Python Internal Read Gadgets

Basic Information

Different vulnerabilities such as Python Format Strings or Class Pollution might allow you to read python internal data but won't allow you to execute code. Therefore, a pentester will need to make the most of these read permissions to obtain sensitive privileges and escalate the vulnerability.

Flask - Read secret key

The main page of a Flask application will probably have the app global object where this secret is configured.

app = Flask(__name__, template_folder='templates')
app.secret_key = '(:secret:)'

In this case it's possible to access this object just using any gadget to access global objects from the Bypass Python sandboxes page.

In the case where the vulnerability is in a different python file, you need a gadget to traverse files to get to the main one to access the global object app.secret_key to change the Flask secret key and be able to escalate privileges knowing this key.

A payload like this one from this writeup:

__init__.__globals__.__loader__.__init__.__globals__.sys.modules.__main__.app.secret_key

Use this payload to change app.secret_key (the name in your app might be different) to be able to sign new and more privileges flask cookies.

Werkzeug - machine_id and node uuid

Using these payload from this writeup you will be able to access the machine_id and the uuid node, which are the main secrets you need to generate the Werkzeug pin you can use to access the python console in /console if the debug mode is enabled:

{ua.__class__.__init__.__globals__[t].sys.modules[werkzeug.debug]._machine_id}
{ua.__class__.__init__.__globals__[t].sys.modules[werkzeug.debug].uuid._node}

⚠️ Warning

Note that you can get the **servers local path to the `app.py`** generating some **error** in the web page which will **give you the path**.

If the vulnerability is in a different python file, check the previous Flask trick to access the objects from the main python file.

Django - SECRET_KEY and settings module

The Django settings object is cached in sys.modules once the application starts. With only read primitives you can leak the SECRET_KEY, database credentials or signing salts:

# When DJANGO_SETTINGS_MODULE is set (usual case)
sys.modules[os.environ['DJANGO_SETTINGS_MODULE']].SECRET_KEY

# Through the global settings proxy
a = sys.modules['django.conf'].settings
(a.SECRET_KEY, a.DATABASES, a.SIGNING_BACKEND)

If the vulnerable gadget is in another module, walk globals first:

__init__.__globals__['sys'].modules['django.conf'].settings.SECRET_KEY

Once the key is known you can forge Django signed cookies or tokens in a similar way to Flask.

Environment variables / cloud creds via loaded modules

Many jails still import os or sys somewhere. You can abuse any reachable function __init__.__globals__ to pivot to the already-imported os module and dump environment variables containing API tokens, cloud keys or flags:

# Classic os._wrap_close subclass index may change per version
cls = [c for c in object.__subclasses__() if 'os._wrap_close' in str(c)][0]
cls.__init__.__globals__['os'].environ['AWS_SECRET_ACCESS_KEY']

If the subclass index is filtered, use loaders:

__loader__.__init__.__globals__['sys'].modules['os'].environ['FLAG']

Environment variables are frequently the only secrets needed to move from read to full compromise (cloud IAM keys, database URLs, signing keys, etc.).

Django-Unicorn class pollution (CVE-2025-24370)

django-unicorn (<0.62.0) allowed class pollution via crafted component requests. Setting a property path such as __init__.__globals__ let an attacker reach the component module globals and any imported modules (e.g. settings, os, sys). From there you can leak SECRET_KEY, DATABASES or service credentials without code execution. The exploit chain is purely read-based and uses the same dunder-gadget patterns as above.

Gadget collections for chaining

Recent CTFs (e.g. jailCTF 2025) show reliable read chains built only with attribute access and subclass enumeration. Community-maintained lists such as pyjailbreaker catalog hundreds of minimal gadgets you can combine to traverse from objects to __globals__, sys.modules and finally sensitive data. Use them to quickly adapt when indices or class names differ between Python minor versions.

References

Wiz analysis of django-unicorn class pollution (CVE-2025-24370)
pyjailbreaker – Python sandbox gadget wiki
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