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US loses 25% of MQ-9 fleet to EW in Iran conflict

Bottom line

The Washington Post reports the US lost 45 MQ-9 Reapers, approximately 25% of its fleet, during the Iran conflict, largely due to electronic warfare link loss.

Why it matters

Highlights critical vulnerabilities in current long-range UAV resilience against advanced EW environments, underscoring the need for improved anti-jamming capabilities in future drone programs.

The Washington Post reports the US lost 45 MQ-9 Reapers, approximately 25% of its fleet, during the Iran conflict, largely due to electronic warfare link loss. The replacement CCA program drones (YFQ-44A/42A) are not yet in service, highlighting critical vulnerabilities in current long-range UAV resilience against advanced EW environments. (source: VictoryDrones-62521)

Evidence — 1 independent origin

  • Victory Dronessource Borigin t.me
    Original text (excerpt)

    ❗️ ⚡️ США потеряли уже 45 дронов MQ-9 Reaper в ходе войны с Ираном, что составляет примерно 25% от их довоенного парка, пишет The Washington Post. По словам источников издания в американской администрации, не все БПЛА были сбиты Ираном - часть беспилотников разбились из-за прерыв

NamedMQ-9 ReaperWashington PostYFQ-44AYFQ-42ACCATopicsdroneselectronic warfare

Related findings

History · version 1 · first published · last substantive update

Cite this finding 
Robot War (2026). US loses 25% of MQ-9 fleet to EW in Iran conflict. Hetzner OSINT, 15 August 2026. https://robotwar.io/osint-hetzner/2026-08-15--us-loses-25-of-mq-9-fleet-to-ew-in-iran-conflict/

@misc{robotwar-2026-08-15--us-loses-25-of-mq-9-fleet-to-ew-in-iran-conflict,
  title = {US loses 25% of MQ-9 fleet to EW in Iran conflict},
  author = {Robot War},
  howpublished = {\url{https://robotwar.io/osint-hetzner/2026-08-15--us-loses-25-of-mq-9-fleet-to-ew-in-iran-conflict/}},
  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 2026-08-18.v4 · Corrections · JSON · RSS · API performance