Arabic AI detector

GPTCleanup Pro's Arabic AI detector reads a passage of Arabic text, fusha or dialect, and reports the patterns typical of AI-generated Arabic writing: register choice, digit set, hamza placement and more, with each signal named rather than folded into one number. It answers the question people actually search, is this Arabic text AI-written, with a breakdown rather than a verdict.

It is a server tool by necessity: the pattern model is too large to run in a browser, so text is sent to our AI server to be scored and the result returned to the page. You get 5 free checks in any rolling 24 hours, no account required.

Arabic carries tells that a detector built around English phrasing habits would never see. No single item below is disqualifying; the read is a function of how many co-occur in one sample.

An all-fusha register

Modern Standard Arabic by default, even where a native writer would shift into dialect. Most everyday Arabic writing happens in Egyptian, Gulf, Levantine or Maghrebi dialect, not fusha.

A single digit set, held throughout

Western numerals, Eastern Arabic-Indic numerals and the Persian and Urdu extended set all appear in genuine Arabic writing. A document that commits to one set for its entire length reads as generated.

Hamza seats with no inconsistency

أ إ ؤ ئ ء sit on distinct seats, and native writers get the harder cases wrong occasionally. Uniformly correct hamza placement across a long passage is unusually clean.

Tatweel absent or misplaced

The elongation mark ـ serves justification and style. Its total absence, or an odd mid-word appearance, is a minor but real signal.

Direction marks carried over

U+200E and U+200F often travel along from copying between right-to-left and left-to-right software, and their distribution differs between an edited document and a raw model export.

One round trip to the server, then a reasoned result.

Step 1

Paste the Arabic sample, dialect or fusha. A longer passage gives the model more structure to weigh.

Step 2

Run the check. The text is sent once to our AI server, scored against the patterns above, and nothing further is done with it.

Step 3

Review each flagged pattern and its stated reasoning. The output is an argument you can inspect, not a number you're asked to trust.

Not with confidence. Models trained predominantly on English carry that shape into Arabic output, defaulting to fusha, Western digits and a narrow set of connectors, so these signals point toward machine-written Arabic broadly rather than any single model specifically.

A prompt requesting dialect, or a particular register, erodes most of this signal in one step. A strong match is grounds for a closer look, not a determination of authorship.

Arabic sits behind English in available training data, and dialectal Arabic sits behind fusha again, so this detector's margins are wider for Arabic than for English, and that limitation should be stated rather than hidden.

Institutional and government Arabic

Official correspondence, and religious or legal writing, default to fusha for reasons unrelated to AI, placing them close to this detector's own default profile.

Machine-translated Arabic

Arabic translated from English by a separate tool commonly reads as stiff, over-formal fusha, the exact shape this detector is calibrated to notice.

Rule-following non-native writers

Fusha is standard Arabic-course material, so a learner following instruction closely produces the same safe, hedge-light Arabic a model defaults to.

A flag from this tool is a signal, not a finding, and that distinction matters more given how thin the underlying Arabic training data still is.

Preserve your drafts

Earlier versions in an Arabic editor or notebook are the clearest evidence a piece was composed, not generated whole.

Document your register choice

Why you wrote fusha, or a particular dialect, is context a generic default cannot supply.

Request the named signal

A specific pattern, a digit set or a hamza seat, can be examined on its own terms. An unexplained score cannot.

Editorial teams screening Arabic submissions, instructors weighing a second opinion on unusually polished fusha, and writers reviewing their own drafts before submission.

5 free checks per rolling 24-hour window, tracked without an account. The window reopens continuously rather than resetting at a fixed hour, which covers ordinary use, one submission, one paragraph under review, without friction.