pg_valve_deal.cpp / pg_valve_main.cpp source shows the 'valve' (pangu_valve) component implements a MAAT-fed, hierarchical (region/group -> dataset -> domain-ID) rule-dispatch engine: each incoming rule line carries a keyword field plus expr_type/match_method/is_hexbin matching flags, an ADD/DEL action, and a percentage-based 'Droprate' throttle parsed out of a semicolon-delimited region string (DOMAIN_ID=...;config_id=...;Droprate=...) — i.e. a keyword/domain-based engine that can partially throttle traffic, not just binary-block it.

The internal 'MAAT网络流处理配置统一描述框架' engineering manual (v3.1.20, author 郑超, 2021) documents MAAT's Redis-synced rule-compilation framework and its RuleScan/Hyperscan-based pattern-matching engine (libmaatframe.so / librulescan), and records that RuleScan's fast-scan feature caused a production outage on 2019-03-19 and has been disabled ever since.

An internal 'MAAT Configuration Description Manual (String)' fully documents MAAT's rule-compilation model: per-field string matches (substring/prefix/suffix/exact/regex/AND-of-substrings/offset-anchored substrings) grouped into up to 8 AND/NOT clauses per compiled rule (conjunctive normal form), each carrying an action code (0=block, 1=monitor-only, 2=whitelist), blacklist and logging flags, and a floating-point execution-order field for safe rule reordering, plus the C scanning API (Maat_full_scan_string) and the file/JSON formats used to push rule updates to production.

Internal MAAT engineering Q&A notes detail the rule engine's filter hierarchy: a 'region' config matches on keyword / regex / IP / extended-IP(CIDR) / numeric / file-digest / text-similarity / FQDN fields; regions roll up via AND/OR into 'group' configs; groups roll up into an 8-clause-max 'compile' config in conjunctive normal form. Rule config is pushed via a Redis single-primary/multi-replica tree, and MAAT itself is not distributed — each production front-end box runs its own single MAAT instance that receives pushed config and calls the shared rulescan library to execute the actual scan.

The AppSketch/MAAT signature system contains a systematically dated, patch-versioned catalog of FQDN-based detection signatures for dozens of individually named commercial VPN apps (e.g. V2VPN, V2Netvpn, Turbo VPN, LetsVPN, AdGuard VPN, Avira Phantom VPN, TouchVPN, FinchVPN, Opera VPN, Ultrasurf VPN, GoFly VPN), each modeled as an 'app' object in category 'networking' / subcategory 'tunnels' whose default deny_action drops the flow while sending both an ICMP-unreachable and a TCP RST to the client. At least 35 such distinct VPN-app signature objects appear in this batch alone, dated July-November 2024, with repeated 'Patch0N' revisions to the same app as its domains rotate.

A production TSG maat.conf shows the MAAT rule-matching engine running four parallel instances (STATIC, DYNAMIC, APP_SIGNATURE_MAAT, CAPTURE); the APP_SIGNATURE_MAAT instance is explicitly configured against app_sketch_tableinfo.conf / app_sketch_maat.json -- directly confirming MAAT is the execution engine underlying the AppSketch signature system -- and is tagged with an ACCEPT_TAGS datacenter value 'xjlhs', indicating this specific instance is scoped to a Xinjiang deployment.

The GitLab group itself is named "K18_NTCS_WEB" (K18 = Kazakhstan), and its "nfs" web app implements per-protocol keyword-filter configuration classes (App/FTP/Mail/P2P/SSL keyword configs), an OpenVPN IP-list config, RADIUS-based logging/reporting entities, MAAT rule-sync beans, and an explicit "IP spoofing" business feature with its own "PXY仿冒地址池" (proxy spoofed-address pool) and dedicated policy-log support -- the single strongest piece of evidence in this batch tying named keyword-filtering plus IP-spoofing capabilities directly to the Kazakhstan deployment.