
The research problem was not simply collecting data. It was extracting defensible security signal from millions of records: which devices existed, where they lived, what they ran, what they exposed, what they were near, and what risk that created.
What I Did
David used Elastic/Kibana-style workflows to support Device Cloud research across healthcare, financial services, OT, IoT, connected medical devices, and rapid-response analyses. The work connected query logic, device classification, sector context, and risk interpretation.
- •Used Forescout Device Cloud as the source dataset for connected-device security research and rapid-response analysis
- •Built Elastic/Kibana-style query and dashboard workflows to explore device populations, sector slices, protocol exposure, services, operating systems, and network relationships
- •Segmented analysis by verticals such as healthcare, financial services, manufacturing, retail, government, operational technology, and medical-device environments
- •Analyzed device fingerprints, classifications, vendors, models, observed functions, operating systems, and network context to identify risk patterns
- •Supported VLAN and network-neighborhood analysis to understand segmentation gaps, POS adjacency, printer and IoT proximity, and lateral-movement paths
- •Helped interpret legacy Windows exposure, unsupported operating systems, RDP exposure, BlueKeep patching needs, and TCP/IP vulnerability relevance
- •Supported analysis around connected medical devices, IoMT systems, unmanaged assets, OT devices, UPS appliances, PLCs, cameras, printers, and collaboration hardware
- •Translated query results into findings that could support public reports, blogs, threat briefings, sales enablement, and customer-risk conversations
The Outcome
The result was an evidence-generation capability behind multiple Forescout research narratives. The same pattern now underpins David's AI-security work: telemetry, normalization, analysis, control evidence, and clear executive communication.
Research Outcomes
Signal Quality
Improved the trustworthiness of operational security signals
Operational Clarity
Translated complex security data into clearer operating views
Executive Visibility
Built dashboards leaders could trust for decision-making
Operational Impact
Turned raw telemetry into actionable security intelligence
Capabilities Demonstrated
Security Analytics
Signal investigation and event analysis
Dashboard Development
Operational and executive views
Executive Reporting
Security data translated for leadership
Operational Reporting
Actionable views for security operations
Public-Safe Evidence
Shareable insights without sensitive data
IAM / Access Control
Identity telemetry and access insights
SIEM Alert Debugging
Noise reduction and signal validation
Telemetry Normalization
Consistent and trusted data
Key Deliverables
- •Device Cloud analytics workflows
- •Elastic/Kibana-style research queries and investigative views
- •Sector-specific connected-device analysis support
- •Healthcare and connected medical-device analytics support
- •Financial-services VLAN and device-neighborhood analysis support
- •Operational technology and Enterprise-of-Things analytics support
- •Rapid-response exposure analysis support
- •Legacy operating-system and service-exposure analysis support
Tools & Technologies
Consulting Translation
The reusable pattern is not Disney-specific: normalize fragmented security telemetry, debug low-signal alert behavior, build trusted operating views, and give leadership evidence they can act on without exposing sensitive systems.