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TacticB3likely · low confidenceRU · adversary

Russian KCPN publishes interview on counter-Geran tactics

Bottom line

Russian KCPN publishes interview with Ukrainian Darknode battalion head on counter-Geran tactics.

Why it matters

Offers valuable intelligence on Ukrainian counter-drone tactics and organizational challenges, which can inform NATO and Ukrainian defense strategies.

Russian KCPN published an interview with Alexander Yarmak, head of Ukrainian Darknode battalion (412th Nemesis Brigade), discussing R&D pains, small air defense organization, and counter-Geran tactics. This provides insight into Ukrainian challenges and tactics against Russian Geran drones.

Evidence — 1 independent origin

  • Беспилотники (дроны, БПЛА, UAV)source Borigin t.me
    Original text (excerpt)

    «Мы устали от новаторских дронов, которые не решают реальных проблем». Darknode и R&D на фронте. Мысли врага. Видеоверсия Некоторое время назад Аналитический центр КЦПН публиковал перевод очень интересной одноимённой статьи врага, написанной на основе интервью с Александром Ярмак

NamedDarknodeAlexander Yarmak412th Nemesis BrigadeGeranTopicsdroneselectronic warfareanalysis

Related findings

← Latest findings · All findings from September 2026

History · version 1 · first published · last substantive update

Cite this finding
Robot War (2026). Russian KCPN publishes interview on counter-Geran tactics. Hetzner OSINT, 9 September 2026. https://robotwar.io/osint-hetzner/2026-09-09--russian-kcpn-publishes-interview-on-counter-geran-tactics/

@misc{robotwar-2026-09-09--russian-kcpn-publishes-interview-on-counter-geran-tactics,
  title = {Russian KCPN publishes interview on counter-Geran tactics},
  author = {Robot War},
  howpublished = {\url{https://robotwar.io/osint-hetzner/2026-09-09--russian-kcpn-publishes-interview-on-counter-geran-tactics/}},
  year = {2026},
  note = {Hetzner OSINT finding B3}
}

Grades: source reliability A–F from the channel register; information credibility 1–6 from independent origins — reposts count once. The bottom line and summary are written by the model from the cited posts; grades and source roles are rule-based. Methodology 2026-10-15.v6 · Corrections · JSON · RSS · API performance