promptmasker 0.0

Heuristic prompt masking utility for sensitive data

PromptMasker

PromptMasker is a prompt-sanitization utility that heuristically detects and masks sensitive data in raw text before it is sent to LLMs, logs, or external services.

It is designed to sit before your model call or logging layer and reduce the risk of accidentally leaking credentials or personal data.

This is redaction, not encryption.

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Why PromptMasker exists

LLMs are often fed:

• raw user input
• debugging prompts
• logs copied from real systems

Those inputs frequently contain:

• API keys
• emails
• phone numbers
• internal IDs

PromptMasker is built to intercept that text early and neutralize obvious sensitive tokens without requiring rigid schemas or strict formatting.

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What it masks

PromptMasker attempts to detect and mask:

• API keys / secrets
  Context-aware, alphanumeric tokens near phrases like “api key”

• Email addresses
  Detected by structure and local intent

• Phone / mobile numbers
  Numeric tokens (8–15 digits) near phone-related phrases

• Generic sensitive tokens
  Long numeric or mixed alphanumeric identifiers via fallback heuristics

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How detection works (important)

Detection is heuristic and layered, not rule-perfect:

• Fuzzy keyword matching
  (api key, email id, phone no, etc.)

• Sliding context windows
  (tokens near intent phrases are prioritized)

• Structural heuristics
  (length, digits, alphanumeric composition)

• Global fallback
  for obviously sensitive-looking tokens

This means:

• false positives are possible
• behavior is intentionally conservative

That trade-off is deliberate.

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What PromptMasker is NOT

• Not encryption
• Not anonymization
• Not compliance-grade security

If you need cryptographic guarantees, do not use this.

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Installation

pip install promptmasker

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Sample Usage

from promptmasker import PromptMasker

masker = PromptMasker(mode="hash", salt="session")
text = "My api key is sk-1234567890 and email [e-mail]"

print(masker.mask(text))