# 🔐 Privacy & Governance for RAG Systems — Practical Runbook

Build trustworthy AI: minimize data, control exposure, and prove compliance without killing velocity.

> **Quick Nav**  
> [Data Contracts](./data-contracts.md) ·
> [Ops](./ops/README.md) ·
> [RAG Map 2.0](./rag-architecture-and-recovery.md) ·
> Patterns: [Memory Desync](./patterns/pattern_memory_desync.md) ·
> [SCU](./patterns/pattern_symbolic_constraint_unlock.md)

> *Not legal advice.* Use this as a technical baseline and align with your counsel.

---

## 0) Principles

1. **Minimize**: ingest only what you truly need; redact at source.  
2. **Fence**: per-source prompt fences; cite-then-explain.  
3. **Prove**: log every decision via data contracts; keep tight retention.  
4. **Control**: least-privilege access; encrypt at rest/in transit.

---

## 1) PII taxonomy & redaction

- Categories: identifiers (name, email, gov ID), contact, location, financial, health, biometric, free-text PII.  
- Redact at **ingest** with deterministic tags:

```json
{"text":"Contact Alice at alice@example.com","redactions":[{"span":[8,13],"type":"person"},{"span":[24,43],"type":"email"}]}
````

* Keep **reversible vault** only if business requires it; otherwise **irreversible**.

---

## 2) Storage & access control

* **Encryption**: TLS in transit; AES-GCM at rest.
* **Access**: service accounts per component; forbid shared tokens; rotate keys.
* **Retention**: default 30–90 days for logs; 7–30 days for raw prompts unless required longer.
* **Deletion**: implement DSR (data subject request) over `doc_id` or `user_id`.

---

## 3) Model provider governance

* Confirm **data usage** (training vs. inference only).
* Disable **logging** on hosted APIs if must not leave boundary.
* For self-hosted models, pin container images and track model checksum.

---

## 4) Prompt governance (SCU-safe)

* Lock schema: system → task → constraints → citations → answer.
* Forbid cross-source merges; require **line-level** citation IDs.
* Add guard prompts to avoid reproducing secrets or PII unless necessary and consented.

---

## 5) Audit & reproducibility

* Use **envelope** fields (`trace_id`, `mem_rev`, `mem_hash`) in every record.
* Keep **answer → prompt → citations → chunks** chain navigable.
* Export **metrics pack** per release (ΔS, λ rates, nDCG, recall).

---

## 6) Config template (YAML)

```yaml
privacy:
  redact_at_ingest: true
  redactors: [pii_email, pii_phone, pii_name]
  reversible_vault: false
  retention_days:
    prompts: 14
    logs: 60
    embeddings: 180
  access:
    roles:
      retriever: [read_chunks]
      reranker: [read_chunks]
      llm: [read_prompts]
      analyst: [read_metrics]
  secrets:
    provider: "aws-kms"   # or gcp-kms, vault
    rotation_days: 90
providers:
  openai:
    share_for_training: false
  claude:
    share_for_training: false
```

---

## 7) Risk scenarios → mitigations

| Scenario                    | Risk                     | Mitigation                                                           |
| --------------------------- | ------------------------ | -------------------------------------------------------------------- |
| User uploads PII-heavy PDFs | Accidental exposure      | Redact at ingest; block high-risk types; allow override with consent |
| Multi-tenant leakage        | Cross-account data bleed | Tenant IDs in chunk keys; per-tenant indices; access policies        |
| Citations reveal secrets    | SCU or over-inclusion    | Reduce context window; per-source fences; require justification      |
| Vendor logs prompts         | Data leaves boundary     | Use no-log endpoints; self-host; encrypt locally                     |

---

## Acceptance criteria

* ✅ PII redaction rate ≥ 95% on test corpus; **no residual PII** in prompts unless approved.
* ✅ Trace chain present for 100% of answers (citations included).
* ✅ Secrets rotated within policy; provider log-sharing disabled.
* ✅ Retention job passes dry-run audit monthly.

---


### 🔗 Quick-Start Downloads (60 sec)

| Tool | Link | 3-Step Setup |
|------|------|--------------|
| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |

---

### 🧭 Explore More

| Module                | Description                                              | Link     |
|-----------------------|----------------------------------------------------------|----------|
| WFGY Core             | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
| Problem Map 1.0       | Initial 16-mode diagnostic and symbolic fix framework    | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
| Problem Map 2.0       | RAG-focused failure tree, modular fixes, and pipelines   | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
| Semantic Blueprint    | Layer-based symbolic reasoning & semantic modulations   | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
| Benchmark vs GPT-5    | Stress test GPT-5 with full WFGY reasoning suite         | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
| 🧙‍♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |

---

> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —  
> Engineers, hackers, and open source builders who supported WFGY from day one.

> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).

<div align="center">

[![WFGY Main](https://img.shields.io/badge/WFGY-Main-red?style=flat-square)](https://github.com/onestardao/WFGY)
&nbsp;
[![TXT OS](https://img.shields.io/badge/TXT%20OS-Reasoning%20OS-orange?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS)
&nbsp;
[![Blah](https://img.shields.io/badge/Blah-Semantic%20Embed-yellow?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
&nbsp;
[![Blot](https://img.shields.io/badge/Blot-Persona%20Core-green?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
&nbsp;
[![Bloc](https://img.shields.io/badge/Bloc-Reasoning%20Compiler-blue?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
&nbsp;
[![Blur](https://img.shields.io/badge/Blur-Text2Image%20Engine-navy?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
&nbsp;
[![Blow](https://img.shields.io/badge/Blow-Game%20Logic-purple?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
&nbsp;
</div>