psyc operations cockpit model
NN-sc — Security/Control
← PSYC-MBAZAAR-1fdd1176933a786b

Worker Mesh

MalwareBazaar: unsigned elf sample — 1fdd1176933a786be5aec4814c143f4a192a32284a015bf3a28d96e6df66a3d9

Watch the case move through psyc's worker mesh — seven bots, each performing one pipeline stage and reporting its real result. The Classifier bot's severity verdict comes from the live fine-tuned model; hit ▶ replay to run it again.

how to use this view

How to use. Let the case token travel the mesh — each bot wakes, performs its stage, and reports. Press ▶ replay to run it again.

What you're seeing. Seven worker bots, one per pipeline stage. Awake bots ran for this case; asleep bots are stages that didn't apply. The Classifier bot's verdict is generated live by the fine-tuned model.

Why it matters. It makes the chain of reasoning legible — you can watch what the platform did and why, not just trust a final answer.

  1. Scout

    I sweep public feeds for fresh threat signals.

    ▸ scanning feeds…

    Scoutline ingested this signal from malware-bazaar.

    • MalwareBazaar: unsigned elf sample — 1fdd1176933a786be5aec4814c143f4a192a32284a015bf3a28d96e6df66a3d9
    • observables: 3 hashs
  2. Classifier

    I judge severity, TLP and incident type.

    ▸ assessing severity…

    Classifyline rated it medium severity, TLP:GREEN, internal class D.

    • incident type: malware
  3. Mapper

    I locate the host and its jurisdiction.

    No host to geolocate for this case.

  4. Sealer

    I encrypt evidence for authorized recipients.

    Evidence not sealed.

  5. Router

    I decide who is allowed to receive this.

    ▸ evaluating destinations…

    Routeline cleared 2 destination(s) and blocked 2 by policy.

    • ✓ MISP-Community
    • ✓ URLhaus
    • ⊘ CERT-Bund — country_mismatch
    • ⊘ AbuseIPDB — tlp_exceeded
  6. Courier

    I deliver the payload to each destination.

    Not yet submitted to any destination.

  7. Ledger

    I record every action, immutably.

    No ledger entries yet.