OpenObscure: Open-Source On-Device Privacy Firewall for AI Agents

What OpenObscure Does

OpenObscure addresses the problem where most PII redaction tools replace sensitive data with placeholders, which breaks LLM functionality since the model can't reason about the structure of obscured data like credit card numbers or SSNs. Instead, OpenObscure uses FF1 Format-Preserving Encryption (AES-256) to encrypt PII values before the request leaves your device. The LLM receives realistic-looking ciphertext that maintains the same format but contains fake values. On the response side, values are automatically decrypted before your agent sees them.

Integration requires just one line: change the base_url to the local proxy.

Core Features

• PII detection: Uses regex + CRF + TinyBERT NER ensemble with 99.7% recall for 15+ data types
• FF1/AES-256 FPE: Keys stored in OS keychain, nothing transmitted
• Cognitive firewall: Scans every LLM response for persuasion techniques across 7 categories using a 250-phrase dictionary + TinyBERT cascade, aligning with EU AI Act Article 5 requirements on prohibited manipulation
• Image pipeline: Face redaction (SCRFD + BlazeFace), OCR text scrubbing, NSFW filter
• Voice processing: Keyword spotting in transcripts for PII trigger phrases
• Architecture: Rust core, runs as Gateway sidecar (macOS/Linux/Windows) or embedded in iOS/Android via UniFFI Swift/Kotlin bindings
• Hardware optimization: Auto-detects device capabilities and selects appropriate tier (Full/Standard/Lite)

Technical Details

The tool is licensed under MIT/Apache-2.0 with no telemetry and no cloud dependency. It's designed to work with OpenClaw, with setup instructions available at the GitHub repository.