How to Monitor WAF Logs?

A WAF generates a record for every request it inspects, and that record usually includes the client IP, the rule ID that fired, the action taken, and the specific field that triggered a match, whether that’s a header, a query parameter, or the request body. Most teams turn on logging once during setup and never look at it again until something breaks. That’s the gap this guide addresses: a practical routine for actually reading these logs and catching problems before they turn into incidents.

How Do You Set Up a Practical WAF Log Monitoring Routine?

Step 1: Get Logs Into One Place

ModSecurity writes to audit.log locally by default, AWS WAF pushes to CloudWatch Logs or an S3 bucket depending on how logging is configured, and Cloudflare exposes events through its Security Events dashboard or the GraphQL Analytics API. Pick one destination and route everything there, whether that’s Splunk, an ELK stack, or a cloud-native tool like CloudWatch Logs Insights. Checking three different dashboards for one incident wastes time you don’t have during an active attack.

Step 2: Parse the Fields That Actually Matter

Raw WAF logs are dense. On AWS WAF, the JSON payload includes httpRequest.clientIp, action, terminatingRuleId, and ruleGroupList for managed rule matches. On ModSecurity, the audit log’s Section H gives you the matched rule ID and the specific variable it triggered on. Write a jq filter or a saved search that pulls just these fields so a daily scan takes minutes instead of an hour of scrolling.

Step 3: Split Blocked Traffic From Allowed Traffic

Blocked requests tell you what your rules have already caught. Allowed requests matter here too, especially the ones that picked up a low anomaly score but didn’t get blocked. Those are usually the ones slipping through. If you’re running ModSecurity in anomaly scoring mode, examine requests sitting just below your block threshold. That’s usually where a rule needs tightening before an actual bypass happens.

Step 4: Flag Repeat Source IPs

Group blocked events by clientIp over a rolling window, an hour or a day depending on traffic volume. An IP hitting the same login endpoint 200 times in ten minutes is a credential-stuffing attempt, not a coincidence. Cloudflare’s dashboard does this grouping automatically under Security Events; on a self-hosted ModSecurity setup, a simple awk and sort | uniq -c on the audit log provides you the same result.

Related Read: How to Create Custom WAF Rules?

Step 5: Monitor Rule Hit Counts Regularly

Pull a count of matches per ruleId over the past 30 days. A managed or custom rule with zero hits for months is either redundant or the traffic pattern it targeted stopped existing, which is worth reviewing either way. A sudden jump in hits from a handful to hundreds usually indicates either a new attack campaign or a legitimate traffic change that is now colliding with an overly broad condition.

Step 6: Audit False Positives From Known-Good Sources

Go through the blocked IP list and verify it against your infrastructure, monitoring tools, partner APIs, and any third-party services you connect to. A payment webhook getting blocked because its payload resembles an injection pattern is a real problem that surfaces here, not in a support ticket three days later.

Step 7: Build Alerts for the Patterns You Already Know Matter

Set a CloudWatch alarm on a sudden spike in BLOCK actions or a Cloudflare notification on a threshold breach for a specific rule. Don’t wait to catch these by manually refreshing a dashboard. The five minutes between an alert firing and someone checking it is usually the difference between stopping an attack and cleaning up after one.

Step 8: Keep Logs Long Enough to Spot Slow Attacks

Retain at least 90 days of WAF logs, longer if your compliance framework requires it. Low-and-slow scanning campaigns, the kind that send a handful of probing requests per day instead of a burst, only show up when you’re looking at data across weeks, not a single day’s export.

Key Takeaway

Logs sitting unread in a bucket don’t stop anything. Value emerges when someone actively pulls rule hit counts, checks repeat attackers, and tunes conditions based on current data rather than outdated assumptions.