In the context of Tor, deanonymization attacks via traffic correlation have long been studied for both clients and onion services. Complementing prior investigations that utilize fine-grained flow metadata such as packet sizes and timings, we study a relatively less explored yet easier-to-obtain adversarial capability: deanonymization using only coarse NetFlow-style telemetry, such as one-minute, 1-out-of-1,000 sampled packet counts. We first revisit active NetFlow-based traffic analysis attacks against Tor onion services and show, through large-scale experiments with live Tor data, that coarse telemetry is sufficient to deanonymize a targeted onion service when the adversary can induce discernible traffic patterns through controlled downloads. We then introduce a stronger active attack based on controlled introduction requests, which removes application-specific assumptions and gives adversaries more flexibility while achieving comparable success rates. Finally, we present a passive deanonymization attack that sends zero traffic to target onion services. The attack exploits Tor's puzzle-based DoS defense as a side channel: public puzzle difficulty reveals service-load changes that can be semantically matched against NetFlow traces. Our findings show that coarse network telemetry poses a practical deanonymization threat to onion services today and call for proactive mitigations and a redesign of the globally visible defense signals that may leak service-load information.

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