promptsanitizer 1.0.0

Secrets firewall for AI pipelines — redact credentials and PII before they reach LLMs

promptsanitizer

Secrets firewall for AI pipelines — redact credentials and PII before they reach (or leave) LLMs.

Install

pip install promptsanitizer
# with LLM middleware
pip install "promptsanitizer[openai]"
pip install "promptsanitizer[anthropic]"
pip install "promptsanitizer[all]"

Quick start

from promptsanitizer import Firewall

fw = Firewall()
safe = fw.clean("My key is sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx and email is [e-mail]")
print(safe)
# My key is [REDACTED:openai_key] and email is [REDACTED:email]

Policies

Policy	Behaviour
Policy.default()	Redact all findings (default)
Policy.strict()	Block on any credential, redact PII
Policy.audit()	Allow everything through, only record findings
Policy.custom(rules)	Per-DataClass action map

from promptsanitizer import Firewall, Policy, BlockedError

# Block on credentials
fw = Firewall(policy=Policy.strict())
try:
    fw.clean("token: ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
except BlockedError as e:
    print(e)
    # Blocked: detected github_token in text

# Audit mode — nothing redacted, everything logged
fw = Firewall(policy=Policy.audit())
out = fw.clean("SSN: 123-45-6789")
print(out)
# SSN: 123-45-6789

print(fw.findings)
# [Finding(data_class=<DataClass.SSN: 'ssn'>, severity=<Severity.CRITICAL: 'critical'>,
#          compliance_tags=[HIPAA, GDPR, SOC2], start=5, end=16,
#          matched_value='123-45-6789', placeholder='[REDACTED:ssn]', direction='inbound')]

Custom patterns

import re
from promptsanitizer import Firewall, SecretPattern, DataClass, Severity, ComplianceTag

pattern = SecretPattern(
    name="internal_token",
    data_class=DataClass.GENERIC_API_KEY,
    regex=re.compile(r"INTERNAL-[A-Z0-9]{16}"),
    severity=Severity.HIGH,
    compliance_tags=[ComplianceTag.SOC2],
    placeholder="[REDACTED:internal_token]",
)
fw = Firewall()
fw.add_pattern(pattern)
print(fw.clean("Use token INTERNAL-ABCDEF1234567890 for staging"))
# Use token [REDACTED:internal_token] for staging

Directions

from promptsanitizer import Firewall, Direction

fw = Firewall()
print(fw.clean("key sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", direction=Direction.INBOUND))
# key [REDACTED:openai_key]

print(fw.clean("token ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", direction=Direction.OUTBOUND))
# token [REDACTED:github_token]

# Direction is recorded on each Finding and appears in the compliance report
print({f.direction for f in fw.findings})
# {'inbound', 'outbound'}

Compliance report

fw = Firewall()
fw.clean("card: 4111111111111111")
fw.clean("ssn: 123-45-6789")
print(fw.report().summary())
# Generated : 2026-04-10T21:36:30.895934+00:00
# Findings  : 2
#
# Severity breakdown:
#   critical   2
#
# Data class breakdown:
#   credit_card                    1
#   ssn                            1
#
# Compliance framework exposure:
#   pci_dss    1
#   hipaa      1
#   gdpr       2
#   soc2       2
#
# Direction:
#   inbound    2

OpenAI middleware

import openai
from promptsanitizer.middleware import PromptGuardOpenAI

client = PromptGuardOpenAI(openai.OpenAI())
# Prompts are automatically cleaned before sending; responses are scanned on return

Anthropic middleware

import anthropic
from promptsanitizer.middleware import PromptGuardAnthropic

client = PromptGuardAnthropic(anthropic.Anthropic())

CLI

$ echo "My key sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" | promptguard clean
My key [REDACTED:openai_key]

$ promptguard scan "email: [e-mail]"
[MEDIUM  ] Email Address                       pos 7:20  (gdpr, hipaa, soc2)

1 finding(s) total.

Detected data classes

openai_key · anthropic_key · google_ai_key · aws_access_key · aws_secret_key · github_token · gitlab_token · stripe_key · twilio_token · sendgrid_key · generic_api_key · private_key · jwt_token · connection_string · password · email · phone · ssn · credit_card · ip_address

Compliance frameworks

HIPAA · GDPR · SOC2 · PCI-DSS

Development

pip install -e ".[dev]"
pytest