Anomaly Detection is the automated identification of patterns in API usage that deviate significantly from established baselines.
Anomaly Detection
Anomaly Detection is the automated identification of patterns in API usage that deviate significantly from established baselines.
Why It Matters
The average time to detect a breach is 258 days (IBM 2024). Anomaly detection dramatically reduces this window by flagging suspicious patterns — unusual request volumes, new IP addresses, off-hours activity — in real time.
How It Works
The system establishes baselines for normal API usage per token/user, then monitors incoming requests against these baselines. Statistical methods or ML models flag deviations — such as a 10x spike in requests, a request from a new country, or calls to previously unused endpoints.
Best Practices
- Establish baselines during normal operation before enabling alerts
- Tune thresholds to minimize false positives
- Combine multiple signals (volume, geography, timing) for higher accuracy
- Integrate alerts with incident response workflows
Common Mistakes
- Setting thresholds so low that alert fatigue sets in
- Only monitoring request volume without geographic or temporal analysis
- Not updating baselines as legitimate usage patterns evolve
How ShieldKey Helps
ShieldKey's Anomaly Detection monitors every proxied request and alerts on unusual patterns — volume spikes, new IPs, geographic shifts — giving you real-time visibility into potential credential misuse.
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How does anomaly detection prevent breaches?
Anomaly detection doesn't prevent breaches directly — it detects them faster. By flagging unusual API usage patterns in real time, it allows teams to revoke compromised credentials before significant damage occurs.