OpenAI released Privacy Filter, an open-weight model that detects and redacts eight categories of personally identifiable information in text using context-aware language understanding rather than simple pattern matching. It runs locally on long inputs in a single pass and uses BIOES span tags for precise masking. The model was built by converting a pretrained language model into a token classifier and trained on a mix of public and synthetic data.

• Uses context-aware language understanding instead of regex, so it distinguishes public figures from private individuals and catches hidden credentials like passwords
• Small enough to run entirely locally, processing long documents in a single pass
• Built by converting a pretrained language model into a bidirectional token classifier trained on public plus synthetic data, with model-assisted annotation and human review filling gaps
• Tags eight PII categories using BIOES span tagging for clean, precise redaction boundaries