A traffic analysis attack against Introduction Protocol and Onion Services

TL;DR

This paper demonstrates a practical traffic analysis attack on Tor's introduction protocol, revealing vulnerabilities in its privacy protections by identifying relay paths through intersection techniques.

Contribution

The authors present a novel intersection attack that can reliably identify relay hops in Tor's introduction circuits without payload access, exposing a privacy gap.

Findings

The attack can accurately identify relay hops with only one relay observation per stage.

Live experiments confirm the attack's effectiveness and convergence under realistic network conditions.

The study discusses implications of relay concentration and partial adversaries on attack feasibility.

Abstract

Tor onion services rely on long-lived introduction circuits to support anonymous rendezvous between clients and services. Although Tor incorporates defenses against traffic analysis, the introduction protocol retains deterministic routing structure that can be exploited by an adversary. We present a practical intersection attack against Tor introduction circuits that over repeated interactions can identify each hop from the introduction point toward the onion service while requiring observation at only one relay per stage. The attack repeatedly probes the target service and intersects sets of destination IP addresses observed within narrowly bounded INTRODUCE1-RENDEZVOUS2 intervals, without assuming global visibility or access to packet payloads. Our traffic-analysis technique identifies with certainty the next relay in the path to target at each stage, thereby revealing a gap in Tor's privacy model, which is intended to resist traffic-analysis attacks in which an adversary uses traffic patterns to determine which points in the network to observe or attack. We evaluate the attack's feasibility through live-network experiments using a self-operated onion service and relays. To support data minimization, we implement a Tor-compatible plugin that computes intersections online over pseudonymized data retained only in volatile memory. Our experiments show reliable convergence in practice, with convergence rate influenced by relay consensus weight and time-varying background traffic. We further assess practicality under a partial-global adversary model and discuss the implications of geographic concentration in Tor relay selection weight across cooperating jurisdictions.