Security Review for Plant and Enterprise AI Copilots

• CISO or Head of IT Security
• CIO or Head of Digital
• OT Security Lead
• AI Programme Manager

Manufacturers are connecting LLM copilots to SAP, maintenance systems, drawing vaults and shared drives so engineers and managers can ask questions in plain language. Each connection widens what a cleverly worded prompt, or a poisoned document, can reach.

We run a structured security review of your copilot before roll-out or after a major change. We map its data sources, user roles, tools and network paths, including any route towards OT systems, and build a threat model with your IT and OT owners. We then run automated adversarial test suites and manual testing for prompt injection, indirect injection through documents, data leakage across roles, plants and customers, excessive tool permissions and unsafe outputs. Every finding is validated by an engineer, given a severity and reproduction steps, and mapped to the OWASP Top 10 for LLM Applications. We retest after your fixes.

• Threat model covering data sources, roles, tools and any path towards OT networks
• Direct and indirect prompt injection tests, including poisoned PDFs, emails and drawing notes
• Cross-role, cross-plant and cross-customer data leakage tests on retrieval and memory
• Tool and permission review for actions in SAP, CMMS, MES or ticketing systems
• Findings with severity, evidence and reproduction steps, mapped to OWASP LLM Top 10 and MITRE ATLAS
• Retest after fixes and a regression test pack for future releases

1. 01Agree scope and rulesWe agree the copilot, environments, test accounts, time windows and what is out of bounds, especially OT.
2. 02Map and threat-modelData sources, roles, tools and network paths are mapped, and threats are ranked with your owners.
3. 03Run adversarial testsAutomated suites and manual testers probe injection, leakage, tool misuse and unsafe outputs.
4. 04Validate findingsAn engineer reproduces each candidate issue; anything unconfirmed is dropped or marked as an observation.
5. 05Report and remediateYou receive validated findings with evidence and fixes, and walk through them with our team.
6. 06RetestAfter your fixes, we retest each finding and hand over a regression test pack.

1. Scoping
   • Asset and data-source inventory
   • Role and permission matrix
   • Rules of engagement with OT exclusions
2. Test generation
   • Adversarial prompt library for injection and jailbreaks
   • Poisoned document set for indirect injection
   • Role-based leakage test cases
3. Execution
   • Automated test runner against the copilot API or UI
   • Manual expert testing
   • Tool-call and log capture
4. Validation and reporting
   • Engineer validation and severity rating
   • Evidence pack mapped to OWASP LLM Top 10
   • Remediation guidance
5. Regression
   • Retest of fixed findings
   • Regression suite for future releases

Our security engineers validate every automated finding before it reaches the report, and your IT, OT and data owners approve the scope and decide how to treat each risk. No test touches live OT control systems.

• Copilot platforms such as Azure OpenAI, Microsoft Copilot Studio or custom LLM apps
• SAP, CMMS and MES APIs used as copilot tools
• SharePoint, network drives or PLM vaults used for retrieval
• Issue trackers such as Jira for findings
• CI pipelines for regression tests

• Testing only within agreed scope, accounts and time windows
• No write actions against production ERP, MES or OT systems
• Synthetic test data used in place of real customer drawings or personal data where possible
• Findings and evidence stored encrypted with restricted access

• Findings are mapped to the OWASP Top 10 for LLM Applications and can feed risk records aligned with the NIST AI RMF and ISO/IEC 42001.
• For copilots near industrial control systems, scoping respects your IEC 62443 zones and conduits.

• Manufacturing

  Maintenance Log and SOP Assistant

  A shop-floor assistant that answers technicians' questions from breakdown history, OEM manuals and SOPs, in Hindi or English, with the source page or work order behind every answer.

• Energy, Mining & Utilities

  Security Review for OT/IT AI Assistants

  Adversarial testing and architecture review for AI assistants that read historian data, manuals and work orders, covering prompt injection, unsafe advice, data leakage and tool permissions.

• SaaS & AI Product Companies

  RAG Data-Leakage and Access-Control Testing

  Test whether your RAG pipeline leaks documents across users, roles or tenants through retrieval, caching, citations or logs, using seeded canary documents and role-based test personas.

• Fintech & Payments

  AI Agent Permission and Tool-Use Security Review

  Find out what your AI agents can actually do: which tools, credentials and money-moving actions they reach, where approvals sit, and whether injected text can make them misuse tools.