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  • Motion Highlights #6 | Codrops

    Motion Highlights #6 | Codrops


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  • Monday Sale! 🎁

    Monday Sale! 🎁


    At Browserling and Online Tools we love sales.

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  • Targeting Taiwan & Japan with DLL Implants

    Targeting Taiwan & Japan with DLL Implants


    • Introduction
    • Initial Findings.
    • Infection Chain.
    • Technical Analysis.
      • Stage 1 – Malicious LNK Script.
      • Stage 2 – Malicious Pterois Implant.
      • Stage 3 – Malicious Isurus Implant.
      • Stage 4 – Malicious Cobalt Strike Shellcode.
    • Infrastructure and Hunting.
    • Attribution
    • Conclusion
    • Seqrite Protection.
    • IOCs
    • MITRE ATT&CK.

    Introduction

    Seqrite Labs APT-Team has recently uncovered a campaign which we have termed as Swan Vector, that has been targeting the nations across the East China sea such as Taiwan and Japan. The campaign is aimed at educational institutes and mechanical engineering industry with lures aiming to deliver fake resume of candidates which acts as a decoy.

    The entire malware ecosystem involved in this campaign comprises a total of four stages, the first being one being a malicious LNK, the second stage involves the shortcut file executing DLL implant Pterois via a very well-known LOLBin. It uses stealthy methods to execute and download the third stage containing multiple files including legitimate Windows executable that is further used to execute another implant Isurus via DLL-Sideloading. This further executes the fourth stage that is the malicious Cobalt Strike shellcode downloaded by Pterois.

    In this blog, we’ll explore the sophistication and cover every minutia technical detail of the campaign we have encountered during our analysis. We will examine the various stages of this campaign, starting with the analysis of shortcut (.LNK) file to multiple DLL implants ending with analyzing the shellcode with a final overview.

    Initial Findings

    Recently in April, our team found a malicious ZIP file named as 歐買尬金流問題資料_20250413 (6).rar which can be translated to Oh My God Payment Flow Problem Data – 2025/04/13 (6) , which has been used as preliminary source of infection, containing various files such as one of them being an LNK and other a file with .PNG extension.

    The ZIP contains a malicious LNK file named, 詳細記載提領延遲問題及相關交易紀錄.pdf.lnk. which translates to, “Shortcut to PDF: Detailed Documentation of Withdrawal Delay Issues and Related Transaction Records.pdf.lnk”, which is responsible for running the DLL payload masqueraded as a PNG file known as Chen_YiChun.png. This DLL is then executed via a very well-known LOLBin that is RunDLL32.exe which further downloads other set of implants and a PDF file, which is a decoy.

    Looking into the decoy

    As, the first DLL implant aka Pterois was initially executed via the LOLBin, we saw a decoy file named rirekisho2025 which basically, stands for a nearly Japanese translation for Curriculum Vitae (CV 2025) was downloaded and stored inside the Temp directory along-side other implants and binaries. In the first page, there is a Japanese resume/employment history form “履歴書・職歴経歴書” dated with the Reiwa era format (令和5年4月). The form has a basic header section with fields for personal information including name (氏名), date, gender selection (男/女), birth date, address fields, email address (E-Mail), and contact numbers. There’s also a photo placeholder box in the upper right corner. The decoy appears to be mostly blank with rows for entering education and work history details. Notable fields include entries for different years (月), degree/qualification levels, and employment dates. At the bottom, there are sections for licenses/certifications and additional notes. In the second page, there are two identical sections labeled “職歴 1” and “職歴 2” for employment history entries. Each section contains fields for company name, position, employment dates, and a large notes section. The fields are arranged in a similar layout with spaces for company/organization name (会社・団体名), position title, dates of employment, and work-related details. There’s also a section with red text indicating additional about documents or materials (調査、調査料、ファイル等). In the third and last page, there is one more employment history section “職歴 3” with the same structure as the previous page – company name, position, employment dates, and notes. Below this, there are five additional employment history sections with repeated fields for company name, position, and employment dates, though these appear more condensed than the earlier sections. Each section follows the same pattern of requesting employment-related information in a structured format. Next, we will look into the infection chain and technical analysis.

    Infection Chain.

    Technical Analysis.

    We will break down the technical capabilities of this campaign into four different parts.

    Stage 1 – Malicious LNK Script.

    The ZIP contains a malicious LNK file, known as 詳細記載提領延遲問題及相關交易紀錄.pdf.lnk which translates to Detailed Record of Withdrawal Delay Issues and Related Transaction Records. Another name is also seen with the same LNK as 針對提領系統與客服流程的改進建議.pdf.lnk that translates to Suggestions for Improving the Withdrawal System and Customer Service Process. Creation time of LNK is 2025-03-04. Upon analyzing the contents of this malicious LNK file, we found that its sole purpose is to spawn an instance of the LOLBin rundll32.exe, which is then used to execute a malicious DLL implant named Pterois. The implant’s export function Trpo with an interesting argument 1LwalLoUdSinfGqYUx8vBCJ3Kqq_LCxIg, which we will look into the later part of this technical analysis, on how this argument is being leveraged by the implant.

    Stage 2 – Malicious Pterois Implant.

    Initially, upon examining the malicious RAR archive, along with the malicious LNK file, we found another file with .PNG extension known as Chen_YiChun.png . On doing some initial analysis, we figured out that the file is basically a DLL implant, and we have called it as Pterois. Now, let us examine the technicalities of this implant. While we did analyze the malicious LNK file, we did see that rundll32.exe is used to execute this DLL file’s export function Trpo. Looking inside the implant’s functionalities, it has two primary features, the first one is to perform API Hashing, and the latter is used to download the next stage of malware. The first function is responsible for resolving all APIs from the DLLs like NTDLL, UCRTBase, Kernel32 and other necessary libraries required, and the APIs required for desired functions. This is done by initially accessing the Process Environment Block (PEB) to retrieve the list of loaded modules. The code then traverses this list using the InMemoryOrderModuleList, which contains linked LDR_DATA_TABLE_ENTRY structures — each representing a loaded DLL. Within each LDR_DATA_TABLE_ENTRY, the BaseDllName field (a UNICODE_STRING) holds just the DLL’s filename (e.g., ntdll.dll), and the DllBase field contains its base address in memory.

    During traversal, the function converts the BaseDllName to an ANSI string, normalizes it by converting to uppercase and computes a case-insensitive SDBM hash of the resulting string. This computed hash is compared against a target hash provided to the function. If a match is found, the corresponding DLL’s base address is obtained from the DllBase field and returned. Now, once the DLL’s base address is returned, the code uses a similar case-insensitive SDBM hashing algorithm to resolve API function addresses within NTDLL.DLL. It does this by parsing the DLL’s Export Table, computing the SDBM hash of each exported function name, and comparing it to a target hash to find the matching function address. Here is a simple python script, which evaluates and performs hashing. So, in the first function, a total of four functions have been resolved. Similarly, the APIs for the other two dynamicalliy linked libraries ucrtbase.dll & Kernel32.dll , are being resolved in the same manner. In the next set of functions, where it is trying to resolve the APIs from DLLs like Iphlapi.dll , shell32.dll and WinHTTP.dll, it initially resolves the DLL’s base address just like the previous functions. Once it is returned, then it uses a simple yet pseudo-anti-analysis technique that is using Timer Objects to load these above DLLs. Initially it creates a timer-object using RtlCreateTimerQueue, once the Timer Object is created, then another API RtlCreateTimer is used to run a callback function, which is LoadLibraryW API in this case, further used to load the DLL. Then, the GetModuleHandleW is used to get a handle to the IPHLAPI.DLL. So, once it succeeds, the RtlDeleteTimerQueue API is used to delete and free the Timer Object. Then, finally an API GetAdaptersInfo is resolved via a hash. Similarly, other DLLs are also loaded in the same manner. Next, we will look into the later part of the implant that is the set of functions responsible for downloading the next stager. The function starts with initially getting the entire Command Line parameter comprising of the LOLBin and the argument, that later gets truncated to 1LwalLoUdSinfGqYUx8vBCJ3Kqq_LCxIg which basically is a hardcoded file-ID. Then it uses a technique to abuse Google Drive as a command-and-control server by first establishing authentication with legitimate OAuth credentials. After obtaining a valid access token through a properly formatted OAuth exchange, it uses the Google Drive API to retrieve files from specific hardcoded file IDs, including malicious executables, DLLs, and configuration files which it downloads to predetermined paths in C:\Windows\Temp.

    Then it sets the appropriate Content-Type header to “application/x-www-form-urlencoded” to ensure the request is processed correctly by Google’s authentication servers. Following this exchange, it performs precise JSON parsing capabilities, where it extracts the “access_token” field from Google’s response using cJSON_GetObjectItem. Looking into the memory dump clearly displays the obtained OAuth token beginning with “ya29.a0AZYk”, confirming a successful authentication process. Once this token is parsed and extracted then it is carefully stored and subsequently used to authorize API calls to Google Drive, allowing the implant to download additional payloads while appearing as legitimate traffic from Google Drive. The parsed JSON extracted from the memory looks something like this. Now, once the files are downloaded, another part of this implant uses CreateThread to spawn these downloaded decoy and other files to execute. Finally, these files are downloaded, and the decoy is spawned on the screen and the task of Pterois implant, is done. Well, the last part of this implant is, once the entire task is complete, it goes ahead and performs Self-Delete to cover its tracks and reduce the chance of detection.

    The self-deletion routine uses a delayed execution technique by spawning a cmd.exe process that pings localhost before deleting the file, ensuring the deletion occurs after the current process has completed and released its file handles.

    Next, we will look into the other DLL implant, which has been downloaded by this malicious loader.

    Stage 3 – Malicious Isurus Implant.

    The previous implant downloads a total of four samples. Out of which one of them is a legitimate Windows Signed binary known as PrintDialog.exe. Now, the other file PrintDialog.dll which is the other implant with compilation timestamp 2025-04-08 03:02:59 UTC, is responsible for running the shellcode contents present inside the ra.ini file, abuses a very well-known technique known as DLL-Sideloading by placing the malicious DLL in the current directory as PrintDialog.exe does not explicitly mention the path and this Implant which we call as Isurus performs malicious tasks. Looking, onto the export table, we can see that the malicious implant exports only two functions, one of them being the normal DllEntryPoint and the other being the malicious DllGetActivationFactory export function. Looking inside the export function, we can see that this Isurus performs API resolution via hash along with shellcode extraction and loads and executes the shellcode in memory. The implant initially resolves the APIs by performing the PEB-walking technique, traversing the Process Environment Block (PEB) to locate the base address of needed DLLs such as ntdll.dll and kernel32.dll. Once the base address of a target DLL is identified, the implant proceeds to manually parse the PE (Portable Executable) headers of the DLL to locate the Export Directory Table. Now, to resolve specific APIs, the implant employs a hashing algorithmCRC32. Instead of looking up an export by name, the loader computes a hash of each function name in the export table and compares it to precomputed constants embedded in the code to finally resolve the hashes. Now, let us look into how this implant extracts and loads the shellcode. It initially opens the existing file ra.ini with read permissions using CreateFileW API, then once it gets the handle, another API known as GetFileSize is used to read the size of the file. Once the file size is obtained, it is processed via ReadFile API. Then, using a hardcoded RC4 key wquefbqw the shellcode is then decrypted and returned. After extracting the shellcode, it is executed directly in memory using a syscall-based execution technique. This approach involves loading the appropriate syscall numbers into the EAX register and invoking low-level system calls to allocate memory, write the shellcode, change memory protections, and ultimately execute the shellcode—all without relying on higher-level Windows API functions. The PDB path of this implant also depicts the functionality:

    • C:\Users\test\source\repos\sysldr\x64\Release\weqfdqwefq.pdb

    In the next part, we will look into the malicious shellcode and its workings.

    Stage 4 – Malicious Cobalt Strike Shellcode.

    Upon looking into the file, we figured out that the shellcode is in encrypted format. Next, we decrypted the shellcode using the key, using a simple Python script. Further, on analyzing the shellcode, we found, that it is a Cobalt Strike based beacon. Therefore, here are the extracted configs. Extracted beacon config:

    Process Injection Targets:
    windir\syswow64\bootcfg.exe
    windir\sysnative\bootcfg.exe
    Infrastructural information:
    hxxps://52.199.49.4:7284/jquery-3.3.1.min.js
    hxxps://52.199.49.4:7284/jquery-3.3.2.min.js
    Request Body :
    GET /jquery-3.3.1.min.js HTTP/1.1
    Host: 52.199.49.4:7284
    
    
    User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.122 Safari/537.36
    Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8
    Referer: http://code.jquery.com/
    Accept-Encoding: gzip, deflate
    Cookie: __cfduid=dT98nN_EYDF96RONtS1uMjE0IZIWy9GljNoWh6rXhEndZDFhNo_Ha4AmFQKcUn9C4ZUUqLTAI6-6HUu3jA-WcnuttiUnceIu3FbAlBPitw52PirDxM_nP460iXUlVqW6Lvv__Wr3k09xnyWZN4besu1gVlk3JWS2hX_yt5EioqY
    Connection: Keep-Alive
    Cache-Control: no-cache
    
    
    HTTP Settings GET Hash:
    52407f3c97939e9c8735462df5f7457d
    HTTP Settings POST Hash:
    7c48240b065248a8e23eb02a44bc910a

    Due to the extensive documentation and prevalence of Cobalt Strike in offensive security operations, an in-depth analysis is deemed unnecessary. Nonetheless, available extracted beacon configuration, confirm that the threat actor leveraged Cobalt Strike as a component of their intrusion toolkit in this campaign.

    Infrastructure and Hunting.

    As, we did encounter while reverse-engineering the implants, we found that the threat actor had been using Google-Drive as a command-and-control (C2) framework, which also leaked a lot of details such as sensitive API-keys and much more. We have found the associated details related to the threat actor’s infrastructure such as associated Gmail Address & list of implants, which had been scheduled by the threat actor for other campaigns, which have not been used In-The-Wild (ITW). Information related to Threat Actor’s Google Drive Account: {  “user”: {    “kind”: “drive#user”,    “displayName”: “Swsanavector56”,    “photoLink”: “https://lh3.googleusercontent.com/a/ACg8ocKiv7cWvdPxivqyPdYB70M1QTLrTsWUb-QHii8yNv60kYx8eA=s64”,    “me”: true,    “permissionId”: “09484302754176848006”,    “emailAddress”: “swsanavector42@gmail.com”  }} List of files found inside the Google Drive

    File Name File ID Type Size SHA-256 Hash
    PrintDialog.exe 14gFG2NsJ60CEDsRxE5aXvFN0Fs83YMMG EXE 123,032 bytes 7a942f65e8876aeec0a1372fcd4d53aa1f84d2279904b2b86c49d765e5a29d6f
    PrintDialog.dll 1VMrUQlxvKZZ-fRyQ8m3Ai8ZEhkzE3g5T DLL 108,032 bytes a9b33572237b100edf1d4c7b0a2071d68406e5931ab3957a962fcce4bfc2cc49
    ra.ini 1JAXiUPz6kvzOlokDMDxDhA4ohidt094b INI 265,734 bytes 0f303988e5905dffc3202ad371c3d1a49bd3ea5e22da697031751a80e21a13a7
    rirekisho2025.pdf 17hO28MbwD2assMsmA47UJnNbKB2fpM_A PDF 796,062 bytes 8710683d2ec2d04449b821a85b6ccd6b5cb874414fd4684702f88972a9d4cfdd
    rirekisho2021_01.pdf 1LwalLoUdSinfGqYUx8vBCJ3Kqq_LCxIg PDF 796,062 bytes 8710683d2ec2d04449b821a85b6ccd6b5cb874414fd4684702f88972a9d4cfdd
    wbemcomn.dll 1aY5oX6EIe4hfGD6QgAAzmCcwxM4DoLke DLL 181,760 bytes c7b9ae61046eed01651a72afe7a31de088056f1c1430b368b1acda0b58299e28
    svhost.exe 1P8_PG2DGtLWA3q8F4XPy43GMLznZFtQv EXE 209,920 bytes e0c6f9abfc11911747a7533f3282e7ff0c10fc397129228621bcb3a51f5be980
    0g9pglZr74.ini 1UE7gNfUIuTRzgjIv188hRIZG3YNtbvkV INI 265,734 bytes 9fb57a4c6576a98003de6bf441e4306f72c83f783630286758f5b468abaa105d
    KpEvjK3KG2.enc 1RxJi1RZMhcF31F1lgQ9TJfXMuvSJkYQl ENC 265,734 bytes e86feaa258df14e3023c7a74b7733f0b568cc75092248bec77de723dba52dd12
    LoggingPlatform.dll 1lZgq1ZNkK88eJsl6GlcvpzRuFlBgxEOF DLL 112,640 bytes 9df9bb3c13e4d20a83b0ac453e6a2908b77fc2bf841761b798b903efb2d0f4f7
    0g9pglZr74.ini 1ky1fEzC6v70U8-RbHBZG_i3YI79Ir8Og INI 265,734 bytes 9fb57a4c6576a98003de6bf441e4306f72c83f783630286758f5b468abaa105d
    python310.dll 1RuMLCJJ5hcFiVXbcg8kZK3giueWiVbTJ DLL 189,952 bytes e1b2d0396914f84d27ef780dd6fdd8bae653d721eea523f0ade8f45ac9a10faf
    ra.ini 13ooFQAYZ27Bx015UQG3qkHR293wlcL90 INI 265,734 bytes 777961d51eb92466ca4243fa32143520d49077a3f7c77a2fcbec183ebf975182
    pythonw.exe 19n1ta4hyQguQQmR8C6SAsZuGNQF4-ddU EXE 97,000 bytes 040d121a3179f49cd3f33f4bc998bc8f78b7f560bfd93f279224d69e76a06e92
    python.xml 1k4Q18FByEXW98Rr1CXyVVC-Kj8T0NBDW XML 1,526 bytes c8ed52278ec00a6fbc9697661db5ffbcbe19c5ab331b182f7fd0f9f7249b5896
    OneDriveFileLauncher.exe 137tczdqf5R7RMRoOb9fI_YjZuncd_TUn EXE 392,760 bytes 7bf5e1f3e29beccca7f25d7660545161598befff88506d6e3648b7b438181a75
    wbemcomn.dll 1xUPkhfaWIgYs5HSmxYPC_sZT4QKm_T7i DLL 181,760 bytes c7b9ae61046eed01651a72afe7a31de088056f1c1430b368b1acda0b58299e28
    0g9pglZr74.ini 1Ylpf9XVnztxeGk-joNw9df3b0Mv8wYU3 INI 265,734 bytes 9fb57a4c6576a98003de6bf441e4306f72c83f783630286758f5b468abaa105d
    svhost.exe 1wo1gZ9acixvy925lM6QAkz6Uaj6cRXxx EXE 209,920 bytes e0c6f9abfc11911747a7533f3282e7ff0c10fc397129228621bcb3a51f5be980
    llv 1ZuzB7x0zzgz34eNhHp_TI3auPhHj8Xhc Folder

    We also observed this host-address was being used where the Cobalt-Strike was being hosted under ASN 16509 with location of IP being in Japan. Also, apart from the Google Drive C2, we have also found that the Gmail address has been used to create accounts and perform activities which have currently been removed under multiple platforms like Google Maps, YouTube and Apple based services.

    Attribution.

    While attribution remains a key perspective when analyzing current and future motives of threat actors, we have observed similar modus operandi to this campaign, particularly in terms of DLL sideloading techniques. Previously, the Winnti APT group has exploited PrintDialog.exe using this method. Additionally, when examining the second implant, Isurus, we found some similarities with the codebase used by the Lazarus group, which has employed DLL sideloading techniques against wmiapsrv.exe – a file that was found uploaded to the threat actor’s Google Drive account. Along with which we have found a few similarities between Swan Vector and APT10’s recent targets across Japan & Taiwan.

    While these observations alone do not provide concrete attribution, when combined with linguistic analysis, implant maturity, and other collected artifacts, we are attributing this threat actor to the East Asian geosphere with medium confidence.

    Conclusion.

    Upon analysis and research, we have found that the threat actor is based out of East Asia and have been active since December 2024 targeting multiple hiring-based entities across Taiwan & Japan. The threat actor relies on custom development of implants comprising of downloader, shellcode-loaders & Cobalt Strike as their key tools with heavily relying on multiple evasion techniques like API hashing, Direct-syscalls, function callback, DLL Sideloading and self-deletion to avoid leaving any sort of traces on the target machine.

    We believe that the threat actor will be using the above implants which have been scheduled for upcoming campaigns which will be using DLL sideloading against applications like Python, WMI Performance Adapter Service, One Drive Launcher executable to execute their malicious Cobalt Strike beacon with CV-based decoys.

    Seqrite Protection.

    • Pterois.S36007342.
    • Trojan.49524.GC
    • trojan.49518.GC.

    Indicators-Of-Compromise (IOCs)

    Decoys (PDFs)

    Filename SHA-256
    rirekisho2021_01.pdf 8710683d2ec2d04449b821a85b6ccd6b5cb874414fd4684702f88972a9d4cfdd
    rirekisho2025.pdf 8710683d2ec2d04449b821a85b6ccd6b5cb874414fd4684702f88972a9d4cfdd

    IP/Domains

    Malicious Implants

    Filename SHA-256
    wbemcomn.dll c7b9ae61046eed01651a72afe7a31de088056f1c1430b368b1acda0b58299e28
    LoggingPlatform.dll 9df9bb3c13e4d20a83b0ac453e6a2908b77fc2bf841761b798b903efb2d0f4f7
    PrintDialog.dll a9b33572237b100edf1d4c7b0a2071d68406e5931ab3957a962fcce4bfc2cc49
    python310.dll e1b2d0396914f84d27ef780dd6fdd8bae653d721eea523f0ade8f45ac9a10faf
    Chen_YiChun.png de839d6c361c7527eeaa4979b301ac408352b5b7edeb354536bd50225f19cfa5
    針對提領系統與客服流程的改進建議.pdf.lnk 9c83faae850406df7dc991f335c049b0b6a64e12af4bf61d5fb7281ba889ca82

    Shellcode and other suspicious binaries

    Filename SHA-256
    0g9pglZr74.ini 9fb57a4c6576a98003de6bf441e4306f72c83f783630286758f5b468abaa105d
    ra.ini 0f303988e5905dffc3202ad371c3d1a49bd3ea5e22da697031751a80e21a13a7
    python.xml c8ed52278ec00a6fbc9697661db5ffbcbe19c5ab331b182f7fd0f9f7249b5896
    KpEvjK3KG2.enc e86feaa258df14e3023c7a74b7733f0b568cc75092248bec77de723dba52dd12

    MITRE ATT&CK.

    Tactic Technique ID Technique Name Sub-technique ID Sub-technique Name
    Initial Access T1566 Phishing T1566.001 Spearphishing Attachment
    Execution T1129 Shared Modules
    Execution T1106 Native API
    Execution T1204 User Execution T1204.002 Malicious File
    Persistence T1574 Hijack Execution Flow T1574.001 DLL Sideloading
    Privilege Escalation T1055 Process Injection T1055.003 Thread Execution Hijacking
    Privilege Escalation T1055 Process Injection T1055.004 Asynchronous Procedure Call
    Defense Evasion T1218 System Binary Proxy Execution T1218.011 Rundll32
    Defense Evasion T1027 Obfuscated Files or Information T1027.007 Dynamic API Resolution
    Defense Evasion T1027 Obfuscated Files or Information T1027.012 LNK Icon Smuggling
    Defense Evasion T1027 Obfuscated Files or Information T1027.013 Encrypted/Encoded File
    Defense Evasion T1070 Indicator Removal T1070.004 File Deletion
    Command and Control T1102 Web Service

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  • PHP 8.3 new features

    PHP 8.3 new features


    PHP 8.3 introduces several new features and improvements to enhance performance and the developer experience. Dive into the latest PHP 8.3 release and discover the new features set to revolutionize how developers build applications. From read-only properties to disjoint unions, learn how these enhancements can help you write more efficient and maintainable code while boosting overall performance.

    Here are some of the most significant updates:

    1. Readonly Properties for Classes.

    • Feature: PHP 8.3 introduces read-only properties that can only be assigned once, typically in the constructor.
    • Benefit: This enforces immutability for properties, which can help prevent accidental modifications and make the code easier to reason about.
    • Example
    class User {
        public readonly string $name;
    
        public function __construct(string $name) {
            $this->name = $name;
        }
    }
    
    $user = new User("Alice");
    // $user->name = "Bob"; // This will throw an error
    
    
    • Performance Impact: Immutable objects can lead to performance benefits by reducing the need for defensive copying and allowing for better optimization by the engine.

    2. Disjoint Unions

    • Feature: PHP 8.3 introduces disjoint unions, allowing developers to declare that a property or return type can be of one type or another, but not a common subtype.
    • Benefit: This adds more precision in type declarations, improving type safety and reducing potential bugs.
    • Example
    function process(mixed $input): int|string {
    if (is_int($input)) {
    return $input * 2;
    }
    if (is_string($input)) {
    return strtoupper($input);
    }
    throw new InvalidArgumentException();
    }

    3. json_validate() Function

    • Feature: A new json_validate() function is introduced, which allows developers to check if a string contains valid JSON without decoding it.
    • Benefit: This is useful for validating large JSON strings without the overhead of decoding them.
    • Example
    $jsonString = '{"name": "Alice", "age": 25}';
    if (json_validate($jsonString)) {
    echo "Valid JSON!";
    } else {
    echo "Invalid JSON!";
    }

    4. Typed Class Constants

    • Feature: PHP 8.3 allows class constants to have types, just like class properties.
    • Benefit: This feature enforces type safety for constants, reducing bugs caused by incorrect types.
    • Example
    class Config {
    public const int MAX_USERS = 100;
    }

    5. Improved Performance

    • JIT Improvements: PHP 8.3 includes enhancements to the Just-In-Time (JIT) compiler introduced in PHP 8.0. These improvements lead to faster execution of some workloads, especially those that are CPU-intensive.
    • Faster Hash Table Operations: Internal improvements have been made to how hash tables (the underlying structure for arrays and many other data structures) are handled, resulting in faster array operations and reduced memory usage.

    6. Enhanced Error Reporting

    • Feature: Error reporting has been improved with more precise messages and additional context, helping developers diagnose issues faster.
    • Benefit: Better error messages lead to quicker debugging and a smoother development experience.

    7. New Random\Engine  Class

    • Feature: PHP 8.3 introduces the Random\Engine class, which provides a standard way to generate random numbers using different engines.
    • Benefit: This adds more control over random number generation and allows for better customization, especially in cryptographic or statistical applications.
    • Example:
    $engine = new Random\Engine\Mt19937();
    $random = new Random\Randomizer($engine);
    echo $random->getInt(1, 100); // Random number between 1 and 100

    Conclusion

    PHP 8.3 brings a mix of new features, performance improvements, and developer experience enhancements. These changes help developers write more robust, efficient, and maintainable code, while also taking advantage of performance optimizations under the hood. The introduction of readonly properties, disjoint unions, and typed class constants, along with improvements in JIT and error reporting, are particularly impactful in making PHP a more powerful and developer-friendly language.



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  • Integrating Rive into a React Project: Behind the Scenes of Valley Adventures

    Integrating Rive into a React Project: Behind the Scenes of Valley Adventures


    Bringing new tools into a workflow is always exciting—curiosity bumps up against the comfort of familiar methods. But when our longtime client, Chumbi Valley, came to us with their Valley Adventures project, we saw the perfect opportunity to experiment with Rive and craft cartoon-style animations that matched the playful spirit of the brand.

    Rive is a powerful real-time interactive design tool with built-in support for interactivity through State Machines. In this guide, we’ll walk you through how we integrated a .riv file into a React environment and added mouse-responsive animations.

    We’ll also walk through a modernized integration method using Rive’s newer Data Binding feature—our current preferred approach for achieving the same animation with less complexity and greater flexibility.

    Animation Concept & File Preparation

    Valley Adventures is a gamified Chumbi NFT staking program, where magical creatures called Chumbi inhabit an enchanted world. The visual direction leans heavily into fairytale book illustrations—vibrant colors, playful characters, and a whimsical, cartoon-like aesthetic.

    To immediately immerse users in this world, we went with a full-section hero animation on the landing page. We split the animation into two parts:

    • an idle animation that brings the scene to life;
    • a cursor-triggered parallax effect, adding depth and interactivity.

    Several elements animate simultaneously—background layers like rustling leaves and flickering fireflies, along with foreground characters that react to movement. The result is a dynamic, storybook-like experience that invites users to explore.

    The most interesting—and trickiest—part of the integration was tying animations to mouse tracking. Rive provides a built-in way to handle this: by applying constraints with varying strengths to elements within a group that’s linked to Mouse Tracking, which itself responds to the cursor’s position.

    However, we encountered a limitation with this approach: the HTML buttons layered above the Rive asset were blocking the hover state, preventing it from triggering the animation beneath.

    To work around this, we used a more robust method that gave us finer control and avoided those problems altogether. 

    Here’s how we approached it:

    1. Create four separate timelines, each with a single keyframe representing an extreme position of the animation group:
      • Far left
      • Far right
      • Top
      • Bottom
    2. Add two animation layers, each responsible for blending between opposite keyframes:
      • Layer 1 blends the far-left and far-right timelines
      • Layer 2 blends the top and bottom timelines
    3. Tie each layer’s blend amount to a numeric input—one for the X axis, one for the Y axis.

    By adjusting the values of these inputs based on the cursor’s position, you can control how tightly the animation responds on each axis. This approach gives you a smoother, more customizable parallax effect—and prevents unexpected behavior caused by overlapping UI.

    Once the animation is ready, simply export it as a .riv file—and leave the rest of the magic to the devs.

    How We Did It: Integrating a Rive File into a React Project

    Before we dive further, let’s clarify what a .riv file actually is.

    A .riv file is the export format from the Rive editor. It can include:

    • vector graphics,
    • timeline animations,
    • a State Machine with input parameters.

    In our case, we’re using a State Machine with two numeric inputs: Axis_X and Axis_Y. These inputs are tied to how we control animation in Rive, using values from the X and Y axes of the cursor’s position.

    These inputs drive the movement of different elements—like the swaying leaves, fluttering fireflies, and even subtle character reactions—creating a smooth, interactive experience that responds to the user’s mouse.

    Step-by-Step Integration

    Step 1: Install the Rive React runtime

    Install the official package:

    npm install @rive-app/react-canvas

    Step 2: Create an Animation Component

    Create a component called RiveBackground.tsx to handle loading and rendering the animation.

    Step 3: Connect animation

    const { rive, setCanvasRef, setContainerRef } = useRive({
      src: 'https://cdn.rive.app/animations/hero.riv',
      autoplay: true,
      layout: new Layout({ fit: Fit.Cover, alignment: Alignment.Center }),
      onLoad: () => setIsLoaded(true),
      enableRiveAssetCDN: true,
    });
    

    For a better understanding, let’s take a closer look at each prop you’ll typically use when working with Rive in React:

    What each option does:

    Property Description
    src Path to your .riv file — can be local or hosted via CDN
    autoplay Automatically starts the animation once it’s loaded
    layout Controls how the animation fits into the canvas (we’re using Cover and Center)
    onLoad Callback that fires when the animation is ready — useful for setting isLoaded
    enableRiveAssetCDN Allows loading of external assets (like fonts or textures) from Rive’s CDN

    Step 4: Connect State Machine Inputs

    const numX = useStateMachineInput(rive, 'State Machine 1', 'Axis_X', 0);
    const numY = useStateMachineInput(rive, 'State Machine 1', 'Axis_Y', 0);

    This setup connects directly to the input values defined inside the State Machine, allowing us to update them dynamically in response to user interaction.

    • State Machine 1 — the name of your State Machine, exactly as defined in the Rive editor
    • Axis_X and Axis_Y — numeric inputs that control movement based on cursor position
    • 0 — the initial (default) value for each input

    ☝️ Important: Make sure your .riv file includes the exact names: Axis_X, Axis_Y, and State Machine 1. These must match what’s defined in the Rive editor — otherwise, the animation won’t respond as expected.

    Step 5: Handle Mouse Movement

    useEffect(() => {
      if (!numX || !numY) return;
    
      const handleMouseMove = (e: MouseEvent) => {
        const { innerWidth, innerHeight } = window;
        numX.value = (e.clientX / innerWidth) * 100;
        numY.value = 100 - (e.clientY / innerHeight) * 100;
      };
    
      window.addEventListener('mousemove', handleMouseMove);
      return () => window.removeEventListener('mousemove', handleMouseMove);
    }, [numX, numY]);

    What’s happening here:

    • We use clientX and clientY to track the mouse position within the browser window.
    • The values are normalized to a 0–100 range, matching what the animation expects.
    • These normalized values are then passed to the Axis_X and Axis_Y inputs in the Rive State Machine, driving the interactive animation.

    ⚠️ Important: Always remember to remove the event listener when the component unmounts to avoid memory leaks and unwanted behavior. 

    Step 6: Cleanup and Render the Component

    useEffect(() => {
      return () => rive?.cleanup();
    }, [rive]);

    And the render:

    return (
      <div
        ref={setContainerRef}
        className={`rive-container ${className ?? ''} ${isLoaded ? 'show' : 'hide'}`}
      >
        <canvas ref={setCanvasRef} />
      </div>
    );
    • cleanup() — frees up resources when the component unmounts. Always call this to prevent memory leaks.
    • setCanvasRef and setContainerRef — these must be connected to the correct DOM elements in order for Rive to render the animation properly.

    And here’s the complete code:

    import {
      useRive,
      useStateMachineInput,
      Layout,
      Fit,
      Alignment,
    } from '@rive-app/react-canvas';
    import { useEffect, useState } from 'react';
    
    export function RiveBackground({ className }: { className?: string }) {
      const [isLoaded, setIsLoaded] = useState(false);
    
      const { rive, setCanvasRef, setContainerRef } = useRive({
        src: 'https://cdn.rive.app/animations/hero.riv',
        animations: ['State Machine 1','Timeline 1','Timeline 2'
    ],
        autoplay: true,
        layout: new Layout({ fit: Fit.Cover, alignment: Alignment.Center }),
        onLoad: () => setIsLoaded(true),
        enableRiveAssetCDN: true,
      });
    
      const numX = useStateMachineInput(rive, 'State Machine 1', 'Axis_X', 0);
      const numY = useStateMachineInput(rive, 'State Machine 1', 'Axis_Y', 0);
    
      useEffect(() => {
        if (!numX || !numY) return;
    
        const handleMouseMove = (e: MouseEvent) => {
    	if (!numX || !numY) {
            return;
          }
    
          const { innerWidth, innerHeight } = window;
          numX.value = (e.clientX / innerWidth) * 100;
          numY.value = 100 - (e.clientY / innerHeight) * 100;
        };
    
        window.addEventListener('mousemove', handleMouseMove);
        return () => window.removeEventListener('mousemove', handleMouseMove);
      }, [numX, numY]);
    
      useEffect(() => {
        return () => {
          rive?.cleanup();
        };
      }, [rive]);
    
      return (
        <div
          ref={setContainerRef}
          className={`rive-container ${className ?? ''} ${isLoaded ? 'show' : 'hide'}`}
        >
          <canvas ref={setCanvasRef} />
        </div>
      );
    }
    

    Step 7: Use the Component

    Now you can use the RiveBackground like any other component:

    <RiveBackground className="hero-background" />

    Step 8: Preload the WASM File

    To avoid loading the .wasm file at runtime—which can delay the initial render—you can preload it in App.tsx:

    import riveWASMResource from '@rive-app/canvas/rive.wasm';
    
    <link
      rel="preload"
      href={riveWASMResource}
      as="fetch"
      crossOrigin="anonymous"
    />

    This is especially useful if you’re optimizing for first paint or overall performance.

    Simple Parallax: A New Approach with Data Binding

    In the first part of this article, we used a classic approach with a State Machine to create the parallax animation in Rive. We built four separate animations (top, bottom, left, right), controlled them using input variables, and blended their states to create smooth motion. This method made sense at the time, especially before Data Binding support was introduced.

    But now that Data Binding is available in Rive, achieving the same effect is much simpler—just a few steps. Data binding in Rive is a system that connects editor elements to dynamic data and code via view models, enabling reactive, runtime-driven updates and interactions between design and development.

    In this section, we’ll show how to refactor the original Rive file and code using the new approach.

    Updating the Rive File

    1. Remove the old setup:
      • Go to the State Machine.
      • Delete the input variables: top, bottom, left, right.
      • Remove the blending states and their associated animations.
    2. Group the parallax layers:
      • Wrap all the parallax layers into a new group—e.g., ParallaxGroup.
    3. Create binding parameters:
      • Select ParallaxGroup and add:
        • pointerX (Number)
        • pointerY (Number)
    4. Bind coordinates:
      • In the properties panel, set:
        • X → pointerX
        • Y → pointerY

    Now the group will move dynamically based on values passed from JavaScript.

    The Updated JS Code

    Before we dive into the updated JavaScript, let’s quickly define an important concept:

    When using Data Binding in Rive, viewModelInstance refers to the runtime object that links your Rive file’s bindable properties (like pointerX or pointerY) to your app’s logic. In the Rive editor, you assign these properties to elements like positions, scales, or rotations. At runtime, your code accesses and updates them through the viewModelInstance—allowing for real-time, declarative control without needing a State Machine.

    With that in mind, here’s how the new setup replaces the old input-driven logic:

    import { useRive } from '@rive-app/react-canvas';
    import { useEffect, useState } from 'react';
    
    export function ParallaxEffect({ className }: { className?: string }) {
      const [isLoaded, setIsLoaded] = useState(false);
    
      const { rive, setCanvasRef, setContainerRef } = useRive({
        src: 'https://cdn.rive.app/animations/hero.riv',
        autoplay: true,
        autoBind: true,
        onLoad: () => setIsLoaded(true),
      });
    
      useEffect(() => {
        if (!rive) return;
    
        const vmi = rive.viewModelInstance;
        const pointerX = vmi?.number('pointerX');
        const pointerY = vmi?.number('pointerY');
    
        if (!pointerX || !pointerY) return;
    
        const handleMouseMove = (e: MouseEvent) => {
          const { innerWidth, innerHeight } = window;
          const x = (e.clientX / innerWidth) * 100;
          const y = 100 - (e.clientY / innerHeight) * 100;
          pointerX.value = x;
          pointerY.value = y;
        };
    
        window.addEventListener('mousemove', handleMouseMove);
    
        return () => {
          window.removeEventListener('mousemove', handleMouseMove);
          rive.cleanup();
        };
      }, [rive]);
    
      return (
        <div
          ref={setContainerRef}
          className={`rive-container ${className ?? ''} ${isLoaded ? 'show' : 'hide'}`}
        >
          <canvas ref={setCanvasRef} />
        </div>
      );
    }

    The Result

    You get the same parallax effect, but:

    • without input variables or blending;
    • without a State Machine;
    • with simple control via the ViewModel.

    Official Live Example from Rive

    👉 CodeSandbox: Data Binding Parallax

    Conclusion

    Data Binding is a major step forward for interactive Rive animations. Effects like parallax can now be set up faster, more reliably, and with cleaner logic. We strongly recommend this approach for new projects.

    Final Thoughts

    So why did we choose Rive over Lottie for this project?

    • Interactivity: With Lottie, achieving the same level of interactivity would’ve required building a custom logic layer from scratch. With Rive, we got that behavior baked into the file—plug and play.
    • Optimization: Rive gives you more control over each asset inside the .riv file, and the output tends to be lighter overall.

    Our biggest takeaway? Don’t be afraid to experiment with new tools—especially when they feel like the right fit for your project’s concept. Rive matched the playful, interactive vibe of Valley Adventures perfectly, and we’re excited to keep exploring what it can do.



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  • Data Discovery and Classification for Modern Enterprises

    Data Discovery and Classification for Modern Enterprises


    In today’s high-stakes digital arena, data is the lifeblood of every enterprise. From driving strategy to unlocking customer insights, enterprises depend on data like never before. But with significant volume comes great vulnerability.

    Imagine managing a massive warehouse without labels, shelves, or a map. That’s how most organizations handle their data today—scattered across endpoints, servers, SaaS apps, and cloud platforms, much of it unidentified and unsecured. This dark, unclassified data is inefficient and dangerous.

    At Seqrite, the path to resilient data privacy and governance begins with two foundational steps: Data Discovery and Classification.

    Shedding Light on Dark Data: The Discovery Imperative

    Before protecting your data, you need to know what you have and where it resides. That’s the core of data discovery—scanning your digital landscape to locate and identify every piece of information, from structured records in databases to unstructured files in cloud folders.

    Modern Privacy tools leverage AI and pattern recognition to unearth sensitive data, whether it’s PII, financial records, or health information, often hidden in unexpected places. Shockingly, nearly 75% of enterprise data remains unused, mainly because it goes undiscovered.

    Without this visibility, every security policy and compliance program stands on shaky ground.

    Data Classification: Assigning Value and Implementing Control

    Discovery tells you what data you have. Classification tells you how to treat it.

    Is it public? Internal? Confidential? Restricted? Classification assigns your data a business context and risk level so you can apply the right protection, retention, and sharing rules.

    This is especially critical in industries governed by privacy laws like GDPR, DPDP Act, and HIPAA, where treating all data the same is both inefficient and non-compliant.

    With classification in place, you can:

    • Prioritize protection for sensitive data
    • Automate DLP and encryption policies
    • Streamline responses to individual rights requests
    • Reduce the clutter of ROT (redundant, obsolete, trivial) data

    The Power of Discovery + Classification

    Together, discovery and classification form the bedrock of data governance. Think of them as a radar system and rulebook:

    • Discovery shows you the terrain.
    • Classification helps you navigate it safely.

    When integrated into broader data security workflows – like Zero Trust access control, insider threat detection, and consent management – they multiply the impact of every security investment.

    Five Reasons Enterprises Can’t Ignore this Duo

    1. Targeted Security Where It Matters Most

    You can’t secure what you can’t see. With clarity on your sensitive data’s location and classification, you can apply fine-tuned protections such as encryption, role-based access, and DLP—only where needed. That reduces attack surfaces and simplifies security operations.

    1. Compliance Without Chaos

    Global data laws are demanding and constantly evolving. Discovery and classification help you prove accountability, map personal data flows, and respond to rights requests accurately and on time.

    1. Storage & Cost Optimization

    Storing ROT data is expensive and risky. Discovery helps you declutter, archive, or delete non-critical data while lowering infrastructure costs and improving data agility.

    1. Proactive Risk Management

    The longer a breach goes undetected, the more damage it does. By continuously discovering and classifying data, you spot anomalies and vulnerabilities early; well before they spiral into crises.

    1. Better Decisions with Trustworthy Data

    Only clean, well-classified data can fuel accurate analytics and AI. Whether it’s refining customer journeys or optimizing supply chains, data quality starts with discovery and classification.

    In Conclusion, Know your Data, Secure your Future

    In a world where data is constantly growing, moving, and evolving, the ability to discover and classify is a strategic necessity. These foundational capabilities empower organizations to go beyond reactive compliance and security, helping them build proactive, resilient, and intelligent data ecosystems.

    Whether your goal is to stay ahead of regulatory demands, reduce operational risks, or unlock smarter insights, it all starts with knowing your data. Discovery and classification don’t just minimize exposure; they create clarity, control, and confidence.

    Enterprises looking to take control of their data can rely on Seqrite’s Data Privacy solution, which delivers powerful discovery and classification capabilities to turn information into an advantage.



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  • Yelp Help Viewer Security Flaw in GNOME Linux Systems

    Yelp Help Viewer Security Flaw in GNOME Linux Systems


    Yelp is the default help browser in GNOME-based Linux distributions, including widely used systems such as Ubuntu, Fedora and Debian etc. It is responsible for rendering help documentation written in the Mallard XML format and integrates tightly with the desktop environment via the ghelp:// URI scheme. This integration allows applications and users to open help topics directly using protocol links, making Yelp a core utility for accessing user guides and documentation.

    A vulnerability was recently discovered in Yelp that allows it to process specially crafted help documents in unsafe ways. This flaw, identified as CVE-2025-3155, can be exploited to execute arbitrary scripts embedded within help files, potentially leading to the exposure of sensitive user data to external systems.

    Vulnerability Overview

    CVE-2025-3155 is a vulnerability in Yelp, the GNOME help browser, related to its handling of help documents written in the Mallard XML format.

    An attacker can craft a malicious .page file that uses XInclude to embed the contents of arbitrary local files—such as /etc/passwd or private SSH keys—directly into the displayed help content. If the user opens this file in Yelp, the referenced file is read and rendered within the interface, leading to local file disclosure.

    An attacker may also embed SVG elements containing JavaScript within the crafted help file. When processed by Yelp, these scripts can be executed as part of the rendering process, enabling the exfiltration of included file content to an external server. The vulnerability affects Yelp versions up to 42.1 and has been confirmed on GNOME-based distributions such as Ubuntu 22.04.

    Attack Flow

    The exploitation of CVE-2025-3155 involves delivering a malicious Mallard .page help file to the victim and leveraging Yelp’s behaviour to access and potentially leak sensitive local files. The process can be broken down into the following steps:

    Craft and Host the Malicious File

    The attacker creates a malicious .page file containing an XInclude directive to reference sensitive local files and embeds SVG-based JavaScript for exfiltration. This file is then hosted on a web page under the attacker’s control.

    Placing the File on the Victim’s System
    Through social engineering or a drive-by download technique, the attacker delivers the crafted file to a user-writable directory on the victim’s system. 

    Trigger Yelp via the ghelp URI Scheme

    The attacker leads the victim to a crafted ghelp:// link that references the previously downloaded malicious page file. When accessed, Yelp opens the file for processing.

    Yelp Processes and Exfiltrates Content

    When Yelp opens the page file, it processes the XInclude directive and reads content from the specified local files. In an attack scenario where the file contains embedded SVG scripting, the extracted data can be exfiltrated to an attacker-controlled server.

     

    Figure 1: Attack sequence demonstrating how an adversary leverages Yelp’s help file handling to read and exfiltrate sensitive files.

    Real-World Consequences

    CVE-2025-3155 highlights a significant weakness in how user-facing applications like Yelp process local help content. This flaw has the potential to enable attackers to exfiltrate sensitive user files such as SSH private keys or password stores. In targeted environments, such as hospitality, entertainment, or enterprise Linux workstations, exploitation of this vulnerability could:

    • Lead to unauthorized access to confidential files and credentials.
    • Serve as an early-stage foothold for lateral movement in broader attack campaigns.
    • Facilitate deployment of backdoors or data-stealing malware.
    • Precede or support larger cyberattacks carried out by advanced threat actors.

    Evidence from recent cyber threat reports suggests this vulnerability has already been leveraged by threat groups in targeted industries.

     

    Countermeasures for CVE-2025-3155

    To safeguard Linux systems and users against exploitation of this vulnerability, the following countermeasures are strongly recommended:

    Update Yelp Immediately: Ensure Yelp is updated to version 42.2 or later, where the vulnerability is patched.

    Restrict ghelp:// URI Usage: Avoid launching help files from untrusted sources or links. Consider limiting the exposure of ghelp:// handlers via URI sandboxing or policy enforcement.

    Harden File Access Permissions: Limit read permissions for sensitive files like ~/.ssh/id_rsa and other secrets. Regularly audit user permissions and use encrypted key storage wherever possible.

    Monitor Yelp Behaviour: Although monitoring is not a primary mitigation, security teams may choose to audit Yelp usage for post-exploitation indicators. Abnormal patterns—such as Yelp accessing sensitive files or initiating network connections—could signal an attempted abuse of the vulnerability. This should be used as part of broader endpoint visibility, not as a standalone defence.

     Educate End Users: Inform users about the risks of opening help files from unknown sources and recognize spoofed support documentation. Implement awareness campaigns that treat .page files as potentially harmful.

    By combining patch management with proactive monitoring and user education, organizations can mitigate the risks posed by CVE-2025-3155 and prevent it from being used as a stepping stone in larger attack chains.

    Conclusion

    CVE-2025-3155 demonstrates how functionality intended for local documentation rendering can become a vector for unintended data exposure. By leveraging features like XInclude and URI-based invocation, an attacker can craft a low-interaction exploitation chain capable of disclosing sensitive files and exfiltrating them without explicit user consent. This case underscores the importance of strict content handling in local applications and reinforces the need for timely updates and user vigilance against unfamiliar file types and protocol-driven links.

    References:

    https://gitlab.gnome.org/GNOME/yelp/-/issues/221

     

    Authors:

    Vinay Kumar

    Adrip Mukherjee

     

     



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  • Sunday Sale! 50% OFF! ☀️

    Sunday Sale! 50% OFF! ☀️


    At Browserling and Online Tools, we love sales.

    We just created a new automated Sunday Sale.

    Now each week on Sunday, we show a 50% discount offer to all users who visit our site.

    Buy Now!

    What Is Browserling?

    Browserling is an online service that lets you test how other websites look and work in different web browsers, like Chrome, Firefox, or Safari, without needing to install them. It runs real browsers on real machines and streams them to your screen, kind of like remote desktop but focused on browsers. This helps web developers and regular users check for bugs, suspicious links, and weird stuff that happens in certain browsers. You just go to Browserling, pick a browser and version, and then enter the site you want to test. It’s quick, easy, and works from your browser with no downloads or installs.

    What Are Online Tools?

    Online Tools is a website that offers free, browser-based productivity tools for everyday tasks like editing text, converting files, editing images, working with code, and way more. It’s an all-in-one Digital Swiss Army Knife with 1500+ utilities, so you can find the exact tool you need without installing anything. Just open the site, use what you need, and get things done fast.

    Who Uses Browserling and Online Tools?

    Browserling and Online Tools are used by millions of regular internet users, developers, designers, students, and even Fortune 100 companies. Browserling is handy for testing websites in different browsers without having to install them. Online Tools are used for simple tasks like resizing or converting images, or even fixing small file problems quickly without downloading any apps.

    Buy a subscription now and see you next time!



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  • Rule of 72 – Useful code

    Rule of 72 – Useful code


    Ever heard of the Rule of 72? It’s a classic finance shortcut that tells you how many years it takes for an investment to double at a given interest rate—without reaching for a calculator! Pretty much, if you want to understand when you are going to double your money, that are growing with 7% per year, then simply divide 72 by 7 and see the approximate answer. It works like that and it is approximately ok, for values between 5 and 10%.

    For all other values, the formula looks like this:

    ln(2) is approximately 0.693. Hence, it is 0.693 divided by ln(1+tiny percentage).

    With Python the formula looks like this:

    If you want to see how exact the formula is, then a good comparison vs the exact value looks like this:

    The execution of the code from above like this:

    The YT video, explaining the code and is here:

    https://www.youtube.com/watch?v=BURstTrQWkA

    The GitHub code is here: https://github.com/Vitosh/Python_personal/tree/master/YouTube/023_Python-Rule-of-72

    A nice picture from Polovrak Peak, Bulgaria

    Enjoy!



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  • 6.47 Million Google Clicks! 💰

    6.47 Million Google Clicks! 💰


    Yesterday Online PNG Tools smashed through 6.46M Google clicks and today it’s smashed through 6.47M Google clicks! That’s 10,000 new clicks in a single day – the smash train keeps on rollin’!

    What Are Online PNG Tools?

    Online PNG Tools offers a collection of easy-to-use web apps that help you work with PNG images right in your browser. It’s like a Swiss Army Knife for anything PNG-related. On this site, you can create transparent PNGs, edit icons, clean up logos, crop stamps, change colors of signatures, and customize stickers – there’s a tool for it all. The best part is that you don’t need to install anything or be a graphic designer. All tools are made for regular people who just want to get stuff done with their images. No sign-ups, no downloads – just quick and easy PNG editing tools.

    Who Created Online PNG Tools?

    Online PNG Tools were created by me and my team at Browserling. We’ve build simple, browser-based tools that anyone can use without needing to download or install anything. Along with PNG tools, we also work on cross-browser testing to help developers make sure their websites work great on all web browsers. Our mission is to make online tools that are fast, easy to use, and that are helpful for everyday tasks like editing icons, logos, and signatures.

    Who Uses Online PNG Tools?

    Online PNG Tools and Browserling are used by everyone – from casual users to professionals and even Fortune 100 companies. Casual users often use them to make memes, edit profile pictures, or remove backgrounds. Professionals use them to clean up logos, design icons, or prepare images for websites and apps.

    Smash too and see you tomorrow at 6.48M clicks! 📈

    PS. Use coupon code SMASHLING for a 30% discount on these tools at onlinePNGtools.com/pricing. 💸



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