Datasets:

intertwine-ai
/

security-verifiers-e1-metadata

license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - security
  - rl
  - network-security
  - anomaly-detection
  - verifiers
  - metadata-only
pretty_name: Security Verifiers E1 - Network Log Anomaly Detection (Metadata)
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: meta
        path: data/meta-*
dataset_info:
  features:
    - name: section
      dtype: string
    - name: name
      dtype: string
    - name: description
      dtype: string
    - name: payload_json
      dtype: string
    - name: version
      dtype: string
    - name: created_at
      dtype: string
  splits:
    - name: meta
      num_bytes: 2518
      num_examples: 6
  download_size: 5613
  dataset_size: 2518

🔒 Security Verifiers E1: Network Log Anomaly Detection (Public Metadata)

⚠️ This is a PUBLIC metadata-only repository. The full datasets are hosted privately to prevent training contamination. See below for access instructions.

Overview

E1 is a network log anomaly detection environment with calibrated classification and abstention. This repository contains only the sampling metadata that describes how the private datasets were constructed.

Why Private Datasets?

Training contamination is a critical concern for benchmark integrity. If datasets leak into public training corpora:

Models can memorize answers instead of learning to reason
Evaluation metrics become unreliable
Research reproducibility suffers
True capabilities become obscured

By keeping evaluation datasets private with gated access, we:

✅ Preserve benchmark validity over time
✅ Enable fair model comparisons
✅ Maintain research integrity
✅ Allow controlled access for legitimate research

Dataset Composition

The private E1 datasets include:

Primary Dataset: IoT-23

Samples: 1,800 network flows (train/dev/test splits)
Source: IoT-23 botnet dataset
Features: Network flow statistics, timestamps, protocols
Labels: Benign vs Malicious with confidence scores
Sampling: Stratified by label and split

Out-of-Distribution Datasets

CIC-IDS-2017: 600 samples (different attack patterns)
UNSW-NB15: 600 samples (different network environment)
Purpose: Test generalization and OOD detection

What's in This Repository?

This public repository contains:

Sampling Metadata (sampling-*.json):
- Dataset versions and sources
- Sampling strategies and random seeds
- Label distributions
- Split ratios
- Reproducibility parameters
Tools Versions (referenced in metadata):
- Exact versions of all preprocessing tools
- Dataset library versions
- Python environment specifications
This README: Instructions for requesting access

Reward Components

E1 uses composable reward functions:

Accuracy: Correctness of malicious/benign classification
Calibration: Alignment between confidence and actual accuracy
Abstention: Reward for declining on uncertain examples
Asymmetric Costs: Higher penalty for false negatives (security context)

Requesting Access

🔑 To access the full private datasets:

Open an access request issue: Security Verifiers Issues
Use the title: "Dataset Access Request: E1"
Include:
- Your name and affiliation
- Research purpose / use case
- HuggingFace username
- Commitment to not redistribute or publish the raw data

Approval criteria:

Legitimate research or educational use
Understanding of contamination concerns
Agreement to usage terms

We typically respond within 2-3 business days.

Citation

If you use this environment or metadata in your research:

@misc{security-verifiers-2025,
  title={Open Security Verifiers: Composable RL Environments for AI Safety},
  author={intertwine},
  year={2025},
  url={https://github.com/intertwine/security-verifiers},
  note={E1: Network Log Anomaly Detection}
}

Related Resources

GitHub Repository: intertwine/security-verifiers
Documentation: See EXECUTIVE_SUMMARY.md and PRD.md in the repo
Framework: Built on Prime Intellect Verifiers
Other Environments: E2 (Config Verification), E3-E6 (in development)

License

MIT License - See repository for full terms.

Contact

Issues: GitHub Issues
Discussions: GitHub Discussions

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