Across 433,286 endpoints from a 10 Gbps university ISP passive tap, 94% responded with data to at least one of 8 protocol probes (TLS, HTTP, STUN, S7, Modbus, DNS-AXFR, random bytes, empty); all five tested probe-resistant proxies (obfs4, Lampshade, Shadowsocks, MTProto, OSSH) never responded with data to any probe. This single filter reduces the suspect set from 433,286 to ~26,000 endpoints and rules out 94% of ISP-observed hosts as non-proxies with zero false negatives against the tested protocols.

Manually-crafted decision trees combining probe non-response, FIN/RST close type, and connection timing achieved a false-positive rate below 0.001% for obfs4, Lampshade, Shadowsocks, and OSSH across 1.9 million endpoints; for OSSH specifically, 7 of 8 flagged Tap endpoints were confirmed genuine Psiphon proxies by developers. MTProto was the sole exception, producing 3,144 false positives (0.56% of Tap, 0.02% of ZMap) because its infinite-timeout behavior is shared by a non-negligible population of common hosts.

§V-A, Table IV evaluation

Endpoints that never close a connection and never respond to any probe ('infinite timeout') represent 0.7% of the ISP Tap dataset and 42% of the ZMap active-scan dataset; this is the single most common probe-indifferent behavior in both datasets. MTProto already exploits this: its strategy of keeping failed connections open indefinitely produces the highest false-positive rate (0.56% of Tap) among all tested protocols, making it effectively uncountable at acceptable collateral-damage thresholds.

§VI, Fig. 13 defense

The authors' ISP Tap dataset yielded 129,000 unique response sets across 433,286 endpoints while ZMap's 1.5 million endpoints produced only 31,000 unique sets — with over 42% of ZMap endpoints behaving identically (infinite timeout, no data) due to firewall chaff. This vantage-point bias means the effective false-positive rate a censor faces when targeting ISP-observed traffic is ~28× lower than against random scans (0.02% vs 0.56% for MTProto), making ISP-scale active probing far more actionable than Internet-wide scanning alone.

§III-B, §V-D, Fig. 2 evaluation

Each probe-resistant proxy exposes a unique TCP close-threshold fingerprint: obfs4 closes with FIN at 8,192–16,384 bytes and RST at the next multiple of 1,448 bytes beyond that; Lampshade at FIN 256 bytes / RST 257 bytes; Shadowsocks-python and -outline both at FIN 50 bytes (outline also RST at 51); OSSH at FIN 24 bytes / RST 25 bytes. A binary-search tool using random probes can discover these thresholds remotely without knowing any shared secret, providing a protocol-specific fingerprint independent of payload content.

§IV-C, Table II detection

Re-testing in 2025 on a Pixel 10 Pro XL running Android 16 with October 2025 security updates confirmed that blind in/on-path VPN inference attacks remain fully viable despite CVE-2019-9461, CVE-2019-14899, and CVE-2024-49734 having been formally closed. All three core attack primitives—VPN-assigned internal IP discovery, active connection inference, and TCP reset injection via sequence/acknowledgment window scanning—succeeded across OpenVPN, WireGuard, and NordLynx.

2026-tolley-architectural §5.1–5.3 traffic-shaperst-injectionactive-probing

Six widely deployed VPN and circumvention tools—OpenVPN, WireGuard/NordLynx, NordWhisper, Orbot (Tor on Android), Lantern, and Psiphon—all failed to block internal IP inference, connection-state detection, and TCP reset injection under identical adversarial conditions on fully patched Android 16. Application-layer obfuscation in Lantern and Psiphon did not prevent TCP-layer disruption; Orbot's VPN-style encapsulation of Tor traffic was bypassed via the same tunnel-level side channels.

2026-tolley-architectural §5.2, §5.4–5.5 traffic-shaperst-injectionactive-probing

The paper proposes an Internet Freedom vulnerability registry with five design principles: persistent cross-vendor tracking under shared identifiers (e.g., IF-ARCH-2025-001) as long as a risk remains reproducible; human-centered impact ratings anchored to harm potential for journalists and dissidents rather than CVSS-style exploitability scores; timestamped re-verification hooks with linked PCAPs and minimal reproduction scripts; a structured media interface to counter vendor narrative capture; and open public APIs for integration into risk dashboards so that users of tools like Orbot or Lantern can directly query their configuration's exposure to known metadata-based attacks.

2026-tolley-architectural §6.1–6.5 traffic-shaperst-injectionactive-probing

The September 2025 leak of ~600 GB from Geedge Networks and the MESA Lab (Institute of Information Engineering, Chinese Academy of Sciences) is the largest known document disclosure from the GFW vendor ecosystem. It establishes a direct lineage: MESA Lab (founded 2012 by Fang Binxing's team, annual contracted revenue >35M RMB by 2016) spun out Geedge Networks in 2018, with MESA alumni filling key engineering roles (e.g. Zheng Chao as CTO). The leak includes ~64 GB of MESA git repositories, ~35 GB of MESA internal documents, ~15 GB of Geedge internal documents, and a ~3 GB Jira export — providing direct access to source code, work logs, and internal communications behind GFW R&D.

2025-geedge-mesa-leak §4 dpiactive-probingml-classifiersni-blockingfully-encrypted-detect

Internal Geedge documents confirm active contracts to deploy GFW-derived censorship and surveillance infrastructure in Myanmar, Pakistan, Ethiopia, Kazakhstan, and at least one additional unidentified country under the Belt and Road framework, in addition to domestic deployments in Xinjiang, Jiangsu, and Fujian. The exported product (the Tiangou Secure Gateway / TSG line) is not a stripped-down export variant — leaked TSG documentation shows DPI, active-probing, ML classifiers, and granular per-region traffic control rules that mirror the domestic GFW capability set.

2025-geedge-mesa-leak §5, §6 dpiactive-probingml-classifiersni-blockingdns-poisoningfully-encrypted-detecttraffic-shape

InterSecLab frames the Geedge/TSG export program as the commoditization of national firewall capability: rather than each censor state independently developing detection infrastructure, they contract Geedge for a turnkey system incorporating the cumulative R&D of MESA Lab (>10 years, National Science and Technology Progress Award winners). This structural shift means the marginal cost for an autocratic government to acquire GFW-grade censorship is now a procurement decision, not a multi-year engineering program. The report identifies that Geedge's relationship with the MESA Lab gives customer states indirect access to ongoing academic R&D improvements, not just a static product.

2025-interseclab-internet-coup §2, §6–§7 (InterSecLab report) dpiactive-probingml-classifier