How to Monitor OpenClaw for Suspicious Activity
You can't defend against what you can't see. Comprehensive monitoring lets you detect attacks in progress, identify compromised API keys, and respond before damage occurs. This guide shows you how to enable detailed logging, set up centralized log aggregation, configure alert rules for anomalies, detect prompt injection attempts, track API key usage patterns, and build real-time security dashboards.
Why This Is Hard to Do Yourself
These are the common pitfalls that trip people up.
Log volume
OpenClaw generates massive logs. Without filtering and aggregation, finding threats is like finding needles in haystacks.
Alert fatigue
Too many false positives and teams ignore alerts. Too few and real attacks slip through.
Detecting injection
Prompt injection attempts look like normal queries. Detection requires pattern matching and anomaly detection.
Real-time vs batch
Batch analysis is too slow for active attacks. Real-time monitoring requires streaming infrastructure.
API key abuse
Stolen keys are used gradually to avoid detection. Tracking usage patterns reveals anomalies.
Step-by-Step Guide
Enable comprehensive logging
Configure OpenClaw to log security-relevant events.
# In gateway.yaml:
logging:
level: info # or debug for investigation
outputs:
- type: file
path: /app/logs/gateway.log
- type: stdout
format: json # Easier to parse
include:
- authentication_events
- rate_limit_violations
- blocked_requests
- api_key_usage
- prompt_injection_attempts
- error_responsesSet up log aggregation
Centralize logs from all OpenClaw instances.
# Using Promtail + Loki + Grafana stack:
# docker-compose.yml additions:
services:
loki:
image: grafana/loki:2.9.0
ports:
- "3100:3100"
volumes:
- ./loki-config.yaml:/etc/loki/local-config.yaml
promtail:
image: grafana/promtail:2.9.0
volumes:
- ./logs:/app/logs
- ./promtail-config.yaml:/etc/promtail/config.yml
command: -config.file=/etc/promtail/config.yml
grafana:
image: grafana/grafana:10.2.0
ports:
- "3001:3000"
environment:
- GF_SECURITY_ADMIN_PASSWORD=<CHANGE-ME-use-a-strong-password>Configure alert rules
Set up alerts for security events.
# In Loki alerting rules:
groups:
- name: openclaw-security
rules:
- alert: HighFailedAuthRate
expr: |
rate({job="openclaw"} |= "authentication failed" [5m]) > 10
annotations:
summary: "High failed auth rate detected"
- alert: PromptInjectionAttempt
expr: |
count_over_time({job="openclaw"} |= "injection attempt blocked" [1m]) > 0
annotations:
summary: "Prompt injection attempt detected"
- alert: UnusualAPIKeyUsage
expr: |
rate({job="openclaw"} |= "api_key_usage" [1h]) > 1000
annotations:
summary: "API key usage spike"Warning: Tune alert thresholds based on your normal traffic patterns. Start conservative and adjust after observing baseline behavior for 1-2 weeks.
Monitor for prompt injection patterns
Track and alert on common injection techniques.
# In gateway config, add injection detection:
injection_detection:
enabled: true
patterns:
- "ignore previous instructions"
- "ignore all prior"
- "you are now"
- "system prompt override"
- "reveal your instructions"
- "base64decode"
actions:
- log_with_severity: critical
- alert: security_team
- block_request: trueTrack API key usage per key
Detect compromised or abused keys.
# Query Loki for per-key usage:
# LogQL:
sum by (api_key) (rate({job="openclaw"} |= "api_key_usage" [1h]))
# Create dashboard panel showing:
# - Requests per key
# - Geographic distribution (if using reverse proxy with GeoIP)
# - Hourly usage patterns
# - Failed vs successful requests per keySet up real-time security dashboard
Visualize threats and metrics in Grafana.
# Grafana dashboard panels:
1. Failed authentication attempts (last 24h)
2. Rate limit violations (by IP and API key)
3. Blocked prompt injection attempts
4. API key usage heatmap
5. Error rate trend
6. Geographic request distribution
7. Response time percentiles
8. Active sessions count
# Export and import dashboard JSON via Grafana UISecurity Monitoring Is Complex
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