SECOPS

Cloudflare Daily Audit Digest with AI Triage

Each morning, pulls the prior day's Cloudflare audit log, uses an AI agent to triage and rank changes by risk.

CategorySecOps
EngineSim + Paperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery morning, pull prior 24h of Cloudflare audit entriesCloudflareCloudflare
  • ActionAI agent triages and risk-ranks each changeOpenAI
  • LogicSplit high-risk items from the rest
  • ActionFile Linear ticket per high-risk changeLinearLinear
  • ActionPost ranked digest to SlackSlack
  • OutputReturn digest and ticket IDs

What it does

Produces a once-a-day, human-readable summary of everything that changed in Cloudflare the previous day. An AI agent reviews each audit entry, scores it for risk (considering actor, action type, off-hours timing, and sensitivity of the resource), and writes a plain-English digest grouped by risk tier. Low and medium items stay in the Slack digest for awareness; only high-risk changes get a Linear ticket so the queue stays clean.

When to use it

Use this when you want daily situational awareness of Cloudflare activity without per-event alert fatigue, and you want a smart summary rather than a raw log dump.

How it works

  1. 1A morning schedule pulls the previous 24 hours of Cloudflare audit entries.
  2. 2An AI agent triages every entry, assigns a risk tier, and drafts a grouped digest with reasoning.
  3. 3A logic step splits high-risk items from the rest.
  4. 4An action files a Linear ticket for each high-risk change with the agent's rationale.
  5. 5An action posts the full ranked digest to the secops Slack channel.
  6. 6The digest and any ticket IDs are returned as output.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect LinearIssues, projects, cycles, triage.
  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.

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