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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
---
# 🔒 Security Verifiers E2: Security Configuration Verification (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
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:
- ✅ Preserve benchmark validity over time
- ✅ Enable fair model comparisons
- ✅ Maintain research integrity
- ✅ 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
🔑 **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)
---
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