Challenge

Data Center Compliance and Security Agent using Google ADK and o3

India's Data Centre Security Bill mandates strict continuous compliance and automated audit logging across cloud workloads. Build an agent using Google ADK integrated with o3 reasoning models to parse security logs and enforce regulatory policies, achieving 95% breach indicator detection accuracy in test simulations.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build an automated cloud infrastructure audit agent using Google Agent Development Kit (ADK) paired with OpenAI o3 model reasoning for complex compliance detection.

Delivery guide

How work is evaluated

Evaluation

Evaluates log audit reasoning, severity scoring, and compliance violation detection accuracy.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

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

critical_threat_detection

Verifies that high-severity database dump anomalies are successfully flagged.

Binary check

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

Dimension 2

detection_accuracy

Accuracy of security anomaly classification. • target: 0.95 • 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

What you should walk away with

  • Build modular agents using Google Agent Development Kit (ADK)

  • Incorporate o3 reasoning model capabilities for complex policy deduction

  • Analyze cloud infrastructure syslog streams and access logs for security anomalies

  • Generate automated compliance failure reports aligned with national data centre standards

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic dataset of 1,000 data center audit logs including simulated breach scenarios.

How this agent runs

Evaluates log audit reasoning, severity scoring, and compliance violation detection accuracy.

Challenge input

JSON array of cloud audit syslog events.

Google ADK

Provides modular agent component abstractions.

o3

Delivers complex logical reasoning across unstructured policy logs.

Evaluated output

JSON containing non_compliant_events count, critical_findings array, and overall_compliance_status.

Checks for
  • Verifies that high-severity database dump anomalies are successfully flagged.
  • Accuracy of security anomaly classification. • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: Cloud Security Policy Reasoning Benchmark
  • Detection Accuracy target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Google ADK · Required
  • Voiceflow · Optional
Policy Serving
  • o3 · Optional

Evaluation contract

  • critical_threat_detection · Weight 1
  • detection_accuracy · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Data Center Compliance and Security Agent using Google ADK and o3