AI AGENTS

WAF block-spike responder from Datadog alert

When Datadog detects a sudden spike in Cloudflare WAF blocks, an agent inspects the offending rule and traffic, decides whether it's an attack or a false-positive surge.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDatadog WAF block-rate monitor firesDatadogDatadog
  • ActionFetch firewall events for the alert windowCloudflareCloudflare
  • LogicClassify attack vs false-positive surge
  • OutputPage security channel on attackSlack
  • OutputPost draft skip rule on false-positive surgeSlack

What it does

Triggers off a Datadog monitor that watches WAF block rate. On a spike it correlates the alert with live Cloudflare firewall events to determine root cause, then branches: real attacks page the security channel with context, while false-positive surges produce a draft skip rule for review.

When to use it

When deploys or marketing campaigns occasionally trip your WAF and you need fast triage that tells real threats apart from self-inflicted blocks — without a human staring at dashboards at 2am.

How it works

  1. 1A Datadog WAF block-rate monitor crosses threshold and fires a webhook into the workflow.
  2. 2The agent queries Cloudflare for the firewall events covering the alert window.
  3. 3It analyzes attacker diversity, payload signatures, and whether traffic maps to known-good clients or a single hostile source.
  4. 4A branch decides: attack vs. false-positive surge.
  5. 5If it's an attack, it posts an enriched incident summary to Slack with the top source IPs and rule IDs.
  6. 6If it's a false-positive surge, it drafts a temporary scoped skip rule and posts it to Slack for an operator to approve and stage.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DatadogMetrics, traces, log search.
  2. 2
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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