ENGINEERING

CVE Exposure-Based Pager Escalation

On a published CVE for a watched package, this determines whether any internet-facing or production service is exposed.

CategoryEngineering
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCVE webhook for a watched package
  • ActionResolve vulnerable repos and map to service exposure metadataGitHubGitHub
  • LogicBranch on exposure: production/edge = high, internal/dev = low
  • ActionOpen a PagerDuty incident for high-exposure matchesPagerDutyPagerDuty
  • OutputLog low-exposure matches as a tracked Datadog eventDatadogDatadog

What it does

Stops CVE alert fatigue by escalating based on actual exposure rather than mere presence. It checks whether the affected package version runs in any production or internet-facing service, and reserves a page for those cases while quietly logging the rest.

When to use it

Use it when your team gets paged for every advisory regardless of reachability and has started ignoring them. This makes the page mean something again by gating it on real production exposure.

How it works

  1. 1A CVE webhook for a watched package triggers the run.
  2. 2The flow queries which GitHub repos pin a vulnerable version and which of those map to production or edge-exposed services via service metadata.
  3. 3A severity branch evaluates exposure: production or internet-facing match is high; internal-only or dev is low.
  4. 4High-severity matches trigger a PagerDuty incident with the affected services and fixed version attached.
  5. 5Low-severity matches are recorded as a Datadog event so they stay tracked without waking anyone.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect PagerDutyIncidents, on-call, escalations.
  3. 3
    Connect DatadogMetrics, traces, log search.
  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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