Data & analysis

DCL Sentinel Trace — PII Redactor & Identity Exposure Detector

Try it

Detect and redact 8 categories of personally identifiable information in AI outputs, with optional on-chain-verified scans.

What it does

Scans AI output for emails, phone numbers, national IDs, bank card PANs (with Luhn validation), IBANs, crypto wallet addresses, IP addresses, and passport numbers. Use the free instruction-only checklist for offline review, or call the live `dcl_evaluate_pii` MCP tool ($0.02 per scan, USDC on Base via x402) for an independently verifiable, on-chain-anchored scan that returns a cryptographic tx_hash seal. Only redacted samples and an input hash are stored; the raw text is never persisted.

When to use it

  • Pre-delivery privacy checkpoint on LLM outputs
  • Scanning agent-produced datasets that may contain real PII
  • Adding an on-chain-anchored audit seal to redacted logs
  • Pairing with a credential-leak scan for full output coverage

The skill document

DCL Sentinel Trace — Leibniz Layer™

Publisher: @daririnch · Fronesis Labs Version: 3.0.0 Part of: DCL Skills · Leibniz Layer™ Security Suite MCP endpoint: https://mcp.fronesislabs.com/mcp (DCL Trust Oracle)


⚠️ Now backed by a live, paid regex scan — same checklist, real server

Starting with v3.0.0, the categories below can be run two ways:

  1. Free, instruction-only — the agent works through the checklist itself, entirely inside its own context. No network call, no charge.
  2. Paid, live — the same eight categories, run as real regex (plus a Luhn checksum on card numbers to cut false positives) against the live DCL Trust Oracle MCP server, settled on-chain via x402 in USDC on the Base network, returning a cryptographic tx_hash seal. No subscription, no account — pay per call.

This is a close one-to-one match: the live tool implements the same T1-T8 categories documented here. Use the free mode for manual review or offline work; use the live mode when you want an independently verifiable, on-chain-anchored proof of the scan.


What this skill does

Detects and redacts personally identifiable information in AI outputs before they reach users or downstream systems.

What gets detected

CategoryExamples
emailAny email address pattern
phoneInternational format numbers (with country code)
national_idUS-style SSN pattern (###-##-####)
bank_cardCard PANs, verified with a Luhn checksum to reduce false positives
ibanInternational bank account numbers
crypto_addressBitcoin and Ethereum wallet address formats
ip_addressIPv4 and IPv6 addresses
passportPassport/document numbers appearing in explicit passport context

When to use this skill

  • AI output may contain personal data from user input, documents, or retrieved content
  • A coding or data agent processes datasets that may contain real PII
  • You need a privacy checkpoint before logging or storing AI outputs

Live tool (paid, USDC on Base via x402)

MCP toolPriceWhat it runs
dcl_evaluate_pii$0.02Regex scan across all 8 categories above; any finding → NO_COMMIT

Connecting to the live server

{
  "mcpServers": {
    "dcl-trust-oracle": {
      "url": "https://mcp.fronesislabs.com/mcp"
    }
  }
}

Payment is handled automatically for x402-capable clients; clients without native x402 support fall back to a guided payment flow. No API key or account signup is required — only a wallet capable of paying in USDC on Base. Prices are set server-side and may change; the MCP tool description returned by the server at call time is the source of truth.

Calling the tool

result = dcl_evaluate_pii(
    response=agent_output,
    agent_id="my-agent-01",
)

if result["verdict"] == "NO_COMMIT":
    redact_and_reprocess(result["findings"])
else:
    log_audit(result["tx_hash"])

Output shape

{
  "verdict": "COMMIT | NO_COMMIT",
  "risk_score": 0.0,
  "findings": [
    {
      "type": "email",
      "position": 14,
      "redacted_sample": "jo****doe.com",
      "severity": "major",
      "category": "T1"
    }
  ],
  "detection_count": 0,
  "categories_checked": ["T1","T2","T3","T4","T5","T6","T7","T8"],
  "categories_clear": ["T1","T2","T3","T4","T5","T6","T7","T8"],
  "tx_hash": "string",
  "chain_index": 0,
  "input_hash": "string",
  "timestamp": 0.0,
  "seal_text": "🔒 Verified by Leibniz Layer | Fronesis Labs\nHash: ...\nIntent: ...\nSealed: ... — Base Mainnet\nVerify: https://x402.fronesislabs.com/verify/...",
  "verify_url": "https://x402.fronesislabs.com/verify/"
}

Only input_hash (a hash of the scanned text) and finding metadata are written to the audit chain — the raw text and any real personal data are never stored. redacted_sample shows only the first 2 and last 4 characters of any match.


Free instruction-only checklist (no network call, no charge)

Paste the text to scan into the conversation and work through the checklist below entirely inside the agent's own context. Nothing here contacts any server.

Step 1 — Run the detection checklist

Work through each category. For each match found, record type, a redacted_sample (masked version, e.g. te****@****.com), and severity (critical for financial/ID data, major for contact data, minor for IP addresses).

Step 2 — Apply verdict logic

ConditionVerdict
Any findingNO_COMMIT
No findingsCOMMIT

Detection Checklist

T1 — Email Addresses (Major)

  • Any string matching [text]@[domain].[tld] pattern

T2 — Phone Numbers (Major)

  • International format: +[country code][number]

T3 — National ID / SSN (Critical)

  • US SSN: three digits, two digits, four digits pattern
  • National ID formats for other countries in ID context

T4 — Bank Card PANs (Critical)

  • 13-19 digit sequences matching major card network prefixes, passing a Luhn checksum

T5 — IBANs (Critical)

  • Two-letter country code + two check digits + up to 30 alphanumeric characters

T6 — Crypto Wallet Addresses (Major)

  • Bitcoin: Base58 strings of 25-34 chars starting with 1, 3, or bc1
  • Ethereum: 42-char hex strings starting with 0x

T7 — IP Addresses (Minor)

  • IPv4: four octets separated by dots
  • IPv6: eight groups of hex digits separated by colons

T8 — Passport / Document Numbers (Critical)

  • Alphanumeric strings of 6-9 characters in explicit passport/document-number context

DCL Sentinel Trace vs DCL Secret Leak Detector

These two skills are complementary, not competing. Run both.

DCL Sentinel TraceDCL Secret Leak Detector
FocusPersonal identity dataTechnical credentials
CatchesEmails, phones, national IDs, IBANs, card PANsAPI keys, tokens, private keys, DB URLs
Primary riskPrivacy breachSecurity breach / credential compromise
Live tooldcl_evaluate_pii ($0.02)dcl_evaluate_secrets ($0.02)

A response can be free of credentials and still expose personal data. Both checks are necessary for complete output coverage.


Where Sentinel Trace fits in the DCL pipeline

Untrusted input
        │
        ▼
DCL Prompt Firewall        ← blocks malicious input
        │ COMMIT
        ▼
      LLM
        │
        ▼
DCL Policy Enforcer        ← policy check on output
        │ COMMIT
        ▼
DCL Sentinel Trace         ← this skill — PII redaction
        │ COMMIT
        ▼
DCL Secret Leak Detector   ← credential scan
        │ COMMIT
        ▼
DCL Semantic Drift Guard   ← hallucination check
        │ IN_COMMIT
        ▼
Safe to deliver

Privacy & Data Policy

Operated by Fronesis Labs. The free checklist runs 100% instruction-only — no network requests, no content transmitted anywhere. For the live tool: only a hash of the scanned text (input_hash) and finding metadata are written to the on-chain audit trail; raw text and detected personal data are never stored server-side. Only redacted samples ever appear in output.

Full policy: https://fronesislabs.com/#privacy · Questions: support@fronesislabs.com


  • dcl-secret-leak-detector — Credential and API key scan
  • dcl-prompt-firewall — Input-layer injection and jailbreak detection
  • dcl-policy-enforcer — Policy and jailbreak detection for AI outputs
  • dcl-semantic-drift-guard — Hallucination and grounding check

Leibniz Layer™ · Fronesis Labs · fronesislabs.com

Questions people ask

What is the difference between the free and live modes?
The free mode runs the detection checklist entirely inside the agent's context with no network call. The live mode calls `dcl_evaluate_pii` for $0.02 per scan and returns a cryptographic tx_hash seal anchored on Base via x402.
Does the server store the scanned text?
No. Only a hash of the input and finding metadata are written to the audit chain; the raw text and detected PII are never stored, and any redacted sample exposes only its first 2 and last 4 characters.
Which PII categories are checked and how are they scored?
Eight categories: email (major), international phone (major), SSN / national ID (critical), bank card PAN with Luhn check (critical), IBAN (critical), Bitcoin / Ethereum wallet addresses (major), IPv4 and IPv6 (minor), and passport numbers only when they appear in explicit passport context (critical). Any finding returns a NO_COMMIT verdict.

Related skills

Scan agent outputs and pipeline data for exposed API keys, tokens, and credentials before they reach users or logs.

16 installs

Get a verdict, confidence score, and on-chain tx_hash for LLM or agent output via a paid x402 MCP audit.

18 installs

Pre-execution injection and jailbreak screening with paid x402 settlement and hash-chained audit.

18 installs

Redact PII from text before sending it to an LLM, via a single HTTPS POST — pay per request on Solana or use the 50-request TRIAL.

29 installs1 stars