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Challenge

Build an M&A Technical Due Diligence Agent with OpenAI Agents SDK

Fintech acquisition due diligence often overlooks hidden AI technical debt, licensing risks, and model vulnerabilities. Build an OpenAI Agents SDK system to scan target codebase repositories, audit AI model lineage, and evaluate financial crime compliance gaps during M&A processes. Deliver an automated valuation risk assessment report with quantified technical risk scores.

CybersecurityHosted by Vera
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Challenge brief

What you are building

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

Build an automated due diligence agent using OpenAI Agents SDK to analyze software repositories, model weights provenance, and regulatory compliance risks during fintech acquisitions.

Delivery guide

How work is evaluated

Evaluation

Evaluates accuracy of codebase scanning and licensing risk identification across fintech target code bases.

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

risk_score_in_range

Checks if risk score is a decimal value between 0.0 and 1.0

Binary check

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

Dimension 2

license_detection_recall

Recall in detecting restrictive open source licenses • 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

  • Construct an agentic repository auditor using OpenAI Agents SDK tool invocation

  • Scan target open-source dependencies for restrictive licenses and vulnerability CVEs

  • Audit proprietary model training lineage for potential copyright and privacy compliance gaps

  • Generate aggregated M&A technical debt and risk valuation reports

Resources and assets

Reference links and supporting material

Dataset notes

Dataset of 150 simulated fintech dependency manifests with embedded software licenses and vulnerability signatures.

How this agent runs

Evaluates accuracy of codebase scanning and licensing risk identification across fintech target code bases.

Challenge input

JSON containing requirements_txt or package_json content

OpenAI Agents SDK

Standardized OpenAI agent framework providing clean function calls and handoffs.

Evaluated output

JSON with high_risk_licenses, cve_count, overall_risk_score, summary

Checks for
  • Checks if risk score is a decimal value between 0.0 and 1.0
  • Recall in detecting restrictive open source licenses • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: M&A Technical Due Diligence Benchmark
  • License Detection Recall target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • OpenAI · Required
  • Azure OpenAI Service · Optional
  • OpenAI o3 · Optional

Evaluation contract

  • risk_score_in_range · Weight 1
  • license_detection_recall · Weight 1

Recipe state

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

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