| --- |
| pretty_name: Agent Authorization Dataset |
| language: |
| - en |
| license: other |
| --- |
| |
| # Agent Authorization Dataset |
|
|
| Versioned evaluation and research data for the |
| [`Agent_Action_Security`](https://github.com/AnshiHuawei/Agent_Action_Security) project. |
| The current release contains deterministic authorization cases for OpenAI-compatible function-tool |
| traffic. It is used for regression, conformance, generated-corpus, benchmark, and optional planner |
| robustness evaluation; it is not runtime policy or production audit data. |
|
|
| ## Files |
|
|
| | File | Purpose | Records | |
| |---|---|---:| |
| | `data/authz_cases.yaml` | Hand-authored deterministic AuthZ regression and demo cases | 54 | |
| | `data/authz_conformance_golden_v1.yaml` | Reviewed `authz_dataset_v1` conformance matrix | 10 | |
| | `data/authz_generated_cases.jsonl` | Reproducible synthetic `authz_test_case_v1` corpus | 400 | |
| | `data/real_llm_prompts.yaml` | Optional real-LLM planner robustness prompts | 14 scenarios | |
|
|
| The authoritative schemas and validators remain versioned with the application code: |
|
|
| - [`authz_dataset_v1.schema.json`](https://github.com/AnshiHuawei/Agent_Action_Security/blob/19fb18f9e557771de4488e06b9f6b86d2e4ef561/schemas/authz_dataset_v1.schema.json) |
| - [`authz_test_case_v1.schema.json`](https://github.com/AnshiHuawei/Agent_Action_Security/blob/19fb18f9e557771de4488e06b9f6b86d2e4ef561/schemas/authz_test_case_v1.schema.json) |
|
|
| ## Provenance and reproducibility |
|
|
| These files were imported without content changes from |
| `AnshiHuawei/Agent_Action_Security@19fb18f9e557771de4488e06b9f6b86d2e4ef561`. Their import |
| checksums are: |
|
|
| | File | SHA-256 | |
| |---|---| |
| | `authz_cases.yaml` | `35e0981d7b367647a8bb5fc0c2c4e1b51b803d9e5ffdc2f99f9b0434786a446d` | |
| | `authz_conformance_golden_v1.yaml` | `e36cc253fd7a54229d632954c250a9e8e029550a698bd78a1a0052f189d9d50b` | |
| | `authz_generated_cases.jsonl` | `140f81f72ef399c82da8a6e9e4fd35fefcb00e3d8a0fb8851d54909c41346756` | |
| | `real_llm_prompts.yaml` | `5d4dab45bd3155416838e83210645ee8bb4ce040a9fbd515fe06729326cd6ce6` | |
|
|
| `authz_generated_cases.jsonl` is regenerated deterministically with seed `20260713` and generation |
| version `authz-corpus-v1` by `scripts/generate_authz_cases.py` in the application repository. Each |
| `authz_dataset_v1` conformance record contains its own source, transformation, human-review, |
| policy-version, and license-review metadata. The synthetic `authz_test_case_v1` records instead |
| carry deterministic generator, seed, split, generation-version, and policy-version metadata. |
|
|
| ## Privacy and security |
|
|
| The corpus uses fictional demo identities and synthetic authorization scenarios. It must not contain |
| production prompts, access tokens, secrets, real salary records, or personally identifiable |
| information. Runtime Decision Log entries are a separate data class and must not be copied here |
| without the project's reviewed sanitization and dataset-admission process. |
|
|
| ## License |
|
|
| The dataset is `Project-Proprietary`. Use, redistribution, or derivative publication requires |
| permission from the dataset owner. Upstream-derived records additionally retain their per-record |
| provenance and license-review metadata. |
|
|
