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CONTRIBUTING.md

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# Contributing to RAG Integrity Firewall
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Thank you for your interest in contributing!
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We welcome bug reports, feature requests, new scanners, policy examples, and integrations with other frameworks.
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---
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## Ways to contribute
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- **Bug reports:** Open an issue with clear steps to reproduce.
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- **Feature requests:** Suggest enhancements or new scanners in [GitHub Issues](https://github.com/taladari/rag-firewall/issues).
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- **Code contributions:** Submit a pull request (PR).
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- **Docs/examples:** Improve the README, examples, or add tutorials.
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---
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## Development setup
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1. Fork and clone the repo:
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```bash
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git clone https://github.com/<your-fork>/rag-firewall.git
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cd rag-firewall
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```
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2. Install in editable mode:
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```bash
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python -m venv .venv && source .venv/bin/activate
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pip install -e .
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pip install -r requirements-dev.txt
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```
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3. Run the test suite:
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```bash
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pytest -q
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```
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---
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## Coding guidelines
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- Follow existing project style (PEP8, docstrings for public methods).
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- Add unit tests for new functionality (`tests/`).
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- Keep scanners modular (one file per scanner under `rag_firewall/scanners/`).
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- Include example usage if adding a new integration or CLI command.
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---
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## Security issues
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If you discover a security vulnerability, please **do not file a public issue**.
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Instead, email us at **[email protected]**.
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We will respond promptly and coordinate a fix.
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---
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## Roadmap
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See [ROADMAP.md](ROADMAP.md) for planned features and enterprise enhancements.
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---
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Thanks for helping improve RAG Integrity Firewall!

README.md

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# RAG Integrity Firewall
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A retrieval-time trust layer for RAG systems.
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The firewall scans chunks before they reach your LLM, detects and blocks risks such as prompt injection or secret leaks, enforces policies, and re-ranks content by trustworthiness.
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RAG Integrity Firewall is a lightweight, client-side security layer for retrieval-augmented generation (RAG) systems.
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It scans retrieved chunks before they reach your LLM, blocks high-risk inputs such as prompt injection and secret leaks, and applies policies to down-rank stale or untrusted content.
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It runs entirely client-side: no data leaves your environment.
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See the [ROADMAP.md](ROADMAP.md) for planned enhancements and upcoming enterprise features.
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---
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## Who is this for?
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- **Teams building RAG/LLM applications** who want to reduce risk before adoption.
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- **Platform engineers** adding guardrails without rewriting their pipelines.
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- **Security-conscious organizations** (finance, government, healthcare) where data must stay inside.
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## What this is not
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- Not a SaaS or cloud service — the firewall runs **entirely client-side**, no data leaves your environment.
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- Not an LLM output filter — it focuses on retrieval-time risks, not response moderation.
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- Not a silver bullet — it complements other security layers like authentication, RBAC, and output review.
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## License
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[Apache 2.0](LICENSE)
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---
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## Next Steps
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- Read the [ROADMAP](ROADMAP.md) to see planned features and enterprise enhancements.
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- Check the [examples](examples/) folder for quick integration demos.
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- File issues or feature requests in [GitHub Issues](https://github.com/taladari/rag-firewall/issues).
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- Contribute scanners, policy examples, or framework adapters via pull requests.
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For organizations interested in enterprise features (dashboard, centralized audit, compliance mapping), please reach out to discuss early access.

ROADMAP.md

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# RAG Integrity Firewall Roadmap
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This roadmap outlines where the project is headed.
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It covers **open-source milestones** as well as **enterprise features** we plan to explore for organizations with stricter requirements.
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---
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## Open Source (Community Edition)
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These features will remain free and open:
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- **Core scanners**
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- Prompt injection (regex)
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- Secrets & API keys
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- PII (emails, phones, SSNs)
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- Encoded/Base64 detection
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- URL/domain allow & deny lists
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- Conflict/staleness detection
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- **Policy engine**
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- Allow, deny, rerank decisions
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- Weighting for recency, provenance, relevance
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- **Provenance**
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- SHA256 hashing of chunks
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- Optional SQLite store
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- **Audit logs**
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- JSONL audit trail for each decision
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- **Integrations**
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- LangChain retrievers (`FirewallRetriever`)
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- LlamaIndex retrievers (`TrustyRetriever`)
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- **CLI**
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- `ragfw index` — index and hash documents
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- `ragfw query` — run queries with firewall checks
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---
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## Short-Term Enhancements (OSS)
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- Additional regex/signature patterns (prompt injection & secrets)
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- Expanded test suite and benchmarks
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- Config schema validation
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- Examples with more frameworks (Haystack, OpenAI RAG SDK)
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---
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## Enterprise Features (Planned)
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These are under active design and may be offered as part of a **paid Enterprise Edition**:
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- **Policy Management Dashboard**
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Web UI for managing firewall policies, roles, and configs without YAML editing.
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- **Centralized Audit & Alerts**
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Aggregated audit logs with dashboards, Slack/email/SIEM integration for high-severity findings.
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- **Threat Intelligence Feeds**
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Regular updates with new prompt injection patterns, API key formats, and risk signatures.
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- **Enterprise Connectors**
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Pre-built ingestion + firewall adapters for platforms like SharePoint, Confluence, and Google Workspace.
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- **Compliance Mapping**
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Exportable reports mapping firewall policies to frameworks such as:
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- EU AI Act
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- NIST AI Risk Management Framework
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- ISO/IEC 42001
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---
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## Longer-Term Ideas
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- ML-based classifiers for sophisticated prompt injection patterns (optional, local-only).
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- Policy simulation mode (dry-run audits without enforcement).
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- “Red team” testing harness to evaluate RAG pipelines automatically.
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- Multi-tenant support for large organizations.
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---
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## How to Contribute
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- Use the [Issues](https://github.com/taladari/rag-firewall/issues) tab for bug reports and feature requests.
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- Pull requests are welcome — especially for new scanners, policy examples, or framework integrations.
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- For enterprise features, please [contact us](mailto:[email protected]) if you’d like to be an early design partner.
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SECURITY.md

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audit.jsonl

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pyproject.toml

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[project]
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name = "rag-firewall"
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version = "0.2.0"
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description = "Retrieval-time trust layer for RAG: poisoning detection, policies, provenance, and audit."
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version = "0.3.0"
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description = "Client-side retrieval firewall for RAG systems — blocks prompt injection and secret leaks, re-ranks stale or untrusted content, and keeps all data inside your environment."
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readme = { file = "README.md", content-type = "text/markdown" }
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requires-python = ">=3.9"
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authors = [{ name = "RAG Firewall Maintainers" }]
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]
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[project.urls]
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Homepage = "https://github.com/your-org/rag-firewall"
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Repository = "https://github.com/your-org/rag-firewall"
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Homepage = "https://github.com/taladari/rag-firewall"
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Repository = "https://github.com/taladari/rag-firewall"
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[project.scripts]
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ragfw = "rag_firewall.cli:main"

requirements-dev.txt

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-r requirements.txt
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# Development and testing dependencies
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pytest>=7.0
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build>=1.0.3
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twine>=5.0.0
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twine>=4.0.2
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tomli>=2.0.1

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