Turning audit logs into active security tools with real-time monitoring
Learn how to implement real-time monitoring and alerting on audit logs to detect security threats, anomalies, and compliance violations as they occur.
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Audit logs are valuable for compliance and post-incident investigation, but their real power comes from real-time monitoring. By analysing audit logs as events occur, you can detect security threats, anomalies, and compliance violations immediately—before they cause significant damage. Let's explore how to implement effective real-time monitoring of audit logs.
Real-time monitoring enables early detection of threats:
Many compliance frameworks require monitoring:
Real-time monitoring provides operational insights:
Not all audit events need real-time monitoring. Focus on security-significant events:
Monitor authentication attempts:
Monitor access control:
Monitor access to sensitive data:
Monitor administrative activities:
Monitor security-relevant events:
Different types of threats require different monitoring patterns:
Alert when a metric exceeds a threshold:
// Alert on multiple failed logins
if (failedLoginAttempts(userId, lastHour) > 5) {
alert('Possible brute force attack', {
userId,
attempts: failedLoginAttempts(userId, lastHour),
timeframe: '1 hour'
});
}
// Alert on bulk data access
if (recordsAccessed(userId, lastMinute) > 1000) {
alert('Unusual bulk data access', {
userId,
records: recordsAccessed(userId, lastMinute),
timeframe: '1 minute'
});
}
Detect specific patterns of events:
// Detect privilege escalation pattern
const pattern = [
{ action: 'login', success: true },
{ action: 'access', resource: 'admin_panel', success: false },
{ action: 'request_privilege', success: true },
{ action: 'access', resource: 'admin_panel', success: true }
];
if (detectPattern(userId, pattern, lastHour)) {
alert('Possible privilege escalation', { userId, pattern });
}
Detect deviations from normal behavior:
// Detect unusual access times
const userNormalHours = getUserNormalHours(userId);
const currentHour = new Date().getHours();
if (!isWithinNormalHours(currentHour, userNormalHours)) {
alert('Unusual access time', {
userId,
currentHour,
normalHours: userNormalHours
});
}
// Detect unusual data access volumes
const normalVolume = getUserNormalDataAccessVolume(userId);
const currentVolume = dataAccessVolume(userId, lastHour);
if (currentVolume > normalVolume * 3) {
alert('Unusual data access volume', {
userId,
currentVolume,
normalVolume
});
}
Correlate events across time or systems:
// Detect coordinated attack
const failedLogins = getFailedLogins(lastHour);
const uniqueIPs = new Set(failedLogins.map((e) => e.ip_address));
if (uniqueIPs.size > 10 && failedLogins.length > 50) {
alert('Possible distributed brute force attack', {
uniqueIPs: uniqueIPs.size,
totalAttempts: failedLogins.length
});
}
Process events as they're ingested:
// Event stream processor
eventStream.subscribe(async (event) => {
// Check thresholds
await checkThresholds(event);
// Detect patterns
await detectPatterns(event);
// Detect anomalies
await detectAnomalies(event);
// Correlate events
await correlateEvents(event);
});
Pros: Real-time, low latency Cons: Requires stream processing infrastructure
Periodically query recent events:
// Run every minute
setInterval(async () => {
const recentEvents = await auditLog.query({
start_time: minutesAgo(5),
end_time: new Date()
});
// Analyse events
await analyseEvents(recentEvents);
}, 60000);
Pros: Simple, works with any storage system Cons: Not truly real-time, might miss rapid events
Use database triggers to detect events:
CREATE TRIGGER audit_event_trigger
AFTER INSERT ON audit_events
FOR EACH ROW
BEGIN
-- Check for suspicious patterns
CALL check_suspicious_pattern(NEW);
END;
Pros: Automatic, no application code needed Cons: Limited to database capabilities, harder to maintain
Use a dedicated monitoring service:
// Send events to monitoring service
await monitoringService.ingest(event);
// Service handles all monitoring logic
// Returns alerts if thresholds exceeded
Pros: Separation of concerns, scalable Cons: Additional service to manage
const rule = {
name: 'Multiple Failed Logins',
condition: (events) => {
const failedLogins = events.filter(
(e) => e.action === 'login' && e.success === false
);
return failedLogins.length > 5;
},
window: '1 hour',
alert: {
severity: 'high',
message: 'Multiple failed login attempts detected'
}
};
const rule = {
name: 'Unusual Data Access Volume',
condition: (events) => {
const dataAccess = events.filter(
(e) => e.action === 'read' && e.resource.type === 'customer'
);
return dataAccess.length > 1000;
},
window: '1 minute',
alert: {
severity: 'medium',
message: 'Unusual bulk data access detected'
}
};
const rule = {
name: 'Privilege Escalation',
condition: (events) => {
const privilegeChanges = events.filter(
(e) => e.action === 'grant_permission' || e.action === 'change_role'
);
return privilegeChanges.length > 0;
},
window: '1 hour',
alert: {
severity: 'high',
message: 'Privilege escalation detected'
}
};
Define severity levels for different types of alerts:
Use multiple alert channels:
Prevent alert fatigue:
Real-time monitoring can impact performance:
Process events asynchronously to avoid blocking:
// Don't block event ingestion
eventQueue.enqueue(event);
// Process in background
eventProcessor.processQueue();
Use efficient storage for monitoring data:
For very high-volume events, consider sampling:
if (shouldSample(event)) {
await processEvent(event);
}
Begin with simple threshold-based monitoring, then add complexity:
Adjust thresholds based on actual patterns:
Regularly test that monitoring works:
Document monitoring rules:
Regularly review alerts and monitoring effectiveness:
Don't try to monitor every event—focus on security-significant events.
False positives reduce trust in monitoring. Tune rules to minimise them.
Test your monitoring regularly. Broken monitoring is worse than no monitoring.
Too many alerts lead to ignored alerts. Tune thresholds and group alerts.
Monitoring is useless without a response plan. Define how to respond to each type of alert.
Real-time monitoring of audit logs transforms them from compliance records into active security tools. By detecting threats as they happen, you can respond faster, reduce impact, and prevent incidents from becoming breaches.
Start with simple threshold-based monitoring for critical events like failed logins and bulk data access. As you gain experience, add pattern detection, anomaly detection, and correlation. Remember to tune thresholds, test regularly, and have response plans for each type of alert.
The goal isn't to monitor everything—it's to monitor the right things effectively. Focus on security-significant events, tune your rules to minimise false positives, and ensure you can respond quickly when alerts fire.
With effective real-time monitoring, audit logs become a powerful security tool that helps you detect and respond to threats before they cause significant damage.