InQL – A Burp Extension For GraphQL Security Testing

Original text by Andrea Brancaleoni (@nJoyneerthypon)

A security testing tool to facilitate GraphQL technology security auditing efforts.

InQL can be used as a stand-alone script or as a Burp Suite extension.

InQL Stand-Alone CLI
Running inql from Python will issue an Introspection query to the target GraphQL endpoint in order fetch metadata information for:

  • Queries, mutations, subscriptions
  • Its fields and arguments
  • Objects and custom object types

InQL can inspect the introspection query results and generate clean documentation in different formats such as HTML and JSON schema. InQL is also able to generate templates (with optional placeholders) for all known basic data types.
For all supported options, check the command line help:

usage: inql [-h] [--nogui] [-t TARGET] [-f SCHEMA_JSON_FILE] [-k KEY]
            [-p PROXY] [--header HEADERS HEADERS] [-d] [--generate-html]
            [--generate-schema] [--generate-queries] [--insecure]
            [-o OUTPUT_DIRECTORY]
InQL Scanner
optional arguments:
-h, --help show this help message and exit
--nogui Start InQL Without Standalone GUI [Jython-only]
-t TARGET Remote GraphQL Endpoint (https://<Target_IP>/graphql)
-f SCHEMA_JSON_FILE Schema file in JSON format
-k KEY API Authentication Key
-p PROXY IP of web proxy to go through (
-d Replace known GraphQL arguments types with placeholder
values (useful for Burp Suite)
--generate-html Generate HTML Documentation
--generate-schema Generate JSO N Schema Documentation
--generate-queries Generate Queries
--insecure Accept any SSL/TLS certificate
-o OUTPUT_DIRECTORY Output Directory

InQL Burp Suite Extension
Since version 1.0.0 of the tool, InQL was extended to operate within Burp Suite. In this mode, the tool will retain all the capabilities of the stand-alone script and add a handy user interface for manipulating queries.
Using the inql extension for Burp Suite, you can:

  • Search for known GraphQL URL paths; the tool will grep and match known values to detect GraphQL endpoints within the target website
  • Search for exposed GraphQL development consoles (GraphiQLGraphQL Playground, and other common consoles)
  • Use a custom GraphQL tab displayed on each HTTP request/response containing GraphQL
  • Leverage the templates generation by sending those requests to Burp’s Repeater tool (“Send to Repeater”)
  • Leverage the templates generation and editor support by sending those requests to embedded GraphIQL (“Send to GraphiQL”)
  • Configure the tool by using a custom settings tab

To use inql in Burp Suite, import the Python extension:

  • Download the Jython Jar
  • Start Burp Suite
  • Extender Tab > Options > Python Enviroment > Set the location of Jython standalone JAR
  • Extender Tab > Extension > Add > Extension Type > Select Python
  • Download the latest release here
  • Extension File > Set the location of > Next
  • The output should now show the following message: InQL Scanner Started!

In the future we might consider integrating the extension within Burp’s BApp Store.

Burp Extension Usage
Getting started with the inql Burp extension is easy:

  1. Load a GraphQL endpoint or a JSON schema file location inside the top input field
  2. Press the “Load” button
  3. After few seconds, the left panel will refresh loading the directory structure for the selected endpoint as in the following example:
  • url
    • query
      • timestamp 1
        • query1.query
        • query2.query
      • timestamp 2
        • query1.query
        • query2.query
    • mutation
    • subscription
  1. Selecting any query/mutation/subscription will load the corresponding template in the main text area

InQL Stand-Alone UI
Since version 2.0.0, InQL UI is now able to operate without requiring BURP. It is now possible to install InQL stand-alone for jython and run the Scanner UI.
In this mode InQL maintains most of the Burp Scanner capabilities with the exception of advanced interactions such as “Send To Repeater” and automatic authorization header generation, available through BURP.
To use inql stand-alone UI:

  • Download and Install Jython. This can be obtained on macOS through brew brew install jython or on Ubuntu derivates through apt-get install -y jython
  • Install inql through pip with jython -m pip install inql
  • Start the UI through jython with jython -m inql

InQL Documentation Generator
In either BURP or in Stand-Alone mode, InQL is able to generate meaningful documentation for available GraphQL entities. Results are available as HTML pages or query templates.
The resulting HTML documentation page will contain details for all available QueriesMutations, and Subscriptions as shown here:

The following screenshot shows the use of templates generation:

Author and Maintainer: Andrea Brancaleoni (@nJoyneer – thypon)
This project was made with love in Doyensec Research island.Download Inql

X Forwarded for SQL injection

Original text by Nikos Danopoulos

Ghost Labs performs hundreds of success tests for its customers ranging from global enterprises to SMEs. Our team consists of highly skilled ethical hackers, covering a wide range of advanced testing services to help companies keep up with evolving threats and new technologies.

Last year, on May, I was assigned a Web Application test of a regular customer. As the test was blackbox one of the few entry points — if not the only — was a login page. The tight scoping range and the staticity of the Application did not provide many options.

After spending some time on the enumeration phase by trying to find hidden files/directories, leaked credentials online, common credentials, looking for vulnerable application components and more I was driven to a dead end.

No useful information were received, the enumeration phase had finished and no process had been made. Moreover, every fuzzing attempt on the login parameters didn’t not trigger any interesting responses.

Identifying the entry point

A very useful Burp Suite Extension is Bypass WAF. To find out how this extension works, have a quick look here. Briefly, this extension is used to bypass a Web Application firewall by inserting specific headers on our HTTP Requests. X-Forwarded-For is one of the them. What this header is also known for though is for the frequent use by the developers to store the IP Data of the client.

The following backend SQL statement is a vulnerable example of this:

mysql_query(«SELECT username, password FROM users-data WHEREusername='».sanitize($_POST[‘username’]).»‘ ANDpassword='».md5($_POST[‘password’]).»‘ AND ip_adr='».ipadr().»‘»);

More info here: SQL Injection through HTTP Headers

Where ipadr() is a function that reads the $_SERVER[‘HTTP_X_FORWARDED_FOR’] value (X-Forwarded-For header) and by applying some regular expression decides whether to store the value or not.

For the web application I was testing, it turned out to have a similar vulnerability. The provided X-Forwarded-For header was not properly validated, it was parsed as a SQL statement and there was the entry point.

Moreover, it was not mandatory to send a POST request to the login page and inject the payload through the header. The header was read and evaluated on the index page, by just requesting the “/” directory.

Due to the application’s structure, I was not able to trigger any visible responses from the payloads. That made the Injection a Blind, Time Based one. Out of several and more complex payloads — mainly for debugging purposes — the final, initial, payload was:

sql injection picture

And it was triggered by a similar request:

GET / HTTP/1.1
User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.21 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.21
X-Forwarded-For: «XOR(if(now()=sysdate(),sleep(6),0))OR”
X-Requested-With: XMLHttpRequest
Connection: close
Accept-Encoding: gzip,deflate
Accept: /

The response was delayed, the sleep value was incremented to validate the finding and indeed, the injection point was ready.

As sqlmap couldn’t properly insert the injection point inside the XOR payload, an initial manual enumeration was done. The next information extracted was the Database Length. That would allow me to later identify the Database Name too. Here is the payload used:

​​SQL injection picture

Of course, Burp Intruder was used to gradually increment the database length value. It turned out that the Database Length is 30. To find the Database Name Burp Intruder was used again with the following payload:

​​SQL injection picture

To automate this in an attack the following payload was used:


During the attack I noticed that the first 3 characters are the same with the first character of the domain name I am testing. The domain were 20 character long. I paused the intruder attack, went back to repeater and verified like this:


Indeed, the server delayed to respond indicating that the 15 first characters of the Database Name are the same as the domain name. The database name was 30 characters long. I had to continue the attack but this time with a different payload, starting the attack from character 21, in order to find the full database name. After a few minutes, the full database name was extracted. Format: “<domain-name>_<subdomain-name>_493 ” With the database name I then attempted to enumerate table names.

Similarly, a char-by-char bruteforce attacks is required to find the valid names.

To do this I loaded the information_schema.tables table that provides information about all the databases’ tables.  I filtered only the current’s database related tables by using the WHERE clause:

«XOR(if(Ascii(substring((​ Select​ table_name ​frominformation_schema.tables ​where​ table_schema=​database​() limit 0​,1),​1,1))=​’100’​, sleep​(5​),​0))​OR​»*/
​​SQL injection picture

As the previous payload was the initial one, I simplified it to this:

«XOR(if((substring((​ Select​ table_name ​ from​ information_schema.tables
where​ table_schema=​database​() ​limit​ ​0,1),​1,1))=​’a’​, sleep​(3),​0))​ OR​ «*/

Again, the payload was parsed to Burp Intruder to automate the process. After a few minutes the first tables were discovered:

​​SQL injection picture
​​SQL injection picture

After enumerating about 20 Tables Names I decided to try again my luck with SQLmap. As several tables where discovered, one of them was used to help sqlmap understand the injection point and continue the attack. Payload used in sqlmap:

XOR(select 1 from cache where 1=1 and 1=1*)OR

By that time I managed to properly set the injection point and I forced sqlmap to just extract the column names and data from the interesting tables.

​​SQL injection picture
​​SQL injection picture

Notes and Conclusion

At the end of the injection the whole database along with the valuable column information was received. The customer was notified immediately and the attack was reproduced as a proof of concept. 

Sometimes manual exploitation — especially blind, time based attacks — may seem tedious. As shown, it is also sometimes difficult to automate a detected injection attack. The best thing that can be done on such cases is to manually attack until all the missing information for the automation of the attack are collected.