ScrambleSuit defeats active probing by requiring clients to prove knowledge of an out-of-band shared secret before the server responds; a probing censor receives only silence. Two mechanisms are provided: session tickets (preferred for non-Tor applications) and an authenticated UniformDH handshake (optimized for Tor's shared-secret bridge distribution model), with both producing payloads computationally indistinguishable from random.

ScrambleSuit's prototype achieves a mean goodput of 148 KB/s (σ=61 KB/s) versus Tor's 286 KB/s (σ=227 KB/s) over a 100 Mbit/s LAN — roughly half Tor's throughput — with 45–50% total protocol overhead compared to Tor's 19.6%. Disabling inter-arrival time obfuscation raises goodput to 321 KB/s (σ=231 KB/s), demonstrating that artificial delays are the dominant cost rather than padding or cryptography.

§5.2, Table 2 evaluation

ScrambleSuit achieves polymorphism by seeding each server's PRNG with a randomly generated 256-bit value, which generates server-specific probability distributions over packet lengths (up to 100 bins) and inter-arrival times (bins in [0, 10) ms). The seed is shared with clients after authentication, so both sides shape traffic identically; a censor monitoring two distinct ScrambleSuit servers observes different distributions and cannot build a single universal classifier.

§4.3 defense

Client proof-of-work puzzles are ineffective as an active-probing defense because a state-level censor with parallel hardware can solve multiple puzzles simultaneously, one per CPU core. The authors estimate that the Tor bridge churn rate (rate of new bridge IP addresses) is too low to raise a well-equipped censor's workload beyond practical limits without simultaneously making the scheme impractical for legitimate clients — the same balancing problem as PoW for spam.

§4.1.1 evaluation

Tor's traffic contains a characteristic prevalence of 586-byte packets (Tor's 512-byte cells plus TLS header overhead) that form a strong flow-level fingerprint detectable from a few dozen captured packets. ScrambleSuit's packet length morphing eliminates this signature and shifts the distribution toward MTU-sized packets, but the authors note that a censor using the VNG++ classifier — which relies on coarse features like connection duration, total bytes, and burstiness — would still require only a marginal increase in ScrambleSuit's overhead to defeat.

§4.3.1, §5.1, Figure 10 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.

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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.

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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.

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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.

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