ShmalexFlow/whiteout-compliance-benchmark

Whiteout AI Compliance Benchmark

A 15,915-prompt benchmark for evaluating AI compliance engines — systems that enforce content policies on user prompts before they reach AI providers.

Built by Groovy Security for the Whiteout AI platform.

Dataset Summary

Property	Value
Total prompts	15,915
Categories	9 (PHI, PII, GDPR, Legal, Code, Confidential, Security, Finance, Education)
Policies	74 across all categories
Prompt types	3 (safe, violation, edge_case)
Character length range	16 — 12,000+
Language	English

Structure

Each row contains:

• text: the prompt to be evaluated
• category: policy category (PHI, PII, GDPR, Legal, Code, Confidential, Security, Finance, Education)
• policy_id: specific policy being tested (e.g., block_ssn, detect_exam_cheating)
• prompt_type: one of safe (should pass), violation (should be blocked), edge_case (borderline, should pass)
• expected: pass or block
• length_chars: character count
• length_bucket: size category (<100, 100-300, 300-800, 800-2K, 2K-5K, 5K-10K, 10K+)
• phase: phase1_short, phase2_long, or education

Phases

• Phase 1 (13,792 prompts): Short prompts (<2K chars) covering 8 enterprise data protection categories
• Phase 2 (1,116 prompts): Long-form prompts (1K-12K chars) — emails, memos, chat transcripts, reports, documents
• Education (1,007 prompts): Academic integrity (student perspective) + institutional data protection (faculty perspective)

Benchmark Results

Evaluated against Whiteout AI's semantic compliance engine (qwen3.5:27b, pure semantic, no regex):

Phase	Prompts	Accuracy
Phase 1 (short)	13,792	99.13%
Phase 2 (long)	1,116	99.91%
Education	1,007	99.21%
Combined	15,915	99.19%

Usage

from datasets import load_dataset

ds = load_dataset("ShmalexFlow/whiteout-compliance-benchmark")

# Filter by category
phi_prompts = ds["train"].filter(lambda x: x["category"] == "PHI")

# Filter by type
violations = ds["train"].filter(lambda x: x["prompt_type"] == "violation")

# Filter by phase
long_prompts = ds["train"].filter(lambda x: x["phase"] == "phase2_long")

Citation

If you use this dataset, please cite:

@dataset{whiteout_compliance_benchmark_2026,
  title={Whiteout AI Compliance Benchmark},
  author={Groovy Security},
  year={2026},
  url={https://huggingface.co/datasets/ShmalexFlow/whiteout-compliance-benchmark},
  note={15,915 prompts for evaluating AI compliance engines across enterprise and education domains}
}

License

Apache 2.0

Contact

• Product: Whiteout AI
• Company: Groovy Security