| --- |
| license: mit |
| task_categories: |
| - text-classification |
| - other |
| language: |
| - en |
| - code |
| tags: |
| - security |
| - secrets |
| - pii |
| - llm |
| - owasp |
| - synthetic |
| - source-code |
| - masking |
| size_categories: |
| - n<1K |
| pretty_name: Synthetic Sensitive Data in Source Code (N=300) |
| --- |
| |
| # Synthetic Sensitive Data in Source Code (N=300) |
|
|
| Synthetic dataset of **300** source-code / config snippets containing **hardcoded secrets and PII**. |
| Every sample includes at least one sensitive finding (no clean negatives). |
|
|
| Designed for evaluating local masking, secret detection, and **OWASP LLM02 — Sensitive Information Disclosure** scenarios in AI-assisted coding workflows. |
|
|
| **Version 1.2:** `multi_secret` (and related) samples label **every** secret present in `code_text` (complete ground truth). |
|
|
| > All values are **synthetic / fake**. Do not treat them as real credentials. |
|
|
| ## Files |
|
|
| | File | Description | |
| |------|-------------| |
| | `synthetic_sensitive_data_in_source_code_n300.json` | Full records + ground-truth `sensitive_findings` | |
| | `synthetic_sensitive_data_in_source_code_n300.csv` | Flat view (`\n` escaped) | |
| | `synthetic_sensitive_data_in_source_code_n300_excel.csv` | Excel-friendly (comma + BOM) | |
| | `synthetic_sensitive_data_in_source_code_n300_tr.csv` | Turkish Excel (semicolon + BOM) | |
| | `synthetic_sensitive_data_in_source_code_n300.xlsx` | Excel workbook | |
| | `dataset_stats.json` | Distribution summary | |
|
|
| ## Categories (N=300) |
|
|
| | Category | Count | |
| |----------|------:| |
| | `api_key` | 55 | |
| | `password_secret` | 50 | |
| | `connection_string` | 45 | |
| | `pii` | 45 | |
| | `internal_url` | 40 | |
| | `multi_secret` | 35 | |
| | `private_key_keystore` | 30 | |
|
|
| Languages include Python, JavaScript, Java, C#, Kotlin, Go, Bash, env, YAML, and JSON. |
|
|
| ## Schema |
|
|
| - `id` — sample id (`SDS-####`) |
| - `category` — primary category |
| - `language` — snippet language |
| - `code_text` — raw code/config (model input) |
| - `sensitive_count` — number of labeled secrets |
| - `finding_types` — secret types joined by `|` (CSV) |
| - `sensitive_findings` — ground-truth list (JSON only) |
|
|
| OWASP alignment is dataset-level (`LLM02`); there is no per-row OWASP column. |
|
|
| ## Intended use |
|
|
| - Secret / PII detection benchmarks |
| - Local masking and reverse-masking evaluation |
| - Prompt/code leakage experiments with LLMs |
|
|
| ## Notes |
|
|
| - Fully synthetic; reproducible with `seed=42` |
| - Average secrets per sample ≈ 1.29 |
| - Not a production vulnerability corpus |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the related thesis / paper work by Nisa Nur Efendioğlu. |
|
|
