The RKS Global report documents a two-tier Russian censorship architecture: TSPU network-layer blocking (documented by Xue et al. 2024) at the ISP level, now supplemented by mandated app-layer VPN detection in the 30 most popular Russian Android apps. This layered approach means a circumvention tool that successfully bypasses TSPU at the network layer can still be detected and reported by the app layer, closing the gap that network-only circumvention leaves open.

Russia's Ministry of Digital Development issued guidelines effective April 15, 2026 requiring popular apps to detect and restrict access from VPN-using devices. RKS Global's analysis of 30 popular Russian Android apps found that 22 of 30 implement VPN detection, and 19 of those transmit the detected VPN status to their servers. This represents a shift from network-layer blocking (TSPU) to app-layer enforcement as an additional censorship vector.

§3, §4 policy

Banking apps from major Russian institutions (Sber, T-Bank, VTB, Alfa-Bank) combine VPN detection with behavioral biometrics — screen pressure, touch coordinates, and gesture timing — enabling cross-account re-identification of users behind proxies. 11 apps received a "RED" (maximum surveillance) rating. T-Bank, Yandex services, and MAX additionally deploy active anti-analysis features that detect research tooling on the device (rooted devices, emulators, Frida, etc.).

§5, §6 detection

Simulating a shift from a 0% to 100% male dataset sample changes Shannon entropy estimates by more than 10% for User-Agent (downward) and more than 68% for WebGL Renderer (upward), revealing that prior large fingerprinting studies — Panopticlick (83.6–94.2% unique, predominantly reached via tech-oriented channels) and AmIUnique (90% desktop unique) — likely misrepresent real-world risk due to uncontrolled male bias, as confirmed by a directly comparable study showing 76.5% male participants.

2025-berke-unique-whose-web §6, Figure 4 tls-fingerprintml-classifier

A simple three-hidden-layer MLP trained on only 13 standard browser attributes achieves AUROC above 0.5 for every tested demographic group: gender 0.663–0.679, age 55+ 0.644, Hispanic ethnicity 0.60, Asian race 0.698, Black race 0.677, and high-income bracket 0.617. Because the model used only attributes already collected by mainstream fingerprinting scripts (e.g., FingerprintJS), richer real-world attribute sets would yield substantially higher demographic inference accuracy.

2025-berke-unique-whose-web §7.1, Table 5 ml-classifiertls-fingerprint

Screen resolution (572 distinct values, 4.5% unique, entropy 5.51), WebGL Unmasked Renderer (654 distinct values, 3.2% unique, entropy 6.833), and User-Agent (434 distinct values, 2.8% unique, entropy 4.613) are simultaneously the most uniquely identifying individual attributes and the strongest demographic predictors by normalized mutual information across all five demographic categories tested (gender, age, income, Hispanic ethnicity, race).

2025-berke-unique-whose-web §7.2, Figure 6, Table 1 tls-fingerprintml-classifier

Obfuscated proxy traffic (including Shadowsocks, VMess, VLESS, Trojan, obfs4, and REALITY) can be reliably fingerprinted by detecting encapsulated TLS handshakes — the inner TLS ClientHello that appears inside an outer encrypted tunnel. This fingerprint is protocol-agnostic: any proxy that wraps TLS-bearing application traffic will produce it. The authors deployed a similarity-based classifier within a mid-size ISP serving over one million users and demonstrated detection with minimal collateral damage.

2024-xue-fingerprinting Abstract, §5, §7 dpitls-fingerprintml-classifier

Dominant failure modes differ systematically by country: China (AS45090) shows connect timeouts in 75% of DoT failures (IP-level blocking); Kazakhstan (AS48716) shows post-TLS-handshake timeouts in 72% of DoT failures (likely ACK or segment discard after handshake); Iran (AS197207) shows TLS handshake timeouts in 80% of DoT failures. Packet capture analysis confirmed that timeouts during and after the TLS handshake correspond to unacknowledged TCP segments, not connection resets.

2021-basso-measuring §V-F, §V-G, Table VIII ip-blockingtls-fingerprintmiddlebox-interference

Vodafone (AS12357, AS12430, AS6739) deployed Allot-based TLS interception to block womenonweb.org: the system resolver returned a legitimate IP (67.213.76.19), but connecting to it triggered a forged certificate signed by Allot; disabling TLS certificate validation fetched the Vodafone blockpage, confirming a man-in-the-middle box rather than a redirect. OONI's standard Web Connectivity test recorded only a generic ssl_error:certificate verify failed and missed this entirely.

2021-ververis-understanding §3.7, §3.8.3 dpimiddlebox-interferencetls-fingerprint