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🧩 How hidden unicode characters can break your system

Introduction While working on a feature that sends notifications to phone numbers, I recently faced one of the trickiest bugs I’ve encountered. Everything looked correct the phone number was valid, the logs seemed fine, and yet the s…

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Introduction



While working on a feature that sends notifications to phone numbers, I recently faced one of the trickiest bugs I’ve encountered. Everything looked correct the phone number was valid, the logs seemed fine, and yet the system kept rejecting the request.



After digging deeper, the culprit turned out to be something almost invisible: hidden Unicode character inside the phone number.



In this article, I’ll explain:




  • What Unicode characters are

  • What hidden Unicode characters are

  • How they can silently break your systems

  • The real bug I faced

  • How I solved it









What Are Unicode Characters?



Computers represent text using numeric codes. Early systems used ASCII, which only supported about 128 characters By using 7 bits to represent each character. Mainly English letters, digits, and basic symbols.



To support all languages, symbols and emojis, the industry adopted the Unicode standard.



Unicode assigns a unique code point to every character.



Examples:




























Character Unicode Code Point
A U+0041
5 U+0035
ع U+0639
😊 U+1F60A


This allows computers to represent text from virtually every language consistently.









Hidden Unicode Characters



Some Unicode characters are not visible when rendered, but they still exist inside the string.



These characters are often used for:




  • text direction control

  • formatting

  • invisible separators



Examples include:



Character Unicode Description

LRM U+200E Left-to-Right Mark

RLM U+200F Right-to-Left Mark

ZWSP U+200B Zero Width Space



These characters can appear when:



copying text from messaging apps



copying from PDFs



user input from multilingual keyboards



some mobile devices






The problem is that they are invisible, but they still affect string processing.






The Bug I Faced



I was sending a request to an external service with a phone number like this: "+2‭12345678"



Everything looked normal, But the API kept rejecting the number.



When I logged the request payload, I saw something strange, At first glance, the number seemed valid.



But there was actually a hidden Unicode character before the digits.



The real string looked like this internally:



\u202D123456789



U+202D is a Left-to-Right Override (LRO) character.



It doesn't display visually, but it changes how text direction is interpreted.



This character was likely introduced when the phone number was copied from a copying from a chat message containing Arabic text or contact list.









Why This Breaks Systems



Most phone number validations expect digits only.



For example:



/^[0-9]+$/



When a hidden Unicode character exists in the string:



\u202D123456789



The regex fails because the string does not actually start with a digit.



So even though the number looks correct, it fails validation.









How I Debugged It



To detect the issue, I inspected the string at the byte level.



In PHP, you can check the raw string representation:



var_dump($phoneNumber);



Or to ensure you could check any online unicode parser i have used this



+2‭12345678 => the one with hidden LTR unicode

+212345678 => the normal number



This revealed the unexpected Unicode character before the digits.









The Solution



The fix was to sanitize the input and remove non-digit characters.



Example:



$phoneNumber = preg_replace('/\D/', '', $phoneNumber);



This removes everything except digits.



Another safe approach is to explicitly remove invisible Unicode characters:



$phoneNumber = preg_replace('/[\x{200B}-\x{200F}\x{202A}-\x{202E}]/u', '', $phoneNumber);



Or simply normalize the phone number before validation.









Key Takeaways



Hidden Unicode characters can silently break systems in ways that are extremely difficult to detect.



Things that can be affected include:




  • phone number validation

  • authentication tokens

  • payment identifiers

  • database lookups



If your system accepts user input, always consider sanitizing and normalizing text before processing it.



Invisible characters might be hiding in plain sight.

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