David Wolf · Portfolio Use Case
Device Cloud research identifying the riskiest IoT devices across financial services, government, healthcare, manufacturing, and retail.
Contributed to Forescout's Enterprise of Things Security Report research, using Device Cloud analytics and Elastic/Kibana-style workflows to help identify and frame the riskiest IoT and connected devices across major enterprise verticals. Contributed to Enterprise of Things research and report work at Forescout, helping frame the security implications of unmanaged, IoT, OT, and connected devices as enterprise attack surfaces requiring visibility, classification, segmentation, monitoring, policy, and response.
Client
Forescout
Engagement Type
Full-Time research contribution; exact title and dates should be confirmed from resume/Profile source
Period
2020
Role
Security Research / Device Cloud Analytics / Kibana & Elastic Analyst Contributor
Focus Areas
Enterprise of Things, IoT Security, Forescout Device Cloud
The Context
The Enterprise of Things was Forescout's way of naming the reality that every organization had become a connected-device environment. IT devices, IoT devices, unmanaged assets, and sector-specific systems all created risk beyond traditional endpoint security.
The Challenge
The research challenge was to rank and explain risk across device types and sectors in a way security leaders could use. The report had to turn connected-device telemetry into a practical story about exposure, prioritization, and next steps.
What I Did
The Outcome
The report helped make enterprise IoT risk more concrete: security teams needed visibility, classification, segmentation, monitoring, and policy enforcement across every connected thing. That same evidence-first logic carries into David's later AI-security work.
To
Enterprise of Things report work at Forescout
On
Unmanaged, IoT, OT, and connected-device security risk across enterprise environments
Frame
Visibility, classification, segmentation, monitoring, and policy as security controls for diverse device estates
Key Deliverables
Collaboration
Worked in a Forescout research and device-intelligence context where large-scale Device Cloud analysis needed to become credible IoT-security insight for practitioners, executives, customers, sales teams, analysts, and market education. Worked in a research and product-security context where technical device-security issues needed to become a clear market narrative for customers, executives, practitioners, and security buyers.
Client
Forescout
Engagement Type
Full-Time research contribution; exact title and dates should be confirmed from resume/Profile source
Period
2020
Role
Security Research / Device Cloud Analytics / Kibana & Elastic Analyst Contributor
Focus Areas
Enterprise of Things, IoT Security, Forescout Device Cloud
The Context
The Enterprise of Things was Forescout's way of naming the reality that every organization had become a connected-device environment. IT devices, IoT devices, unmanaged assets, and sector-specific systems all created risk beyond traditional endpoint security.
The Challenge
The research challenge was to rank and explain risk across device types and sectors in a way security leaders could use. The report had to turn connected-device telemetry into a practical story about exposure, prioritization, and next steps.
What I Did
The Outcome
The report helped make enterprise IoT risk more concrete: security teams needed visibility, classification, segmentation, monitoring, and policy enforcement across every connected thing. That same evidence-first logic carries into David's later AI-security work.
To
Enterprise of Things report work at Forescout
On
Unmanaged, IoT, OT, and connected-device security risk across enterprise environments
Frame
Visibility, classification, segmentation, monitoring, and policy as security controls for diverse device estates
Key Deliverables
Collaboration
Worked in a Forescout research and device-intelligence context where large-scale Device Cloud analysis needed to become credible IoT-security insight for practitioners, executives, customers, sales teams, analysts, and market education. Worked in a research and product-security context where technical device-security issues needed to become a clear market narrative for customers, executives, practitioners, and security buyers.
At a Glance
Focus Areas
Tools & Technologies
Evidence & Artifacts
Public-Safe Caveat
This case study uses public Forescout sources for report-level facts and user-provided context for the author's Device Cloud and Elastic/Kibana contribution. Exact authorship, internal queries, dashboards, customer details, raw datasets, proprietary scoring logic, unpublished drafts, and non-public analysis details are omitted unless later confirmed and approved for public use. This case study describes Enterprise of Things report contribution in public-safe terms. Exact authorship details, internal drafts, private datasets, proprietary research methods, customer examples, and unpublished findings are omitted unless later confirmed and approved for public use.
David Wolf
AI Security · Product Security · Security Leadership
Based on analyzed public signals, not proof of any individual's or company's internal state.
