SECOPS

Daily Lookalike Domain Sweep into Linear

Runs a scheduled Brave Search sweep for typosquat and lookalike variants of your brand, scores each hit for impersonation risk.

CategorySecOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires the sweep
  • ActionBrave Search for lookalike domain permutationsBraveBrave Search
  • LogicScore impersonation risk and drop known/low-risk hits
  • ActionCreate a triage ticket per candidate in LinearLinearLinear
  • OutputPost run summary to SlackSlack

What it does

Every morning this workflow hunts the open web for domains that imitate your brand — common typos, character swaps, and added keywords like "login" or "support" — then turns the suspicious ones into actionable Linear tickets so your secops team can start takedown prep.

When to use it

Use it when you want continuous, hands-off monitoring for brand-impersonation domains without a paid threat-intel feed. Ideal for security teams that already triage work in Linear and want a steady, deduplicated queue rather than noisy alerts.

How it works

  1. 1A daily schedule fires the run at a fixed hour.
  2. 2A Brave Search action queries a generated list of lookalike permutations of your brand name and domain.
  3. 3A logic step scores each result on signals like edit distance to your real domain, presence of phishing keywords, and recency, then filters out low-risk and already-known hits.
  4. 4For each surviving candidate, a Linear action creates a ticket pre-filled with the domain, risk score, and evidence snippet.
  5. 5The output posts a one-line run summary so the team knows the sweep completed and how many tickets were opened.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Brave SearchWeb, news, image, video search.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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