SECOPS

Agent-driven WAF burst triage and investigation

On a WAF burst, an agent investigates by querying Cloudflare and Honeycomb, forms a hypothesis about the attack type and blast radius.

CategorySecOps
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCloudflare WAF burst triggers the agentCloudflareCloudflare
  • ActionCharacterize attack signature via Cloudflare GraphQLCloudflareCloudflare
  • ActionInspect traces and error response in HoneycombHoneycomb
  • LogicClassify attack type and estimate blast radius
  • OutputPublish triage brief to NotionNotionNotion

What it does

When a WAF burst fires, an investigative agent takes over: it queries Cloudflare for the attack signature (rule IDs, paths, methods, geographies) and queries Honeycomb for what reached origin and how the service responded. It reasons about whether this looks like credential stuffing, an L7 flood, a scanner, or a targeted exploit attempt, estimates blast radius, and writes a structured triage brief.

When to use it

Use it when you want a first-pass human-readable investigation done before an engineer even opens the dashboards, especially off-hours when context-gathering is the slow part.

How it works

  1. 1Cloudflare WAF burst triggers the agent.
  2. 2The agent calls Cloudflare GraphQL to characterize the attack signature across the burst window.
  3. 3The agent calls Honeycomb to inspect traces, latency, and error response for the targeted routes.
  4. 4A logic step has the agent classify the attack type and estimate blast radius from the gathered evidence.
  5. 5The output step publishes a triage brief to Notion with the hypothesis, evidence links, and recommended next actions.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  2. 2
    Connect HoneycombDistributed traces and queries.
  3. 3
    Connect NotionPages, databases, comments.
  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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