IT OPS

Cloudflare WAF Incident Rollback Investigator

A CEO-driven agent that, when a WAF incident is declared, gathers recent rule changes and Axiom block logs, reasons about the likely culprit rule.

CategoryIT Ops
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWAF incident declaredHTTP webhook
  • ActionFetch recent ruleset change historyCloudflareCloudflare
  • ActionQuery Axiom for block pattern and timingAxiom
  • LogicCorrelate evidence to culprit rule
  • ActionPost rollback proposal for approvalSlack
  • OutputExecute approved rollback in CloudflareCloudflareCloudflare

What it does

This is an agent-driven investigator for live WAF incidents. Instead of a fixed pipeline, the CEO agent pulls recent Cloudflare ruleset history and Axiom traffic logs, correlates the blocked-traffic pattern to a specific rule change, and writes up a recommended rollback with its reasoning.

When to use it

Use it during a suspected WAF-caused outage when you need fast triage but still want a human to authorize the revert. The agent does the correlation legwork; the Chairman makes the call.

How it works

  1. 1An incident webhook declares a suspected WAF problem with the affected zone.
  2. 2The agent fetches recent ruleset change history from Cloudflare.
  3. 3The agent queries Axiom for the blocked-request pattern and timing around each change.
  4. 4It reasons over the evidence to name the most likely culprit rule and a precise rollback target.
  5. 5The proposed rollback plus supporting evidence is posted to Slack for Chairman approval.
  6. 6On approval, the agent executes the rollback against Cloudflare and confirms in-thread.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  3. 3
    Connect AxiomLog streams, queries, dashboards.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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