The hybrid idle scan technique converts approximately 1% of the total IPv4 address space into passive measurement vantage points without requiring control of either the censored client or the destination server, enabling full bipartite connectivity measurements across 161 geographically stratified Chinese clients and 176 servers over 27 days. After data pruning for quality, 36% of raw measurements were usable; ARMA modeling was sufficient (over Hidden Markov Models) because only level-shift detection was needed.

The GFW blocks Tor primarily by dropping SYN/ACK segments entering China from blacklisted IP/port pairs, not by dropping SYN segments leaving China. Of 142,802 CN→Tor-Relay measurements, 81.52% were Server-to-client-dropped versus only 0.55% Client-to-server-dropped. Blocking Tor directory authorities also showed substantial Client-to-server drops (19.61%), suggesting authorities may be treated differently.

§4.1, Table 1 detection

GFW filtering failures — cases where blocked Tor traffic passed through — showed no conspicuous geographic patterns across China. The maximum observed Pearson correlation coefficient between neighboring clients' failure counts was 0.26 (near-zero), and failure cases were geographically distributed in proportion to Internet penetration, not clustered by province or ISP region.

§4.2, Figure 6, Figure 8 evaluation

GFW failures are both persistent and intermittent: four client/server pairs showed all 22 hourly measurements over a full day returning No-packets-dropped (entirely unblocked), while many others showed only sporadic failures. Temporal analysis showed failures cluster in bursts of hours, with probability of a second failure decaying sharply beyond ~5 hours after the first.

§4.1, §4.2, Figure 7 evaluation

Routing is the dominant structural factor in GFW failures. CERNET (the Chinese Educational and Research Network) accounted for 503 of 135 destination IPs' failures — by far the most of any network — and packets transiting CERNET→CERNET links reached Tor destinations at an r=0.9896 ratio, near 1.0. Within CHINANET and CNC Group backbones, the Tor-to-non-Tor traversal ratio dropped to 0.403 and 0.272 respectively (Table 4), indicating heavy intra-ISP filtering.

§5.2, §5.3, Table 3, Table 4 evaluation

The largest single source of censored domains in the GNL is MESA lab's SNI monitoring dataset (E21-SNI-Top200w.txt) containing 57,362 censored domains, and E21-SNI-Top120W-20221020.txt with 36,467 domains—totaling over 93K domains from network tap data alone for a single country (E21 = Ethiopia per InterSecLab attribution). A separate Xinjiang dataset (XJ-CUCC-SNI-Top200w.txt) contains 13,604 domains. These datasets "do not seem to come from popular domain lists, and instead appear to be gathered from network taps," confirming that Geedge builds censorship target lists directly from passive traffic observation.

2026-sheffey-geedge §4.2, Table 3 dpisni-blockingmeasurement-platform

Of 6,915,266 domains extracted from the 572 GiB Geedge Networks Leak (GNL), 298,955 censored domains (93.7% of all GNL-censored domains) appear in neither Tranco top-1M nor CitizenLab test lists. Measurements across China (Guangzhou/Nanjing), Myanmar, Pakistan, and Algeria confirmed censorship via DNS injection and SNI-based TLS connection termination. The GNL covers 25–62% of Tranco-censored domains across countries, showing substantial but incomplete overlap. This vendor-side ground truth reveals a censorship surface roughly two orders of magnitude larger than curated academic test lists.

2026-sheffey-geedge §4.1, Table 2 dpisni-blockingdns-poisoningmeasurement-platform

CensorAlert aggregates censorship signals from heterogeneous open sources — including OONI, Cloudflare Radar, NetBlocks, GitHub Issues of circumvention tools (Hysteria, Xray), Net4People BBS, NTC Party forum, Mastodon, X, Telegram channels, and arXiv — normalizing each item into a common schema preserving timestamp, source, raw data, and provenance with a link to the original content.

2026-zohaib-extended §2 (Data Sources) measurement-platform

Systematic measurement platforms (OONI, Censored Planet, Cloudflare Radar, NetBlocks) have inherent blind spots due to geographic coverage and protocol-specific test constraints; critical censorship discoveries — including GFW fully-encrypted protocol blocking and regional Chinese censorship — were first surfaced by user reports on forums and GitHub issue pages of circumvention tools, not by automated measurement infrastructure.

2026-zohaib-extended §1 measurement-platformfully-encrypted-detect

CensorAlert generates text embeddings (OpenAI text-embedding-3-small) from each item's summary, title, and tags to cluster semantically similar reports within configurable time windows; near-duplicates such as reposts, copied headlines, and translations are collapsed into a single canonical post that preserves all original source URLs and metadata.

2026-zohaib-extended §2 (AI-based Scoring) measurement-platform

CensorAlert's LLM agent scores each ingested item 0–5 on five independent dimensions — credibility, novelty, impact, timeliness, and verifiability — then computes a normalized significance score (0–10) from these components; items are processed every two hours using OpenAI GPT-5 Thinking (hosted on Azure) constrained to return structured JSON output.

2026-zohaib-extended §2 (AI-based Scoring) measurement-platform