How to Automate OT Threat Detection with AI
Operational Technology (OT) environments are no longer isolated islands. Remote engineering, IIoT telemetry and cloud analytics have blurred old boundaries - and attackers are adapting faster than ever. This Shieldworkz playbook, How to Automate OT Threat Detection with AI, is a practical, safety-first guide for CISOs, OT leads and operations managers who need AI that helps protect availability, safety and profits - not produce noise or accidental outages. Read on how Shieldworkz helps you move from passive visibility to careful, governed automation.
Why this guide matters
Modern attacks against industrial environments rarely look like classic malware. They “live off the land,” misuse legitimate engineering tools, or subtly alter process setpoints so damage is only visible after the fact. Legacy signature-based IDS and rule-only SOC playbooks miss these patterns.
AI offers three operational advantages that matter for OT:
Sequence recognition - detect when an engineering command sequence is anomalous for the current process state.
High-dimensional correlation - combine network activity, engineering workstation logs and process telemetry into high-confidence alerts.
Noise reduction - reduce false positives by learning what normal truly means for your plant modes (startup, production, maintenance).
But AI must be designed for OT - passive-by-default, context-aware, and governed by operations and safety stakeholders. When applied correctly, it shortens detection lead time, reduces unplanned downtime, and prevents safety incidents.
What’s in the E-Book - practical, field-tested guidance
This guide distills Shieldworkz experience into an actionable roadmap you can apply now. You’ll get:
A safety-first architecture (passive taps, analytics sandbox, air-lock automation gates).
The 5-phase implementation roadmap (Visibility → Baseline → Pilot → Human-in-the-loop → Managed Automation).
Telemetry requirements: which feeds matter, how to collect them non-intrusively, and how to label data for AI training.
AI techniques mapped to OT use cases (unsupervised novelty detection, time-series LSTM models, graph analytics for lateral movement).
Governance templates: establish a Safety Board, approve automation playbooks, and define human veto controls.
OT-SOAR design: examples of safe automations (session termination, VLAN reassignments, PLC snapshot) - and a clear list of forbidden automations.
KPIs that matter to executives (detection lead time, false positive ratio, risk reduction score, cost avoidance).
Common failure modes and mitigations (model drift, alert fatigue, black-box skepticism) and how to operationalize explainable AI.
Why download this guide - immediate, measurable benefit
This is not an academic paper. It’s a field manual for teams with production constraints:
Avoid risky mistakes: learn the passive-first patterns that protect fragile PLCs and SIS devices.
Reduce noise: adopt baselining methods that shrink false positives so your OT team trusts the alerts.
Govern automation safely: templates and checklists to get cross-functional approval without paralysis.
Deploy faster: a ready-to-use 180-day plan with milestones you can implement alongside operations.
Vendor- and platform-agnostic: techniques and controls that integrate with existing switches, historians and SIEMs.
Download it if you need a pragmatic path to AI-driven detection that won’t interrupt production.
Key takeaways you’ll walk away with
Shieldworkz helps teams move from theory to working capability with minimal disruption:
Passive-first is mandatory: mirror traffic and collect telemetry; the AI must see but never touch control systems in early phases.
Context beats volume: the most effective detections combine network, process and engineering context.
Human-in-the-loop is safety-critical: every automation playbook must be pre-approved by a cross-discipline Safety Board.
Measure what executives care about: translate technical gains into business KPIs - hours of downtime avoided, MTTD improvement, and inventory of protected critical assets.
Plan for drift and maintenance windows: use maintenance-mode toggles and quarterly baseline refreshes to avoid alert storms.
Explainability wins trust: XAI tools that show why the model alerted accelerate operator buy-in.
How Shieldworkz supports you - services that deliver outcomes
Shieldworkz blends OT domain expertise, AI engineering and operational delivery. Typical engagements include:
7-Day Passive Discovery Assessment: deploy a non-intrusive sensor on your primary switch to produce a Behavioural Gap Report within one week - asset map, telemetry gaps, and initial anomaly examples.
90-180 day Implementation Program: end-to-end delivery across the five phases - asset hygiene, behavioral baselining, pilot detection, human-in-loop orchestration and managed automation.
AI Model Design & Ops: OT-tuned models (sequence, graph, autoencoder) plus continuous model maintenance to handle drift and new process modes.
Governance & Playbook Design: assemble your Operational Safety Board, draft automation playbooks, and implement manual-override and audit trails.
OT-SOAR Integration: safe automation recipes that integrate with your ticketing, jump hosts and network enforcement points - always with operator approval gating.
Managed Detection & Response: 24/7 OT-aware monitoring with on-call analysts who understand process impact and can coordinate safe responses.
Deliverables include an executive KPI dashboard, behavioural baselines for crown-jewel assets, approved automation playbooks, and a prioritized remediation roadmap.
Next steps - Download the guide and start with a low-risk assessment
Automating OT detection with AI is a journey - but you don’t have to navigate it alone. Download the Shieldworkz playbook and request a 7-Day Passive Discovery Assessment. We’ll deliver a behavioural gap report that shows immediate priorities and a realistic 90-day plan you can implement with operations-grade safety.
Fill the form to download the guide and book your complimentary scoping call with a Shieldworkz OT specialist. Protect availability. Reduce risk. Let AI do the heavy lifting - safely.
Download your copy today!
Get our free How to Automate OT Threat Detection with AI and make sure you’re covering every critical control in your industrial network
Operational Technology (OT) environments are no longer isolated islands. Remote engineering, IIoT telemetry and cloud analytics have blurred old boundaries - and attackers are adapting faster than ever. This Shieldworkz playbook, How to Automate OT Threat Detection with AI, is a practical, safety-first guide for CISOs, OT leads and operations managers who need AI that helps protect availability, safety and profits - not produce noise or accidental outages. Read on how Shieldworkz helps you move from passive visibility to careful, governed automation.
Why this guide matters
Modern attacks against industrial environments rarely look like classic malware. They “live off the land,” misuse legitimate engineering tools, or subtly alter process setpoints so damage is only visible after the fact. Legacy signature-based IDS and rule-only SOC playbooks miss these patterns.
AI offers three operational advantages that matter for OT:
Sequence recognition - detect when an engineering command sequence is anomalous for the current process state.
High-dimensional correlation - combine network activity, engineering workstation logs and process telemetry into high-confidence alerts.
Noise reduction - reduce false positives by learning what normal truly means for your plant modes (startup, production, maintenance).
But AI must be designed for OT - passive-by-default, context-aware, and governed by operations and safety stakeholders. When applied correctly, it shortens detection lead time, reduces unplanned downtime, and prevents safety incidents.
What’s in the E-Book - practical, field-tested guidance
This guide distills Shieldworkz experience into an actionable roadmap you can apply now. You’ll get:
A safety-first architecture (passive taps, analytics sandbox, air-lock automation gates).
The 5-phase implementation roadmap (Visibility → Baseline → Pilot → Human-in-the-loop → Managed Automation).
Telemetry requirements: which feeds matter, how to collect them non-intrusively, and how to label data for AI training.
AI techniques mapped to OT use cases (unsupervised novelty detection, time-series LSTM models, graph analytics for lateral movement).
Governance templates: establish a Safety Board, approve automation playbooks, and define human veto controls.
OT-SOAR design: examples of safe automations (session termination, VLAN reassignments, PLC snapshot) - and a clear list of forbidden automations.
KPIs that matter to executives (detection lead time, false positive ratio, risk reduction score, cost avoidance).
Common failure modes and mitigations (model drift, alert fatigue, black-box skepticism) and how to operationalize explainable AI.
Why download this guide - immediate, measurable benefit
This is not an academic paper. It’s a field manual for teams with production constraints:
Avoid risky mistakes: learn the passive-first patterns that protect fragile PLCs and SIS devices.
Reduce noise: adopt baselining methods that shrink false positives so your OT team trusts the alerts.
Govern automation safely: templates and checklists to get cross-functional approval without paralysis.
Deploy faster: a ready-to-use 180-day plan with milestones you can implement alongside operations.
Vendor- and platform-agnostic: techniques and controls that integrate with existing switches, historians and SIEMs.
Download it if you need a pragmatic path to AI-driven detection that won’t interrupt production.
Key takeaways you’ll walk away with
Shieldworkz helps teams move from theory to working capability with minimal disruption:
Passive-first is mandatory: mirror traffic and collect telemetry; the AI must see but never touch control systems in early phases.
Context beats volume: the most effective detections combine network, process and engineering context.
Human-in-the-loop is safety-critical: every automation playbook must be pre-approved by a cross-discipline Safety Board.
Measure what executives care about: translate technical gains into business KPIs - hours of downtime avoided, MTTD improvement, and inventory of protected critical assets.
Plan for drift and maintenance windows: use maintenance-mode toggles and quarterly baseline refreshes to avoid alert storms.
Explainability wins trust: XAI tools that show why the model alerted accelerate operator buy-in.
How Shieldworkz supports you - services that deliver outcomes
Shieldworkz blends OT domain expertise, AI engineering and operational delivery. Typical engagements include:
7-Day Passive Discovery Assessment: deploy a non-intrusive sensor on your primary switch to produce a Behavioural Gap Report within one week - asset map, telemetry gaps, and initial anomaly examples.
90-180 day Implementation Program: end-to-end delivery across the five phases - asset hygiene, behavioral baselining, pilot detection, human-in-loop orchestration and managed automation.
AI Model Design & Ops: OT-tuned models (sequence, graph, autoencoder) plus continuous model maintenance to handle drift and new process modes.
Governance & Playbook Design: assemble your Operational Safety Board, draft automation playbooks, and implement manual-override and audit trails.
OT-SOAR Integration: safe automation recipes that integrate with your ticketing, jump hosts and network enforcement points - always with operator approval gating.
Managed Detection & Response: 24/7 OT-aware monitoring with on-call analysts who understand process impact and can coordinate safe responses.
Deliverables include an executive KPI dashboard, behavioural baselines for crown-jewel assets, approved automation playbooks, and a prioritized remediation roadmap.
Next steps - Download the guide and start with a low-risk assessment
Automating OT detection with AI is a journey - but you don’t have to navigate it alone. Download the Shieldworkz playbook and request a 7-Day Passive Discovery Assessment. We’ll deliver a behavioural gap report that shows immediate priorities and a realistic 90-day plan you can implement with operations-grade safety.
Fill the form to download the guide and book your complimentary scoping call with a Shieldworkz OT specialist. Protect availability. Reduce risk. Let AI do the heavy lifting - safely.
Download your copy today!
Get our free How to Automate OT Threat Detection with AI and make sure you’re covering every critical control in your industrial network
Operational Technology (OT) environments are no longer isolated islands. Remote engineering, IIoT telemetry and cloud analytics have blurred old boundaries - and attackers are adapting faster than ever. This Shieldworkz playbook, How to Automate OT Threat Detection with AI, is a practical, safety-first guide for CISOs, OT leads and operations managers who need AI that helps protect availability, safety and profits - not produce noise or accidental outages. Read on how Shieldworkz helps you move from passive visibility to careful, governed automation.
Why this guide matters
Modern attacks against industrial environments rarely look like classic malware. They “live off the land,” misuse legitimate engineering tools, or subtly alter process setpoints so damage is only visible after the fact. Legacy signature-based IDS and rule-only SOC playbooks miss these patterns.
AI offers three operational advantages that matter for OT:
Sequence recognition - detect when an engineering command sequence is anomalous for the current process state.
High-dimensional correlation - combine network activity, engineering workstation logs and process telemetry into high-confidence alerts.
Noise reduction - reduce false positives by learning what normal truly means for your plant modes (startup, production, maintenance).
But AI must be designed for OT - passive-by-default, context-aware, and governed by operations and safety stakeholders. When applied correctly, it shortens detection lead time, reduces unplanned downtime, and prevents safety incidents.
What’s in the E-Book - practical, field-tested guidance
This guide distills Shieldworkz experience into an actionable roadmap you can apply now. You’ll get:
A safety-first architecture (passive taps, analytics sandbox, air-lock automation gates).
The 5-phase implementation roadmap (Visibility → Baseline → Pilot → Human-in-the-loop → Managed Automation).
Telemetry requirements: which feeds matter, how to collect them non-intrusively, and how to label data for AI training.
AI techniques mapped to OT use cases (unsupervised novelty detection, time-series LSTM models, graph analytics for lateral movement).
Governance templates: establish a Safety Board, approve automation playbooks, and define human veto controls.
OT-SOAR design: examples of safe automations (session termination, VLAN reassignments, PLC snapshot) - and a clear list of forbidden automations.
KPIs that matter to executives (detection lead time, false positive ratio, risk reduction score, cost avoidance).
Common failure modes and mitigations (model drift, alert fatigue, black-box skepticism) and how to operationalize explainable AI.
Why download this guide - immediate, measurable benefit
This is not an academic paper. It’s a field manual for teams with production constraints:
Avoid risky mistakes: learn the passive-first patterns that protect fragile PLCs and SIS devices.
Reduce noise: adopt baselining methods that shrink false positives so your OT team trusts the alerts.
Govern automation safely: templates and checklists to get cross-functional approval without paralysis.
Deploy faster: a ready-to-use 180-day plan with milestones you can implement alongside operations.
Vendor- and platform-agnostic: techniques and controls that integrate with existing switches, historians and SIEMs.
Download it if you need a pragmatic path to AI-driven detection that won’t interrupt production.
Key takeaways you’ll walk away with
Shieldworkz helps teams move from theory to working capability with minimal disruption:
Passive-first is mandatory: mirror traffic and collect telemetry; the AI must see but never touch control systems in early phases.
Context beats volume: the most effective detections combine network, process and engineering context.
Human-in-the-loop is safety-critical: every automation playbook must be pre-approved by a cross-discipline Safety Board.
Measure what executives care about: translate technical gains into business KPIs - hours of downtime avoided, MTTD improvement, and inventory of protected critical assets.
Plan for drift and maintenance windows: use maintenance-mode toggles and quarterly baseline refreshes to avoid alert storms.
Explainability wins trust: XAI tools that show why the model alerted accelerate operator buy-in.
How Shieldworkz supports you - services that deliver outcomes
Shieldworkz blends OT domain expertise, AI engineering and operational delivery. Typical engagements include:
7-Day Passive Discovery Assessment: deploy a non-intrusive sensor on your primary switch to produce a Behavioural Gap Report within one week - asset map, telemetry gaps, and initial anomaly examples.
90-180 day Implementation Program: end-to-end delivery across the five phases - asset hygiene, behavioral baselining, pilot detection, human-in-loop orchestration and managed automation.
AI Model Design & Ops: OT-tuned models (sequence, graph, autoencoder) plus continuous model maintenance to handle drift and new process modes.
Governance & Playbook Design: assemble your Operational Safety Board, draft automation playbooks, and implement manual-override and audit trails.
OT-SOAR Integration: safe automation recipes that integrate with your ticketing, jump hosts and network enforcement points - always with operator approval gating.
Managed Detection & Response: 24/7 OT-aware monitoring with on-call analysts who understand process impact and can coordinate safe responses.
Deliverables include an executive KPI dashboard, behavioural baselines for crown-jewel assets, approved automation playbooks, and a prioritized remediation roadmap.
Next steps - Download the guide and start with a low-risk assessment
Automating OT detection with AI is a journey - but you don’t have to navigate it alone. Download the Shieldworkz playbook and request a 7-Day Passive Discovery Assessment. We’ll deliver a behavioural gap report that shows immediate priorities and a realistic 90-day plan you can implement with operations-grade safety.
Fill the form to download the guide and book your complimentary scoping call with a Shieldworkz OT specialist. Protect availability. Reduce risk. Let AI do the heavy lifting - safely.
Download your copy today!
