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
Develop an autonomous agent that refactors legacy Python/C++ code to use NIST PQC standards through a crypto-agile wrapper using OpenAI Agents SDK and Gemini 2.5 Flash.
How work is evaluated
The evaluation measures the agent's ability to refactor a vulnerable codebase to be PQC-ready and crypto-agile.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
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.
Learning goals
Master the OpenAI Agents SDK for multi-turn code refactoring tasks
Implement NIST Post-Quantum Cryptography standards (ML-KEM, ML-DSA)
Design crypto-agile software architectures that support algorithm hot-swapping
Configure Gemini 2.5 Flash for high-speed, cost-effective code analysis and generation
Integrate liboqs for standardized PQC implementations in legacy environments
Resources
Synthetic codebase containing 20+ Python files with varied cryptographic implementations (RSA, ECDSA, AES-GCM) and associated mock unit tests.
Challenge setup
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 (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
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
Metrics
- PQC Coverage · Target 100
Benchmarks
- CyberMetric-PQC
- security
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: Legacy source code with embedded RSA-2048 signing/encryption.
Output: Refactored code using a generic 'AgileCrypto' class and liboqs backends.
Execution harness: Python
Evaluation tools
- OpenAI Agents SDK · agent-orchestrator
- Gemini 2.5 Flash · reasoning-model
- liboqs · crypto-library
Recipe freeze marker
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