SECOPS

WAF False-Positive Auto-Remediation with GitHub Rule PR

Confirms a WAF block spike is a false positive against Sentry, then drafts a tightened Cloudflare rule expression and opens a GitHub pull request with the change for review.

CategorySecOps
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook fires on suspected false-positive ruleHTTP webhook
  • ActionFetch blocked requests and URIs from CloudflareCloudflareCloudflare
  • ActionConfirm endpoints are healthy in SentrySentrySentry
  • ActionDraft tightened rule expression and rationaleOpenAI
  • OutputOpen GitHub PR with the proposed rule changeGitHubGitHub

What it does

When a Cloudflare WAF rule starts blocking legitimate traffic, this agent-driven workflow confirms the false positive by checking that the blocked endpoints have healthy Sentry traces, then drafts a narrower rule expression that stops catching the good traffic and opens a GitHub pull request against your infrastructure-as-code repo so a human approves the fix.

When to use it

Use it when your WAF rules live in version control and you want false-positive fixes proposed as reviewable diffs instead of hand-edited in the dashboard. It turns a noisy alert into a ready-to-merge change.

How it works

  1. 1A webhook fires from your alerting layer when a specific rule's false-positive signal trips.
  2. 2An action fetches the blocked requests and their URIs from Cloudflare for the affected rule.
  3. 3An action checks Sentry for those endpoints and confirms they return normal traffic with no attack signature.
  4. 4An agent step drafts a tightened rule expression scoped to exclude the legitimate pattern and writes a plain-English rationale.
  5. 5An action opens a GitHub pull request with the new expression and rationale for human review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Connect HTTP webhookTrigger any URL on agent actions.
  5. 5
    Connect OpenAIModels, embeddings, files.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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