Build a Crypto-Agile PQC Migration Agent with OpenAI Agents SDK
With the rise of quantum computing threats, organizations must transition from classical RSA/ECC to NIST-standardized Post-Quantum Cryptography (PQC). This challenge involves building an autonomous migration agent using the OpenAI Agents SDK and Gemini 2.5 Flash to identify vulnerable cryptographic implementations in legacy codebases and refactor them into a crypto-agile architecture. You will implement a 'Wrapper-First' approach, allowing applications to switch between ML-KEM (Kyber) and classical algorithms without redeploying the entire service. The agent must perform static analysis to detect hardcoded primitives, suggest library replacements using `liboqs`, and generate unit tests that verify both security and performance. The system will leverage OpenAI's tool-calling capabilities to interface with Git repositories and static analysis tools, ensuring that the migration preserves the application's functional integrity while mitigating 'Harvest Now, Decrypt Later' risks.
What you are building
The core problem, expected build, and operating context for this challenge.
With the rise of quantum computing threats, organizations must transition from classical RSA/ECC to NIST-standardized Post-Quantum Cryptography (PQC). This challenge involves building an autonomous migration agent using the OpenAI Agents SDK and Gemini 2.5 Flash to identify vulnerable cryptographic implementations in legacy codebases and refactor them into a crypto-agile architecture. You will implement a 'Wrapper-First' approach, allowing applications to switch between ML-KEM (Kyber) and classical algorithms without redeploying the entire service. The agent must perform static analysis to detect hardcoded primitives, suggest library replacements using `liboqs`, and generate unit tests that verify both security and performance. The system will leverage OpenAI's tool-calling capabilities to interface with Git repositories and static analysis tools, ensuring that the migration preserves the application's functional integrity while mitigating 'Harvest Now, Decrypt Later' risks.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Functional Integrity
Refactored code must pass existing unit tests for the application logic.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Crypto-Agility Test
Changing the configuration must successfully switch the algorithm from ML-KEM to a classic fallback.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
PQC Coverage
Percentage of legacy crypto calls successfully migrated to the agile wrapper. • target: 100 • range: 0-100
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Master OpenAI Agents SDK by defining functions that allow an agent to read, edit, and test source code within a sandbox.
Implement Crypto-Agile abstractions by creating an interface layer that decouples the application logic from specific cryptographic algorithm implementations.
Design Post-Quantum migration pipelines that prioritize high-risk assets like TLS terminators and identity providers.
Orchestrate multi-step migration workflows where the agent first audits, then patches, and finally validates code performance using Gemini 2.5 Flash.
Optimize agent performance by using structured output to ensure PQC library calls are syntax-correct and follow secure coding guidelines.
Deploy a proof-of-concept that successfully swaps between RSA-3072 and ML-KEM-768 via a simple environment variable change.
How this agent runs
The evaluation measures the agent's ability to refactor a vulnerable codebase to be PQC-ready and crypto-agile.
Challenge input
Legacy source code with embedded RSA-2048 signing/encryption.
OpenAI Agents SDK
Required framework for agentic multi-turn logic.
Gemini 2.5 Flash
Provides fast and accurate code analysis.
liboqs
Industry standard for PQC algorithm implementations.
Evaluated output
Refactored code using a generic 'AgileCrypto' class and liboqs backends.
- Refactored code must pass existing unit tests for the application logic.
- Changing the configuration must successfully switch the algorithm from ML-KEM to a classic fallback.
- Percentage of legacy crypto calls successfully migrated to the agile wrapper. • target: 100 • range: 0-100
- Benchmark: CyberMetric-PQC
- PQC Coverage target: 100
- 1 public reference case
- Python execution harness
- Python sandbox
View technical recipe
Configured tools
- OpenAI · Required
- Azure OpenAI Service · Optional
- OpenAI o3 · Optional
Evaluation contract
- Functional Integrity · Weight 1
- Crypto-Agility Test · Weight 1
- PQC Coverage · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.
Run this agent on your dataset and AI stack
Bring your dataset, model providers, and success criteria. We will scope the right managed run for your team.
Scope a managed run[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
Requires VERSALIST_API_KEY. Works with any MCP-aware editor.
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