Your WAF Is Either Blocking Real Users or Missing Real Attacks

Generic WAF rule sets are built to catch common attack signatures across every kind of application at once, which means they're tuned toward false positives on anything unusual, a rich text editor that legitimately submits HTML-like content, a search field where a user pastes a chunk of code, a webhook receiver with deliberately unusual payloads. Running default rules in blocking mode from day one, without first understanding what your own traffic actually looks like, is the most common reason WAF rollouts get quietly disabled a month later.

Run new rules in a log-only, detection mode against real production traffic for at least a week before switching any of them to block, and review what would have been blocked. This surfaces every legitimate traffic pattern the generic rules misclassify as an attack before it becomes a support ticket, and gives you a concrete, evidence-based list of exceptions to write rather than guessing at them in advance.

The tempting fix for a false positive is to disable the entire rule category it came from, which quietly removes real protection along with the false positive. Write a narrow exception instead, scoped to the specific route, parameter, and pattern that triggered it, so the rule keeps protecting every other path in your application. This takes more upfront effort per exception but avoids the slow erosion where a WAF that started strict ends up with entire categories disabled and effectively useless.

• SQL injection and command injection patterns: the highest-confidence, lowest-false-positive category for most applications, and worth blocking early.
• Known bad IP reputation and bot signatures: blocking traffic from sources with an established pattern of abuse carries little risk to legitimate users.
• Rate-based rules on sensitive endpoints: login, password reset, and checkout specifically, where a burst of requests is a strong signal regardless of payload content.
• Generic XSS pattern matching: genuinely useful, but tune it against your own forms specifically before blocking, since this category produces the most false positives on rich content fields.

Start with the first two, which carry the least risk of blocking real users, before moving to the more application-specific categories.

A WAF operates at the edge, inspecting requests before they reach your application; a platform like CrowdStrike adds visibility at the runtime and endpoint layer, catching what got past the edge or originated from inside your own infrastructure. Pairing edge filtering with runtime visibility closes a real gap: a WAF alone can't tell you whether a request that looked legitimate at the edge went on to trigger unusual behavior once it reached your application code, which is exactly the kind of signal that catches an attack the WAF's pattern matching missed. If you're still weighing options for that layer, this comparison of endpoint security platforms is worth reading first.

A WAF tuned carefully at launch drifts out of sync with your application as new features ship, new form fields get added, and traffic patterns change. Set a recurring review, monthly is reasonable for most teams, to check for new false positives introduced by recent releases and to confirm the highest-priority rule categories are still catching what they're meant to catch. Treat the WAF as a living part of the deployment pipeline that needs the same ongoing attention as any other production system, not a one-time configuration task that's finished once it goes live.