Skip to main content
Loading navigation
Back to challenges

CrewAI ISA/IEC 62443 Security Compliance Verification with Lakera

Industrial power utilities struggle to continuously audit OT infrastructure against ISA/IEC 62443 cybersecurity standards. Develop a multi-agent auditing workflow using CrewAI and Lakera to inspect zone boundaries and prevent prompt-driven parameter tampering. The pipeline must detect 100% of non-compliant network conduits and malicious instruction injections.

EngineeringHosted by Vera
Sign in free to start

What you are building

Deploy a CrewAI multi-agent team integrated with Lakera guardrails to audit Purdue Model zones and secure LLM inputs against injection attacks.

How work is evaluated

Evaluation

Evaluates multi-agent compliance auditing accuracy and prompt injection defense efficacy.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

injection_defense

Verifies that 100% of embedded prompt injection attempts are intercepted by Lakera

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

compliance_audit_accuracy

Accuracy in detecting ISA/IEC 62443 conduit violations • target: 1 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Orchestrate a multi-agent CrewAI system with specialized compliance roles

  • Integrate Lakera Guard to filter malicious prompt injections targeting control parameters

  • Validate network conduits and firewall rules against ISA/IEC 62443 zone specifications

  • Generate automated compliance reports for ISASecure certification submission

Resources

Dataset notes

Utility OT network topography dataset including zone bounds, firewall conduit rules, and adversarial prompt injection benchmarks.

Challenge setup

Evaluates multi-agent compliance auditing accuracy and prompt injection defense efficacy.

Challenge input

JSON with zone_definitions, conduit_rules, and text_queries containing prompt injection attempts

CrewAI

Assigned framework for role-playing multi-agent systems.

Lakera

Assigned tooling for protecting agent systems from prompt injection.

Evaluated output

JSON with non_compliant_conduits (list), prompt_injection_blocked (bool), compliance_score (float)

Evaluation checks
  • Verifies that 100% of embedded prompt injection attempts are intercepted by Lakera
  • Accuracy in detecting ISA/IEC 62443 conduit violations • target: 1 • range: 0-1
Configured evaluation evidence
  • Benchmark: ISA 62443 Compliance Benchmark
  • Compliance Audit Accuracy target: 1
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • CrewAI · Required
  • crewAI · Optional
Safety / Guardrails
  • Lakera · Optional

Evaluation contract

  • injection_defense · Weight 1
  • compliance_audit_accuracy · Weight 1

Metrics

  • compliance_audit_accuracy · Target 1

Benchmarks

  • ISA 62443 Compliance Benchmark
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with zone_definitions, conduit_rules, and text_queries containing prompt injection attempts

    Output: JSON with non_compliant_conduits (list), prompt_injection_blocked (bool), compliance_score (float)

    Execution harness: Python

Evaluation tools

  • CrewAI · Agent Orchestration Framework
  • Lakera · AI Safety / Injection Guard

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about CrewAI ISA/IEC 62443 Security Compliance Verification with Lakera