SECOPS

Cloudflare Bot ASN Anomaly Hunter with Auto-Quarantine

Scans Cloudflare access logs every 10 minutes for ASNs generating abnormal request volume or error rates, blocks the worst offenders via a firewall rule.

CategorySecOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 10 minutes
  • ActionQuery per-ASN request and error ratesAxiom
  • LogicFlag ASNs exceeding baseline
  • ActionAdd offender ASNs to Cloudflare block listCloudflareCloudflare
  • OutputOpen Linear evidence ticketLinearLinear

What it does

This workflow continuously hunts for malicious bot traffic in your Cloudflare logs. It pulls recent HTTP events from Axiom, groups them by source ASN, and flags any network whose request rate or 4xx/5xx ratio spikes far above its own rolling baseline. Confirmed offenders get dropped into a Cloudflare IP-list block rule automatically, and a Linear ticket is filed so a human can review the evidence and decide whether to keep or lift the block.

When to use it

Run this when you are getting hammered by credential-stuffing, scraping, or layer-7 floods that rotate IPs but stay within a handful of hosting ASNs. It is built for teams who want fast, evidence-backed mitigation without paging a human for every blip.

How it works

  1. 1A 10-minute schedule fires the hunt.
  2. 2Axiom runs a grouped query over the last hour of Cloudflare logs, returning per-ASN request counts and error ratios.
  3. 3A logic step compares each ASN to its 7-day baseline and keeps only those exceeding the anomaly threshold.
  4. 4For each flagged ASN, Cloudflare adds it to the managed block list.
  5. 5A Linear issue is opened with the ASN, sample paths, and the exact Axiom query as evidence.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  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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