6.6 KiB
PII Handling and Minimization — Guardrails and Fix Patterns
A governance fix page for when personally identifiable information (PII) leaks, handling is unclear, or minimization principles are violated.
Use this page when data pipelines, embeddings, or RAG outputs contain sensitive fields that cannot be justified or audited.
When to use this page
- Retrieval responses contain raw PII that was not required for the task.
- Embeddings or chunks accidentally ingest names, emails, IDs, or financial data.
- Redaction or anonymization rules are inconsistently applied.
- No audit trail exists for who accessed or approved PII exposure.
- Waivers for PII usage lack expiry, owner, or justification.
Acceptance targets
- PII fields are redacted, hashed, or minimized in ≥ 0.98 of stored embeddings.
- Retrieval outputs contain no raw identifiers unless explicitly approved.
- ΔS(question, retrieved) ≤ 0.45 for governed answers (no drift into unapproved fields).
- All PII queries pass through policy checks with logging enabled.
- Every waiver or override has an accountable owner and time-bound expiry.
Typical breakpoints and WFGY fix
-
Embedding or vector ingestion leaks PII
→ embedding-vs-semantic.md
Enforce PII scrub before embedding. Validate with spot-checks against gold set. -
Chunking preserves identifiers across splits
→ chunking-checklist.md
Require token-level scrub of identifiers, then re-chunk. -
Answers expose sensitive spans without approval
→ retrieval-traceability.md
Enforce citation schema, ensure only approved snippets are surfaced. -
Policy bypass in orchestration or tools
→ prompt-injection.md
Guard against malicious queries that try to extract hidden PII. -
Audit trail gaps
→ audit_and_logging.md
Require immutable logs of every PII access and minimization check.
Minimal governance checklist
- Redact on ingest — Apply regex/sensitive data detection before storing text or embeddings.
- Schema enforce — Store
doc_id,pii_flag,redacted_textside by side for traceability. - Chunk validation — Randomly sample and confirm PII scrubbed before index build.
- Policy in LLM prompts — Require “no PII unless approved waiver” as hard guardrail.
- Audit logs — Track every waiver, approval, and override. Immutable and joinable to lineage.
- Expiry enforcement — Waivers expire automatically; extension requires re-approval.
🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
| TXT OS (plain-text 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 → |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | View → |
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | View → |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | View → |
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | View → |
| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | View → |
| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | Start → |
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Engineers, hackers, and open source builders who supported WFGY from day one.
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