Security●●Solid
NoPII – One line of code to protect PII before it hits your LLM
Change one base_url to tokenize PII — blocks requests if the service is unreachable.
Solve My ProblemSlick
mroling
251mo ago
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Blindfold – PII protection for LLM apps (local regex and cloud NLP)
by mnagas·Mar 3, 2026·1 point·1 comment
AI Analysis
●●SolidSolve My ProblemSlick
Reversible tokenization for LLM prompts, but this exact problem has competing solutions.
Strengths
- •Multi-mode architecture: free offline regex + optional cloud NLP covers both budget and accuracy needs.
- •Genuinely multi-language support (18 languages with tiered NLP accuracy) is rare in PII detection.
- •Wire-protocol agnostic — works with any LLM API (OpenAI, Claude, Bedrock) via simple tokenize/detokenize sandwich.
Weaknesses
- •PII scrubbing for LLMs is increasingly table stakes — Anthropic has prompt caching guards, Anthropic/OpenAI both filter headers; positioning unclear.
- •No independent audit of regex accuracy or cloud NLP false positive rates; regex-only mode at 86 types lacks real-world benchmark against alternatives.
Category
Target Audience
AI/LLM application developers handling sensitive data (healthcare, finance, SaaS)
Similar To
Anthropic (prompt guards) · Presidio (Microsoft's open-source PII detection) · AWS Macie
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