Important

Analysis Author: Excellent

Solemn Statement:

Caution

This analysis report aims to objectively present observations and technical speculations based on questionnaire data, revealing the operational logic of game security systems. The report content does not constitute any form of cheating instruction or guidance, nor does it encourage any behavior that violates the principles of game fairness. All mentioned technical details and countermeasures are solely for technical discussion and security education purposes, intended to help players understand game security mechanisms, thereby better protecting their own accounts and game environment. We urge all players to cherish their accounts, abide by game rules, and jointly maintain a fair and healthy gaming ecosystem.

Important Notes:

Caution

This report was compiled and analyzed on October 20, 2025. The game will continue to make adjustments, but the general direction remains unchanged. There may be slight differences compared to the detections you encountered before or after. If you believe any part of this report needs correction, feel free to contact me via email.

User Agreement:

Caution

Using this document for profit will result in your demise. Reproducing, pasting, scanning, or mass-distributing this document without permission will result in your demise. Reading the following content is deemed as your agreement to this covenant. Violating the agreement defaults to the demise of your entire family.

Game Ban Mechanism Analysis and Modeling Based on User Feedback Data

This report follows the following analytical path:

1. Data summarization and classification: Summarize fragmented descriptions from the questionnaire and extract key ban patterns.
2. Model construction: Abstract these ban patterns and build them into four core technical analysis frameworks: Data Modification Detection Ban, Behavioral Anomaly Detection Ban, Environmental Anomaly Detection Ban, and Device Anomaly Detection Ban.

Research Significance:

Note

This report aims to go beyond scattered guesses and rumors, providing a structured, technically reasonable analysis based on large-scale user data for the "black box" field of game security.

Its significance lies in:

• For players: Helping players more clearly understand the boundaries of game security rules, recognizing which device states and in-game behaviors may trigger bans, thereby better protecting personal digital assets and fundamentally understanding the importance of maintaining a fair gaming environment.
• For game security researchers: Providing an empirical case of reverse-engineering anti-cheat strategies based on user behavior, offering data references and analytical frameworks for subsequent related research.
• For game developers: Although this report is based on external data, the player community's perceptions and feedback on ban mechanisms can also serve as side references for optimizing anti-cheat system strategies and user communication.

Through this research, we hope to more scientifically and systematically depict the true picture of this digital arms race, revealing the complex and sophisticated technical game behind it.

Game Detection Mechanism Analysis:

The ban mechanisms can be mainly divided into the following categories:

• Data Modification Ban: This is the most basic and core detection method. The game client and server continuously verify various data during gameplay, such as values in memory, network packet content, game file integrity, etc.
  • Trigger Conditions: Modifying game memory (e.g., using GG modifier), tampering with game resource files (e.g., models, textures), using unofficial clients, abnormal network packets (e.g., speed hacks, instant-kill cheats).
• Behavioral Anomaly Detection Ban: With the development of machine learning and artificial intelligence, behavioral detection has become increasingly important. The system no longer relies solely on "catching signatures" but judges whether a player "behaves like a cheater" by analyzing a series of behavioral data in the game.
  • Trigger Conditions: Far beyond human aiming precision and reaction speed (e.g., "head lock"), movement trajectories that defy physics (e.g., teleportation, flying), precise enemy location and attack without line of sight (e.g., wallhack), abnormally high headshot rate and kill/death ratio (K/D), etc.
• Environmental Anomaly Ban: This mechanism focuses on detecting whether the environment in which the player runs the game is risky, rather than directly detecting cheating behavior itself. It is one of the most preventive ban methods.
  • Trigger Conditions: Device has been rooted or jailbroken, running in an emulator or virtual space, detection of known cheating tools or frameworks (e.g., Magisk, LSPosed, GG modifier) processes or file remnants, abnormal TEE (Trusted Execution Environment) status, modified system kernel, etc.
• Hardware Ban: Using cheats multiple times on the same device leads to permanent account ban, and network IP is also banned.

The above are detection methods common to all games. In detail, each game adopts different targeted strategies, but they are all related to reports — that is, after an account receives reports, corresponding detections are triggered according to the different detection methods of each game.

Game Detection Principle Analysis

Before a more detailed analysis, we must first understand the underlying detection principles of games.

The current game detection model principle is differential comparison, and it does not detect a single thing in isolation. Instead, it continuously compares and analyzes. The more similar your features are to those of cheating players, the higher your confidence level.

To summarize detection in one sentence: What normal users do not have, cheating users do. The more cheating user samples there are, the more features there are.

Therefore, the stable principle is: Use more things that normal users also use, and use less things that only cheating users use.

Note

Terminology explanation: Differential comparison is an analysis method that finds key differences between two or more objects through multi-dimensional comparison. Its core is "finding differences," but not aimlessly; it is carried out around specific goals.

Confidence level, also called confidence, is an indicator in statistics used to express "how reliable the conclusion is," usually expressed as a percentage (e.g., 55%, 99%). It does not mean the conclusion is definitely correct, but indicates "the probability that the correct conclusion appears in multiple experiments."

When the confidence level reaches a certain threshold, a ban is triggered. Depending on the mechanism, different thresholds lead to different ban measures. This is the core reason why some people get banned for the same thing while others remain stable. For example: Using the same cheat, some get banned for 7 days, some for 3 days. This is caused by differences in their account confidence levels.

Currently, the main factors affecting confidence level are: environment, behavior, reports, device.

Environment includes not only the phone environment but also game environment and account environment. Others are abbreviations; see detailed analysis below.

Most games do not ban based on a single factor's confidence level; at least two factors must be met, or a single factor reaches the upper threshold limit.

Example 1: In CFM, Triangle Continent Auto, Valorant, after receiving a certain number of reports, even manual play can result in a 24-hour or 3-day ban.

Example 2: Peace Elite device face: ① IP change ② Reports ③ Long-term inactivity ④ Multiple account login records on the same device or same IP.

Meeting any two conditions has a high probability of triggering device face, such as long-term inactivity plus IP change, or long-term inactivity plus many device account records plus many login accounts plus reports, etc.

For other game mechanism factors, see detailed analysis below.

Important

This article mainly studies the Triangle Continent mechanism. Therefore, it focuses on analyzing Triangle Continent. The following is a summary of the security detection model.

In-depth Analysis Report on Triangle Continent Auto Security Mechanism

1. Mechanism Overview:

Compared with other games, Triangle Continent's detection mechanism shows the following characteristics: Multi-factor temporary bans: Unless directly detecting the cheat itself, it generally does not issue permanent bans, but applies different measures based on the player's playstyle, such as environmental anomaly, behavioral anomaly, third-party software/plugins, game data anomaly.

Coordinate Encryption:

Coordinate encryption tends to be a hidden mechanism, applied only to certain groups, mostly high-rank players or those with good historical records. Currently, switching accounts can resolve it, confirming it is an account-specific strategy, unrelated to the device. It may be highly related to reports. Since this mechanism has just appeared and there has been limited exposure, accurate analysis is not yet possible. I believe that after an account reaches a certain confidence level and receives reports, encryption is issued. It may also be related to account level, for example, a level 30 account with 50 confidence may get an abnormal ban, while a level 60 account with 50 confidence only gets coordinate encryption, and 80 confidence leads to a ban.

Environment Detection:

Triangle Continent's ban detection differs from other games; it has lower tolerance for cheating environments. Some modules may not trigger bans when used by normal players, but once a large number of hateful cheating users use this module, the module will be identified as a cheating environment module. The more people get banned, the more obvious the feature, and the higher the confidence level. This is why something that was fine before suddenly starts causing TEE or TS module anomaly bans.

The characterization of cheating tools is a gradual, iterative process. It starts with running naked, then becomes ban after many reports, then ban after using the tool and receiving one report, and finally instant ban upon login.

Also includes report detection:

Receiving reports causes the account's confidence level to drop. Combined with other factors, it leads to a decrease in report tolerance. Each account has daily and seasonal report quotas. Different accounts have different report quotas (related to device environment, account level), for example, abnormal device environment + receiving more than 5 reports in a match, or receiving too many reports in a day, generally causes the account to go abnormal. Even with no environmental anomaly, reaching the account limit can lead to a 24-hour ban, even for clean games. Environment is also affected by other factors; here only report factors are analyzed for reference (report quota has too many influences, only examples are given, not actual representation).

2. Detailed Ban Mechanism Analysis

Default-triggered report detection: BL lock, TEE: Currently the game does not detect these two individually, but uses them as feature points for comparison analysis, causing account confidence to rise. Different games have inconsistent confidence weights for each feature. Confidence in turn affects report quota strategy.

Example: In CFM, just unlocking BL, a normal player receiving 100 reports this season results in 24-hour environmental anomaly. After unlocking BL it becomes 75, and after TEE damage it becomes 50. In Triangle Continent Auto it may be harsher: after unlocking, seasonal quota becomes 30, TEE damage makes it 10. Quota numbers are only illustrative examples and differ from reality

• Other factors also cause report quota to decrease. For example: in-game behavior, account level, reputation score, device environment, abnormal records, real-name ban records, unusual login locations, etc. This creates the feeling: same thing, one report and I'm gone, but he stays stable.

  • There is also a very abstract report detection (in some games): If quota is exhausted and banned, the device is flagged, causing confidence to drop after account unban, leading to repeated bans. Possibly one report, or even just idling in lobby results in 1-day ban (also related to account; if device is blacklisted, unusual login causes instant 1-day ban). The solution is simple: lower confidence level by slightly modifying device info, even just changing the phone model can slightly lower confidence and allow more reports. (Bans exceeding 24 hours are influenced by other feature factors.)

Why say it's not single detection but feature analysis comparison? Because it's not banned for unlocking BL, but because report quota decreased. Even normal players without unlocking can get banned due to confidence drop. If you don't cheat, at worst you get 24 hours. All bans exceeding 24 hours trigger other detection points.

Generally triggered environmental security detection after reports:

2.1 Game environment and behavior data anomaly (Security Center displays as third-party tool)

• Root related (1 day, 3 days, 7 days, 30 days): Triangle Continent has a lower environmental confidence threshold. For example, if 30% of cheating users use a certain plugin or module, that module will be identified as a cheating auxiliary. Other games use 80%. After receiving reports, device inspection is performed, increasing device scanning (disk sweep) and raising device suspicion.
• Emulator / Virtual machine / Framework / Direct install: In this era, probably no one uses these anymore (third-party plugin 7/30 days/3650)
• Peripherals, macros, auto-clickers (7 days, 30 days)
• Installed GG modifier or other modifiers (even unused; using directly results in 10 years) (30 days)

• Root-related modules or software (3 days)

  The above are results scanned by the game without injection into the game.

  2.2 Game environment and behavior data anomaly (Security Center displays as modified data or code or game client data anomaly)

• Root injection behavior: Different from above, root processes were scanned or injection behavior into the game was detected during game runtime. Using TrickStore module also triggers this detection. Ban duration varies based on featured situation and account confidence. (1 day, 3 days, 7 days, 30 days)
• Port interception and other network fluctuations
• Device has abnormal records: As long as the device has abnormal records, report quota decreases. During security observation period (3 days, 15 days, 30 days), possibly one report or any anomaly detected leads to ban. (1 day, 3 days, 7 days, 30 days)
• Outdated touch drivers: Touch used by auxiliary gets featured (30 days / 3650 days)
• ADB debugging: shizuku, scene, etc. (7 days, 30 days)
• Regarding BL, TEE: Based on results, unlocking BL is not used as a feature for analysis; instead, modules that hide BL cause anomalies, but TEE damage may lead to frequent 1-day bans (exceeding one day involves stacking other factors)
• GPU detection: If your Android version is below 16, do not use GPU auxiliaries; must use CPU auxiliaries (otherwise 30 or 3650 ban)

• Account abnormal records: After ban, more frequent bans. Confidence rises. Also includes account security detection: unusual login locations, too many accounts logged in on same device, too many IP logins.

  Third-party plugins (Security Center displays behavioral anomaly)

  1. Generally because server-received data does not conform to human behavior, e.g., shotgun hits all on body at dozens of meters, bullet tracking hits all at hundreds of meters or hits wall

  2. No data modification detected but AI considers problematic.

  This is behavioral anomaly for auxiliary type; for more accurate, see behavioral anomaly analysis below

  This detection targets excessively outrageous operations that violate game logic but were not detected locally.

  AI behavior analysis is irregular; sometimes ban after playing a few days, sometimes immediately upon playing, possibly influenced by different factors deciding whether AI analyzes you

  How to avoid third-party plugins?

  • Avoid using global injection modules and game injection modules. After ban or anomaly, clean device info + uninstall and reinstall game.
  • Avoid MT Manager/scene/ROOT-level processes injecting into game runtime (for auxiliaries, use no-background mode). It won't detect MT Manager itself but will detect MT Manager process injecting into game.
  • After flashing ROM, try not to install any modules except SUSFS module. In SUSFS module, enable: Auto hide default/bind mount, Hide sus-mounts from all processes.
  • Core principle: Use more things normal users also use, use less things only cheating users use.
  • Ultimate hiding secret: Relock BL for lifetime stability. Even if reported and certain environmental anomaly detected, it will not immediately ban; only when certain confidence level is met will it ban. Therefore, the fewer environment modifications, the more stable.

Simple Ban Summary

It is: Receive report → Issue file for strong detection → Environmental detection → Strongly flag account → Confidence level met → Ban

Issued file view path:

/data/user/0/game package name/files/ano_tmp/ or /data/user/0/game package name/files/ano_tmp

Issued file analysis: (copied from others + combined with Little Snow author analysis)

• A_v Environment monitoring (basic detection; let teammates report yourself, no ban means pass)

• A_cd Behavior monitoring ( Issued locally without pop-up is local issuance; pop-up is cloud This issuance has trap addresses. Auxiliary passes but driver fails may lead to follow-up ban. ACD is issued locally but without triggering cloud CD there is no pop-up; trap trigger may lead to 10-day follow-up) Depending on confidence level, each account has different quota; some get issuance after one report, some can take more, possibly related to other analyses in this article.

• A_h Data anomaly (ban 1/3/7)

• A_s Strongly flag device/account (coordinate encryption, issued after continuous reports)

• A_r Ban flag After confidence level reached, ban 30 days or 10 years

• A_cp Unknown Account flag, enter little black room

Environmental anomaly 1 day (Security Center displays as modified data or code)

Report fallback mechanism: Receiving reports causes account confidence to drop. Combined with other factors, report quota decreases. Each account has daily and seasonal report quotas. Different accounts have different report quotas (related to device environment, account level). Receiving more than 5 reports in a match generally causes immediate sleep for this account. Even with no environmental anomaly, reaching account limit causes 1-day ban, even for clean games. After cumulative report quota upper limit reached, ban 1 day Each account's report quota varies based on behavior/environment/level/rank/reputation/device/login IP changes, etc.

Try to avoid slaughter right after switching accounts, avoid cross-rank games. If low-rank gets reported by high-rank, extremely high probability of trigger.

Environmental anomaly 1 day (Security Center displays as behavioral data anomaly or no display)

Triggered by abnormal behavior, mostly aimbot too obvious, or wallbang through smoke/water, etc. After report, if AI considers abnormal behavior, ban 1 day then lifted. If acting too poorly and AI considers excessively abnormal, may become 3650 (Security Center displays behavioral data anomaly)

Avoid abnormal behavior, don't make aimbot too obvious, avoid cross-rank games. If low-rank gets reported by high-rank, extremely high probability of trigger. In treasure hunt mode, don't just stare at best loot ignoring everything else; doing so many times will be judged abnormal.

3650 Ban (Security Center displays as "Modified game code or data")

• Trigger conditions:
  1. Account confidence level reaches upper limit, and device has history of 10-year ban
  2. Used featured auxiliary.
  3. Memory-modifying auxiliary, port not protected
  4. Second time using third-party plugin.

• How to avoid: Fundamentally, as long as no form of memory cheat is used, after ban flash ROM and only use CPU no-decryption kernel that passed detection will not trigger 10 years. This is pure technical detection that cannot be avoided by "acting."

Some auxiliaries use memory decryption for temporary stability, but may get follow-up ban later (still骗 you saying pure algorithm decryption)

Behavioral anomaly type 24 hours 3 days 7 days

Behavioral anomaly (technical factors)

• Low level but killing experts like killing dogs (commonly called fish bombing)
• Continuous team wipes, excessive head count
• Device has ban history, real-name has ban history
• Multiple bans
• Unusual login locations

Feedback investigation says: Not killing, dog-play style, take loot then avoid people and extract; after many times becomes behavioral anomaly. This is individual case for reference only.

The above may meet two or three conditions for high probability trigger. After one trigger, subsequent triggers possible with one condition met and reported.

Poor personal character (playstyle factors)

• Fist-supplementing others
• Damaging teammates or deliberately not saving teammates
• Other ways to disturb teammates
• Selling/duplicating equipment or other abnormal playstyles

Device Ban (Security Center displays as "Modified data or code")

If devices used have maxed out report quotas leading to ban records, the device's report quota decreases more and more, and may cause confidence level to continuously rise, ultimately leading to direct 10-year ban

Device ban is not direct ban, but a linked detection. When detecting device ID, Android ID, Google Advertising ID, network IP info, or other features with ban records, account confidence is raised. If other aspects also abnormal, direct ban due to other aspects, e.g., environmental anomaly, third-party, high-risk/little black room, etc.

Simply put, it is an important influencing factor for other factors.

Current recommendation: If conditions allow, after ban directly flash ROM and change network IP (turn off modem for 1 minute), phone toggle airplane mode for 1 minute. If no conditions, at least use script to change device info.

Device ban: After 10-year ban, if not cleaned, subsequent anomaly or report has extremely high probability of direct 10 years. Real-name ban: Too many real-name bans may affect confidence, but only for reference; currently no proof found of real-name impact