Implement Fireflies.ai PII handling, data retention, and GDPR/CCPA compliance patterns. Use when handling sensitive data, implementing data redaction, configuring retention policies, or ensuring compliance with privacy regulations for Fireflies.ai integrations. Trigger with phrases like "fireflies data", "fireflies PII", "fireflies GDPR", "fireflies data retention", "fireflies privacy", "fireflies CCPA".
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
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skills listSkill Instructions
name: fireflies-data-handling description: | Implement Fireflies.ai PII handling, data retention, and GDPR/CCPA compliance patterns. Use when handling sensitive data, implementing data redaction, configuring retention policies, or ensuring compliance with privacy regulations for Fireflies.ai integrations. Trigger with phrases like "fireflies data", "fireflies PII", "fireflies GDPR", "fireflies data retention", "fireflies privacy", "fireflies CCPA". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Fireflies.ai Data Handling
Overview
Handle sensitive data correctly when integrating with Fireflies.ai.
Prerequisites
- Understanding of GDPR/CCPA requirements
- Fireflies.ai SDK with data export capabilities
- Database for audit logging
- Scheduled job infrastructure for cleanup
Data Classification
| Category | Examples | Handling |
|---|---|---|
| PII | Email, name, phone | Encrypt, minimize |
| Sensitive | API keys, tokens | Never log, rotate |
| Business | Usage metrics | Aggregate when possible |
| Public | Product names | Standard handling |
PII Detection
const PII_PATTERNS = [
{ type: 'email', regex: /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/g },
{ type: 'phone', regex: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g },
{ type: 'ssn', regex: /\b\d{3}-\d{2}-\d{4}\b/g },
{ type: 'credit_card', regex: /\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b/g },
];
function detectPII(text: string): { type: string; match: string }[] {
const findings: { type: string; match: string }[] = [];
for (const pattern of PII_PATTERNS) {
const matches = text.matchAll(pattern.regex);
for (const match of matches) {
findings.push({ type: pattern.type, match: match[0] });
}
}
return findings;
}
Data Redaction
function redactPII(data: Record<string, any>): Record<string, any> {
const sensitiveFields = ['email', 'phone', 'ssn', 'password', 'apiKey'];
const redacted = { ...data };
for (const field of sensitiveFields) {
if (redacted[field]) {
redacted[field] = '[REDACTED]';
}
}
return redacted;
}
// Use in logging
console.log('Fireflies.ai request:', redactPII(requestData));
Data Retention Policy
Retention Periods
| Data Type | Retention | Reason |
|---|---|---|
| API logs | 30 days | Debugging |
| Error logs | 90 days | Root cause analysis |
| Audit logs | 7 years | Compliance |
| PII | Until deletion request | GDPR/CCPA |
Automatic Cleanup
async function cleanupFireflies.aiData(retentionDays: number): Promise<void> {
const cutoff = new Date();
cutoff.setDate(cutoff.getDate() - retentionDays);
await db.firefliesLogs.deleteMany({
createdAt: { $lt: cutoff },
type: { $nin: ['audit', 'compliance'] },
});
}
// Schedule daily cleanup
cron.schedule('0 3 * * *', () => cleanupFireflies.aiData(30));
GDPR/CCPA Compliance
Data Subject Access Request (DSAR)
async function exportUserData(userId: string): Promise<DataExport> {
const firefliesData = await firefliesClient.getUserData(userId);
return {
source: 'Fireflies.ai',
exportedAt: new Date().toISOString(),
data: {
profile: firefliesData.profile,
activities: firefliesData.activities,
// Include all user-related data
},
};
}
Right to Deletion
async function deleteUserData(userId: string): Promise<DeletionResult> {
// 1. Delete from Fireflies.ai
await firefliesClient.deleteUser(userId);
// 2. Delete local copies
await db.firefliesUserCache.deleteMany({ userId });
// 3. Audit log (required to keep)
await auditLog.record({
action: 'GDPR_DELETION',
userId,
service: 'fireflies',
timestamp: new Date(),
});
return { success: true, deletedAt: new Date() };
}
Data Minimization
// Only request needed fields
const user = await firefliesClient.getUser(userId, {
fields: ['id', 'name'], // Not email, phone, address
});
// Don't store unnecessary data
const cacheData = {
id: user.id,
name: user.name,
// Omit sensitive fields
};
Instructions
Step 1: Classify Data
Categorize all Fireflies.ai data by sensitivity level.
Step 2: Implement PII Detection
Add regex patterns to detect sensitive data in logs.
Step 3: Configure Redaction
Apply redaction to sensitive fields before logging.
Step 4: Set Up Retention
Configure automatic cleanup with appropriate retention periods.
Output
- Data classification documented
- PII detection implemented
- Redaction in logging active
- Retention policy enforced
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| PII in logs | Missing redaction | Wrap logging with redact |
| Deletion failed | Data locked | Check dependencies |
| Export incomplete | Timeout | Increase batch size |
| Audit gap | Missing entries | Review log pipeline |
Examples
Quick PII Scan
const findings = detectPII(JSON.stringify(userData));
if (findings.length > 0) {
console.warn(`PII detected: ${findings.map(f => f.type).join(', ')}`);
}
Redact Before Logging
const safeData = redactPII(apiResponse);
logger.info('Fireflies.ai response:', safeData);
GDPR Data Export
const userExport = await exportUserData('user-123');
await sendToUser(userExport);
Resources
Next Steps
For enterprise access control, see fireflies-enterprise-rbac.
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