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---
license: mit
task_categories:
- text-classification
- token-classification
language:
- en
tags:
- security
- rl
- kubernetes
- terraform
- config-verification
- verifiers
- metadata-only
pretty_name: Security Verifiers E2 - Config Verification (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: 2380
    num_examples: 6
  download_size: 5778
  dataset_size: 2380
---

# ๐Ÿ”’ Security Verifiers E2: Security Configuration Verification (Public Metadata)

> **โš ๏ธ This is a PUBLIC metadata-only repository.** The full datasets are hosted privately to prevent training contamination. See below for access instructions.

## Overview

E2 is a tool-grounded configuration auditing environment for Kubernetes and Terraform. 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:
- โœ… Preserve benchmark validity over time
- โœ… Enable fair model comparisons
- โœ… Maintain research integrity
- โœ… Allow controlled access for legitimate research

### Dataset Composition

The private E2 datasets include:

#### Kubernetes Configurations
- **Source**: Real-world K8s manifests from popular open-source projects
- **Scans**: KubeLinter, Semgrep, OPA/Rego policies
- **Violations**: Security misconfigurations, best practice violations
- **Severity**: Categorized (high/medium/low) based on tool outputs

#### Terraform Configurations
- **Source**: Infrastructure-as-code from real projects
- **Scans**: Semgrep, OPA/Rego policies, custom rules
- **Violations**: Security risks, compliance issues
- **Severity**: Weighted scoring for reward computation

### What's in This Repository?

This public repository contains:

1. **Sampling Metadata** (`sampling-*.json`):
   - Source repository information
   - File selection criteria
   - Scan configurations
   - Label distributions
   - Reproducibility parameters

2. **Tools Versions** (`tools-versions.json`):
   - KubeLinter version (pinned)
   - Semgrep version (pinned)
   - OPA version (pinned)
   - Ensures reproducible scanning

3. **This README**: Instructions for requesting access

### Reward Components

E2 uses tool-grounded reward functions:
- **Detection Precision/Recall/F1**: Against ground-truth violations
- **Severity Weighting**: Higher reward for catching critical issues
- **Patch Delta**: Reward for proposed fixes that eliminate violations
- **Re-scan Verification**: Patches must pass tool validation

**Multi-turn performance**: Models achieve ~0.93 reward with tool calling vs ~0.62 without tools.

### Requesting Access

๐Ÿ”‘ **To access the full private datasets:**

1. **Open an access request issue**: [Security Verifiers Issues](https://github.com/intertwine/security-verifiers/issues)
2. **Use the title**: "Dataset Access Request: E2"
3. **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:

```bibtex
@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={E2: Security Configuration Verification}
}
```

### Related Resources

- **GitHub Repository**: [intertwine/security-verifiers](https://github.com/intertwine/security-verifiers)
- **Documentation**: See `EXECUTIVE_SUMMARY.md` and `PRD.md` in the repo
- **Framework**: Built on [Prime Intellect Verifiers](https://github.com/PrimeIntellect-ai/verifiers)
- **Other Environments**: E1 (Network Logs), E3-E6 (in development)

### Tools

The following security tools are used for ground-truth generation:
- **KubeLinter**: Kubernetes YAML linting and security checks
- **Semgrep**: Pattern-based static analysis for K8s and Terraform
- **OPA**: Policy-as-code validation with Rego

### License

MIT License - See repository for full terms.

### Contact

- **Issues**: [GitHub Issues](https://github.com/intertwine/security-verifiers/issues)
- **Discussions**: [GitHub Discussions](https://github.com/intertwine/security-verifiers/discussions)

---

**Built with โค๏ธ for the AI safety research community**