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.

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

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.

§V, Table III detection

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

InterSecLab's 76-page analysis of the Geedge/MESA leak (based on nine months of indexing and translating >100,000 documents) characterizes the Tiangou Secure Gateway (TSG) product line as a commercially deployable detection stack that combines deep packet inspection, real-time mobile subscriber monitoring, active probing, ML-based traffic classifiers, and granular per-region rule sets. TSG is not a research prototype — leaked documentation includes deployment timelines and client government interactions for Kazakhstan, Ethiopia, Pakistan, Myanmar, and one unnamed country, with censorship rules explicitly tailored to each region.

2025-interseclab-internet-coup §3–§5 (InterSecLab report) dpiactive-probingml-classifiersni-blockingip-blockingtraffic-shapefully-encrypted-detect

Justice for Myanmar documents that Geedge Networks supplied Myanmar's military junta with GFW-derived surveillance and censorship infrastructure under Belt and Road frameworks following the February 2021 coup. The deployed system (Tiangou Secure Gateway / TSG) incorporates the same DPI, active-probing, and ML-classifier capabilities as the domestic Chinese GFW, giving Myanmar one of the most technically capable censorship systems in Southeast Asia.

2025-jfm-silk-road-surveillance §3, §5 dpisni-blockingip-blockingtraffic-shapeml-classifieractive-probing

The paper proposes modeling HCS undetectability as a simulation-based cryptographic distinguishability problem: if traces produced by the real-world HCS channel are computationally indistinguishable from ideal-world application-channel traces (T_HCS ∼ T_simulator), the HCS achieves provable security against any adversary — passive or active. The simulation paradigm is parametric in adversary capability, meaning a single proof covers the full spectrum from passive SNI monitoring to active DPI.

2025-pereira-position §1, §2 dpitraffic-shapeactive-probing