FiveM Anticheat Logs Explained

Your anticheat fired an alert. Now what? Most server owners open the log panel, stare at a wall of JSON-like fields, and either over-ban on instinct or under-ban from uncertainty. Neither outcome is good. This guide walks through how detection logs are structured, what each field actually tells you, and how to build a moderation workflow that converts raw log data into defensible decisions.

What a Detection Log Entry Actually Contains

A well-designed FiveM anticheat log entry is not a simple sentence. It is a structured record with at least five pieces of information: the player identity (license, HWID, IP), the module that triggered, the raw observed value, the threshold that value exceeded, and a timestamp tied to the server tick. Some systems also attach a session ID so you can correlate multiple alerts from the same player within a single play session.

Understanding these fields matters because the same detection module can fire for very different reasons. A movement check might flag a player whose client rubber-banded during a network spike, or it might flag someone flying 400 metres per second through a building. The raw observed value is the only thing that separates those two cases. Always read the delta or magnitude field first, before reading the module name.

The Six Detection Families and What Their Logs Look Like

Fiveuxe organises its 27 detection modules into six families. Knowing which family a log entry belongs to immediately narrows down what kind of cheat you are dealing with and what follow-up evidence to look for.

• 1. Event Security. Logs show the event name, the triggering resource, and the payload. A money-injection attempt will list the exact amount passed and the account type targeted. Compare the payload against your economy's legitimate ranges.
• 2. Economy Forensics. These logs capture balance deltas over time. A spike far outside normal earning velocity is the signal. The log will show the before value, the after value, and the elapsed time between them.
• 3. Entity Protection. Logs record the entity type, the network owner, and the action attempted. Spawn-flood entries will show the entity count per tick window.
• 4. Movement & Combat. Position deltas, speed readings in metres per second, and weapon fire intervals are the key fields. Noclip, teleport, and rapid-fire detections all live here.
• 5. Screen & Snapshot Intelligence. When a screenshot check fires, the log links to the captured image and records the detection reason. Pair these with screenshot evidence best practices to build an airtight ban record.
• 6. SENTINEL AI Co-pilot. Rather than a single threshold, SENTINEL correlates signals across modules and assigns a composite risk score. Its log entries summarise which contributing modules fired and the weight each one carried.

Reading Severity Levels Without Getting Them Wrong

Severity is not a ban button. It is a confidence indicator. A high-severity entry means the system observed something that is physically or logically impossible under normal gameplay. A teleport delta of 800 metres in a single tick cannot happen without external intervention. That is a high-severity, act-immediately signal.

A medium-severity entry means the observation is unusual but not impossible on its own. Firing 30 rounds per second is outside the norm for most weapons, but a desync burst can produce a similar artefact. Check whether the module fired once or repeatedly. Check whether other modules also fired in the same session. One medium-severity ping is informational. Five medium-severity pings across three different modules in twenty minutes is a pattern worth acting on.

Low-severity entries are your audit trail. They rarely justify a ban in isolation. They do justify watching the player more closely and can significantly strengthen a ban case that already has higher-severity evidence behind it.

Correlating Logs Across Multiple Identifiers

A single log entry is tied to a player session. But cheaters rotate accounts, spoof IPs, and claim hardware bans are false positives. The real power of structured logs comes from correlating across identifiers: license hash, HWID fingerprint, Discord ID, and IP history. If a newly registered account triggers the same detection module that a banned account did, and the HWID or IP overlaps, that correlation is the actual evidence.

This is why systems like Fiveuxe's Shadow-Link identity enforcement track 12 or more identifiers per player. When you review a log entry in the web panel, you can see the full identity cluster, not just the surface-level Steam or CFX license. A ban that stands up to an appeal is one where the log shows the detection, the identity record shows the cluster match, and the moderation note records the staff member who reviewed both. If you want to understand how the web panel surfaces this workflow, the anticheat web panel guide covers the full layout.

Building a Moderation Workflow Around Your Logs

Raw logs without a review process are just noise. A practical workflow has four steps. First, triage incoming alerts by severity. High-severity entries go to a dedicated review queue immediately. Medium and low entries aggregate into a daily review pass. Second, cross-reference the player's full log history before taking action. A first-time high-severity flag from a veteran player with a clean record warrants more scrutiny than the same flag from an account registered yesterday.

Third, attach evidence to every ban. For movement and combat detections this usually means exporting the relevant log segment. For screen-based detections it means attaching the captured image. For economy detections it means exporting the balance delta timeline. Fourth, document the reviewing staff member and the timestamp. This is the difference between a ban that survives a chargeback or a community dispute and one that does not.

SENTINEL's composite scoring helps with triage by surfacing the highest-risk players first rather than forcing staff to wade through every individual module alert. Understanding how AI co-pilots weight behavioural signals is covered in depth in the behavioural detection explainer.

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