llm-redacted
Stop leaking secrets. One function call.
A lightweight, zero-dependency Python library that sanitizes secrets, API keys, PII, and sensitive data from text. Designed for LLM output pipelines.
Installation
pip install llm-redacted
Quick Start
from llm_redacted import sanitize_output
text = "My API key is sk-12345678901234567890"
clean = sanitize_output(text)
print(clean)
# Output: My API key is [OPENAI_KEY]
Features
- 20 Built-in Detectors: OpenAI, AWS, GitHub, Stripe, JWT, GCP, Slack, Twilio, Azure, Discord, PEM, Email, Phone, IPv4, SSN, Credit Cards, Env Vars, Local Paths, Connection Strings, Bearer Tokens.
- Zero Dependencies: Pure Python stdlib.
- Reversible Redaction: Keep a mapping of original secrets to restore them later.
- Streaming Support: Sanitize LLM streams token-by-token.
- Extensible: Add custom regex detectors easily.
Advanced Usage
Reversible Redaction
from llm_redacted import sanitize_output, restore_output
result = sanitize_output("Email admin@test.com", detailed=True)
print(result.cleaned) # Email [EMAIL_1]
restored = restore_output(result.cleaned, result.mapping)
print(restored) # Email admin@test.com
Streaming
from llm_redacted import StreamingSanitizer
sanitizer = StreamingSanitizer()
# feed tokens one by one
safe_token = sanitizer.feed("sk-")
1 maintainer
Metadata
1 maintainer
Release files for llm-redacted 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| llm_redacted-0.2.2.tar.gz | 11.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_redacted-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.9 kB
Release files / llm_redacted-0.2.2.tar.gz
| Download URL | llm_redacted-0.2.2.tar.gz |
|---|---|
| Size | 11.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.9
|
Release files / llm_redacted-0.2.2-py3-none-any.whl
| Download URL | llm_redacted-0.2.2-py3-none-any.whl |
|---|---|
| Size | 14.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1fb348ec132dcbd8ff15b7a30a505ec1407ddf0a62f95e65d77034dee7f9a7f2
|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.9
|
Security for llm-redacted 0.2.2
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None of the files in this release were uploaded with provenance metadata.
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