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The Sensitive Data Protection analyzer (formerly DLP) detects personally identifiable information (PII), credentials, financial identifiers, and protected health information using Google Cloud DLP. Agnes wraps DLP behind a tenant-scoped SDP policy so you control which info types are inspected and how findings are de-identified.
Canonical namesensitive-data
Pythonsensitive_data
TypeScriptsensitiveData
Server keydlp_analyzer
CategoryData Protection

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What it detects

Google Cloud DLP recognizes ~150 built-in info types. Agnes ships five default SDP policies covering common bundles:
  • General PII — email, phone, person name, location, date of birth, IP address, URL, age.
  • Financial — credit cards, IBAN, SWIFT, U.S. bank routing / account numbers.
  • Healthcare PHI — medical record number, NPI, DEA, ICD-9 / 10, FDA codes, blood type.
  • Government IDs — SSN, passport, driver’s license, ITIN, ATIN.
  • Credentials & Secrets — auth tokens, basic-auth headers, passwords, GCP API keys, signed URLs.
You can author your own SDP policy with any combination of info types and likelihood thresholds; see SDP policies.

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How it works

The prompt is sent to the Google Cloud DLP API (projects.content.inspect or projects.content.deidentify depending on the policy). DLP returns findings — info type, likelihood, location, optionally the matched quote — and Agnes packages them into the analyzer output. Findings can optionally be de-identified in place: Agnes returns a sanitized copy of the input with the configured transformation applied (replace with [REDACTED], mask with *, replace with the info type label, fully redact, etc.).

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Parameters

KeyTypeRequiredDefaultNotes
sdp_policy_idselectNotenant defaultReference an SDP policy. Leave empty to use the tenant default.
You can also override per-request: 
{ "prompt": "...", "policy_slug": "default-inbound", "sdp_policy_id": "ph-strict" }

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Outputs and metrics

{
  "findings": [
    { "info_type": "EMAIL_ADDRESS", "likelihood": "VERY_LIKELY",
      "quote": "alice@example.com", "byte_range": { "start": 12, "end": 30 } },
    { "info_type": "US_SOCIAL_SECURITY_NUMBER", "likelihood": "LIKELY",
      "quote": "123-45-6789", "byte_range": { "start": 60, "end": 71 } }
  ],
  "deidentified_text": "Email me at [REDACTED] - SSN [REDACTED]",
  "metrics": {
    "dlp_processing_time_ms": 312.0,
    "findings_count": 2
  },
  "status": "OK"
}
MetricSuggested thresholds
findings_count> 0 (any finding), >= 3 (multiple), >= 10 (high volume).
dlp_processing_time_msObservability only; no recommended threshold.

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Termination signals

SignalWhat it matches
Boolean: has_sensitive_dataAny finding (regardless of info type).
Match: info_typeA specific info type, e.g. US_SOCIAL_SECURITY_NUMBER, EMAIL_ADDRESS, CREDIT_CARD_NUMBER.
Output match hints (regex) ship for the most common info types: EMAIL_ADDRESS, PHONE_NUMBER, CREDIT_CARD_NUMBER, US_SOCIAL_SECURITY_NUMBER, plus a wildcard .* for “any sensitive data”.

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Limits and cost

LimitValue
Max input tokens1,000,000
Requests / minute500 (per tenant)
DLP timeout30 s
Findings per request100 (DLP default)
Cost is Google Cloud DLP pricing — billed per content item inspected. See the DLP pricing page for current rates.

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Typical latency

100–3000 ms depending on input size and the number of info types inspected. Networking to DLP dominates; expect ~200 ms baseline.

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When to use it

  • Inbound and outbound. SDP is one of the highest-value analyzers to put on outbound — LLMs hallucinate plausible-looking PII (credit cards, SSNs, emails) regularly.
  • Match info types to your domain. Healthcare apps want PHI detection; fintech wants financial info types; everyone wants credential detection. Author per-product SDP policies.
  • Use replaceConfig for high-precision sanitization. Replacing with [REDACTED] keeps the LLM’s surrounding context legible while removing the leak.

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Failure modes

  • DLP API error → the analyzer status flips to ERROR and the combined run’s overall status follows.
  • Token limit exceeded → payload_too_large 413.

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