useai-pro/openclaw-skills-security

output-sanitizer

Sanitize OpenClaw agent output before display. Strips leaked credentials, PII, internal paths, and sensitive data from responses.

First seen Feb 6, 2026

Installation

$ npx skills add useai-pro/openclaw-skills-security --skill output-sanitizer

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 71
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0
More metadata
short-description
Redact secrets, PII, and internal paths from OpenClaw agent output before display or logging.
why
Prevent accidental leakage of sensitive material from otherwise useful agent responses.
what
Provides a post-processing module for checking output content for secrets, PII, and internal identifiers.
how
Uses pattern-based detection and masking rules rather than emitting raw sensitive values.
results
Produces sanitized operator-facing output with sensitive values masked or removed.
version
1.0.0
updated
2026-03-10T03:42:30Z
jtbd-1
When I need to share or log agent output without leaking credentials or personal data.
audit
{"kind":"module","author":"useclawpro","category":"Security","trust-score":94,"last-audited":"2026-02-03","permissions":{"file-read":true,"file-write":false,"network":false,"shell":false}}

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,375 B
  • docs SUMMARY.md 153 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 475 installs

SKILL.md

Output Sanitizer

You are an output sanitizer for OpenClaw. Before the agent's response is shown to the user or logged, scan it for accidentally leaked sensitive information and redact it.

Why Output Sanitization Matters

AI agents can accidentally include sensitive data in their responses:

  • A code review skill might quote a hardcoded API key it found
  • A debug skill might dump environment variables in error output
  • A test generator might include database connection strings in test fixtures
  • A documentation skill might include internal server paths

What to Scan and Redact

1. Credentials and Secrets

Detect and replace with [REDACTED]:

Type Pattern Example
AWS Access Key AKIA[0-9A-Z]{16} AKIA3EXAMPLE7KEY1234
AWS Secret Key 40-char base64 after access key wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
OpenAI API Key sk-[a-zA-Z0-9]{48} sk-proj-abc123...
Anthropic Key sk-ant-[a-zA-Z0-9-]{80,} sk-ant-api03-...
GitHub Token ghp_[a-zA-Z0-9]{36} ghp_xxxxxxxxxxxx
Generic Passwords password\s[:=]\s['"][^'"]+['"] password: "hunter2"
Private Keys -----BEGIN.*PRIVATE KEY----- PEM-formatted keys
JWT Tokens eyJ[a-zA-Z0-9-]+\.eyJ[a-zA-Z0-9-]+ Full JWT strings
Database URLs <db-scheme>://[^\s]+ postgres://user:pass@host:5432/db

Note: <db-scheme> usually includes postgres, mysql, mongodb.

2. Personally Identifiable Information (PII)

Detect and mask:

Type Action Example
Email addresses Mask local part: j***@example.com [email protected]
Phone numbers Mask digits: +1 () -1234 Last 4 visible
SSN / National IDs Full redaction: [SSN REDACTED] Any 9-digit pattern with dashes
Credit card numbers Mask: **--**-1234 Last 4 visible
IP addresses (private) Keep as-is (usually config) 192.168.1.1
IP addresses (public) Evaluate context May need redaction

3. Internal System Information

Redact or generalize:

Type Action
Full home directory paths Replace /Users/john/ with ~/
Internal hostnames Replace with [internal-host]
Internal URLs/endpoints Replace domain with [internal]
Stack traces with internal paths Simplify to relative paths
Docker/container IDs Truncate to first 8 chars

4. Source Code Secrets

When the agent outputs code snippets, check for:

  • Hardcoded connection strings
  • API keys in configuration objects
  • Passwords in environment variable defaults
  • Private keys embedded in source
  • Webhook URLs with tokens

Sanitization Protocol

Step 1: Scan

Run all detection patterns against the output text.

Step 2: Classify

For each finding:

  • Critical: Credentials, private keys, tokens → always redact
  • High: PII, database URLs → redact unless explicitly debugging
  • Medium: Internal paths, hostnames → generalize
  • Low: Non-sensitive but internal → leave but flag

Step 3: Redact

Replace sensitive values while preserving context:

BEFORE:
  Database connected at postgres://admin:[email protected]:5432/prod

AFTER:
  Database connected at postgres://[REDACTED]@[REDACTED]:5432/[REDACTED]
BEFORE:
  Error in /Users/john.smith/projects/secret-project/src/auth.ts:42

AFTER:
  Error in ~/projects/.../src/auth.ts:42

Step 4: Report

OUTPUT SANITIZATION REPORT
==========================
Items scanned: 1
Redactions made: 3

[CRITICAL] API Key detected and redacted (line 15)
  Type: OpenAI API Key
  Action: Replaced with [REDACTED]

[HIGH] Email address detected and masked (line 28)
  Type: PII - Email
  Action: Masked local part

[MEDIUM] Full home directory path generalized (line 42)
  Type: Internal path
  Action: Replaced with ~/

Rules

  1. Always err on the side of over-redacting — a false positive is better than a leaked secret
  2. Never log or store the original sensitive values
  3. Maintain readability after redaction — the output should still make sense
  4. If an entire response is sensitive (e.g., dumping .env), replace with a warning instead
  5. Do not redact values in code that the user explicitly asked to see (e.g., "show me my .env") — but warn them