glean-data-handling

v2026.09.24

PII filtering: strip emails, phone numbers, SSNs from document body before indexing. Trigger: "glean data handling", "data-handling".

GitHub
安装命令
npx skhub add jeremylongshore/glean-data-handling
Markdown
SKILL.md

Glean Data Handling

Overview

Glean enterprise search ingests documents from dozens of connectors (Google Drive, Confluence, Slack, Jira, Salesforce, etc.) and builds a unified search index with permission-aware access control. Data types include indexed document content, connector metadata, user permission maps, query logs, and search analytics. All document content must be PII-filtered before indexing, permission boundaries must be preserved to prevent data leakage across teams, and retention policies must be enforced to comply with corporate governance and GDPR/CCPA obligations.

Data Classification

Data TypeSensitivityRetentionEncryption
Indexed document contentHigh (may contain PII)Per source retention policyAES-256 at rest
User permission mapsHigh (access control)Sync lifecycleTLS + at rest
Connector metadataMediumUntil connector removedAES-256 at rest
Search query logsMedium (reveals intent)90 days defaultAES-256 at rest
Search analytics/aggregatesLow1 yearTLS in transit

Data Import

interface GleanDocument {
  id: string; datasource: string; title: string;
  body: string; permissions: { allowedUsers?: string[]; allowAnonymousAccess?: boolean };
  updatedAt: string; url: string;
}

async function indexDocuments(docs: GleanDocument[], datasource: string) {
  // PII strip before indexing
  const sanitized = docs.map(doc => ({
    ...doc,
    body: stripPII(doc.body),
  }));
  // Batch upload with pagination (max 100 per request)
  for (let i = 0; i < sanitized.length; i += 100) {
    const batch = sanitized.slice(i, i + 100);
    await fetch(`https://customer-be.glean.com/api/index/v1/bulkindexdocuments`, {
      method: 'POST',
      headers: { Authorization: `Bearer ${process.env.GLEAN_INDEXING_TOKEN}`, 'Content-Type': 'application/json' },
      body: JSON.stringify({ datasource, documents: batch }),
    });
  }
}

function stripPII(text: string): string {
  return text
    .replace(/\b[\w.+-]+@[\w-]+\.[\w.]+\b/g, '[EMAIL_REDACTED]')
    .replace(/\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g, '[PHONE_REDACTED]')
    .replace(/\b\d{3}-\d{2}-\d{4}\b/g, '[SSN_REDACTED]');
}

Data Export

async function exportSearchAnalytics(startDate: string, endDate: string) {
  const res = await fetch(`https://customer-be.glean.com/api/v1/analytics`, {
    method: 'POST',
    headers: { Authorization: `Bearer ${process.env.GLEAN_API_TOKEN}`, 'Content-Type': 'application/json' },
    body: JSON.stringify({ startDate, endDate, metrics: ['query_count', 'click_through', 'zero_results'] }),
  });
  const data = await res.json();
  // Redact user identifiers from analytics export
  return data.results.map((r: any) => ({ ...r, userId: undefined, query: r.query?.length > 3 ? r.query : '[SHORT_QUERY_REDACTED]' }));
}

Data Validation

function validateDocument(doc: GleanDocument): string[] {
  const errors: string[] = [];
  if (!doc.id || doc.id.length > 512) errors.push('Invalid document ID');
  if (!doc.datasource) errors.push('Missing datasource identifier');
  if (!doc.title || doc.title.length > 1000) errors.push('Title missing or exceeds 1000 chars');
  if (!doc.body || doc.body.length === 0) errors.push('Empty document body');
  if (!doc.permissions) errors.push('Missing permissions — defaults to deny-all');
  if (doc.updatedAt && isNaN(Date.parse(doc.updatedAt))) errors.push('Invalid updatedAt timestamp');
  return errors;
}

Compliance

  • PII stripped from document body before indexing (emails, phones, SSNs)
  • Permission boundaries enforced: allowedUsers scope matches source system ACLs
  • Connector credentials stored in secret manager, rotated quarterly
  • Search query logs retained max 90 days, purged via automated job
  • GDPR right-to-erasure: delete all indexed content referencing a specific user on request
  • CCPA: honor do-not-sell signals for search analytics data
  • SOC 2 Type II audit trail for all indexing and deletion operations

Error Handling

IssueCauseFix
403 on bulk indexExpired or insufficient indexing tokenRotate token, verify datasource permissions
Permission mismatch in searchStale ACL sync from connectorForce re-sync connector permissions via admin API
PII detected in indexed contentNew PII pattern not in strip regexAdd pattern to stripPII, re-index affected datasource
Zero-result queries spikeConnector sync failure, stale indexCheck connector health dashboard, trigger manual re-crawl
Rate limit 429 on indexingBatch size too large or too frequentReduce batch to 50 docs, add 500ms delay between batches

Prerequisites

  • A documented data owner and approved classification/retention policy for the source being indexed.
  • A non-production sample containing fictitious identities, plus an allowlisted destination and credentials scoped only to that datasource.
  • A reviewed redaction and deletion plan; pattern matching is a safeguard, not proof that sensitive data is absent.

Instructions

  1. Inventory fields and source ACLs before indexing; default any unknown permission or classification to deny and quarantine the record.
  2. Run redaction and schema validation on a bounded staging batch, logging only record counts, rule versions, and opaque document identifiers.
  3. Compare source and proposed index ACLs for both an allowed and denied test principal before approving a production batch.
  4. Send idempotent, bounded batches to the approved datasource and retain a reversible manifest of submitted opaque IDs and timestamps.
  5. On a failed validation, stop the batch, delete only the staged artifacts, and escalate to the data owner rather than weakening redaction or ACL rules.

Output

Return a handling receipt with source classification, approved destination, policy and redaction-rule versions, input/accepted/quarantined counts, ACL comparison result, retention date, and deletion or rollback reference. Do not emit bodies, queries, emails, phone numbers, or access tokens.

Examples

Example receipt: source=staging-wiki; classification=confidential; accepted=96; quarantined=4; acl_probe=allow+deny pass; retention=2026-10-01; redaction_rules=v3. The sample is fictional and identifies no employee or document.

Resources

Next Steps

See glean-security-basics.

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最新版本元数据

版本

v2026.09.24

发布时间

Sep 24, 2026

分类

未分类

许可证

MIT

源路径

skills/.curated/glean-data-handling

默认分支

main

最新提交

e5a6c3b

Tree SHA

c2dc8e8