Common Weakness Enumeration

A Community-Developed List of Software Weakness Types

CWE/SANS Top 25 Most Dangerous Software Errors
Home > CWE List > CWE- Individual Dictionary Definition (3.0)  

CWE-502: Deserialization of Untrusted Data

Weakness ID: 502
Abstraction: Variant
Structure: Simple
Status: Draft
Presentation Filter:
+ Description
The application deserializes untrusted data without sufficiently verifying that the resulting data will be valid.
+ Extended Description

It is often convenient to serialize objects for communication or to save them for later use. However, deserialized data or code can often be modified without using the provided accessor functions if it does not use cryptography to protect itself. Furthermore, any cryptography would still be client-side security -- which is a dangerous security assumption.

Data that is untrusted can not be trusted to be well-formed.

When developers place no restrictions on "gadget chains," or series of instances and method invocations that can self-execute during the deserialization process (i.e., before the object is returned to the caller), it is sometimes possible for attackers to leverage them to perform unauthorized actions, like generating a shell.

+ Alternate Terms
Marshaling, Unmarshaling:
Marshaling and unmarshaling are effectively synonyms for serialization and deserialization, respectively.
Pickling, Unpickling:
In Python, the "pickle" functionality is used to perform serialization and deserialization.
+ Relationships

The table(s) below shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.

+ Relevant to the view "Research Concepts" (CWE-1000)
+ Relevant to the view "Weaknesses for Simplified Mapping of Published Vulnerabilities" (CWE-1003)
+ Relevant to the view "Architectural Concepts" (CWE-1008)
MemberOfCategoryCategory1019Validate Inputs
+ Relevant to the view "Development Concepts" (CWE-699)
+ Background Details
Serialization and deserialization refer to the process of taking program-internal object-related data, packaging it in a way that allows the data to be externally stored or transferred ("serialization"), then extracting the serialized data to reconstruct the original object ("deserialization").
+ Modes Of Introduction

The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the software life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.

Architecture and DesignOMISSION: This weakness is caused by missing a security tactic during the architecture and design phase.
+ Applicable Platforms
The listings below show possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.


Java (Undetermined Prevalence)

Ruby (Undetermined Prevalence)

PHP (Undetermined Prevalence)

Python (Undetermined Prevalence)

JavaScript (Undetermined Prevalence)

+ Common Consequences

The table below specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.


Technical Impact: Modify Application Data; Unexpected State

Attackers can modify unexpected objects or data that was assumed to be safe from modification.

Technical Impact: DoS: Resource Consumption (CPU)

If a function is making an assumption on when to terminate, based on a sentry in a string, it could easily never terminate.

Technical Impact: Varies by Context

The consequences can vary widely, because it depends on which objects or methods are being deserialized, and how they are used. Making an assumption that the code in the deserialized object is valid is dangerous and can enable exploitation.
+ Likelihood Of Exploit
+ Demonstrative Examples

Example 1

This code snippet deserializes an object from a file and uses it as a UI button:

(bad code)
Example Language: Java 
try {
File file = new File("object.obj");
ObjectInputStream in = new ObjectInputStream(new FileInputStream(file));
javax.swing.JButton button = (javax.swing.JButton) in.readObject();


This code does not attempt to verify the source or contents of the file before deserializing it. An attacker may be able to replace the intended file with a file that contains arbitrary malicious code which will be executed when the button is pressed.

To mitigate this, explicitly define final readObject() to prevent deserialization. An example of this is:

(good code)
Example Language: Java 
private final void readObject(ObjectInputStream in) throws {
throw new"Cannot be deserialized"); }

Example 2

In Python, the Pickle library handles the serialization and deserialization processes. In this example derived from [R.502.7], the code receives and parses data, and afterwards tries to authenticate a user based on validating a token.

(bad code)
Example Language: Python 
try {
class ExampleProtocol(protocol.Protocol):
def dataReceived(self, data):

# Code that would be here would parse the incoming data
# After receiving headers, call confirmAuth() to authenticate

def confirmAuth(self, headers):
token = cPickle.loads(base64.b64decode(headers['AuthToken']))
if not check_hmac(token['signature'], token['data'], getSecretKey()):
raise AuthFail
self.secure_data = token['data']
raise AuthFail


Unfortunately, the code does not verify that the incoming data is legitimate. An attacker can construct a illegitimate, serialized object "AuthToken" that instantiates one of Python's subprocesses to execute arbitrary commands. For instance,the attacker could construct a pickle that leverages Python's subprocess module, which spawns new processes and includes a number of arguments for various uses. Since Pickle allows objects to define the process for how they should be unpickled, the attacker can direct the unpickle process to call Popen in the subprocess module and execute /bin/sh.

+ Observed Examples
Deserialization issue in commonly-used Java library allows remote execution.
Deserialization issue in commonly-used Java library allows remote execution.
Use of PHP unserialize function on untrusted input allows attacker to modify application configuration.
Use of PHP unserialize function on untrusted input in content management system might allow code execution.
Use of PHP unserialize function on untrusted input in content management system allows code execution using a crafted cookie value.
Content management system written in PHP allows unserialize of arbitrary objects, possibly allowing code execution.
Python script allows local users to execute code via pickled data.
Unsafe deserialization using pickle in a Python script.
Web browser allows execution of native methods via a crafted string to a JavaScript function that deserializes the string.
+ Potential Mitigations

Phases: Architecture and Design; Implementation

If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.

Phase: Implementation

When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.

Phase: Implementation

Explicitly define a final object() to prevent deserialization.

Phases: Architecture and Design; Implementation

Make fields transient to protect them from deserialization.

An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.

Phase: Implementation

Avoid having unnecessary types or gadgets available that can be leveraged for malicious ends. This limits the potential for unintended or unauthorized types and gadgets to be leveraged by the attacker. Whitelist acceptable classes. Note: new gadgets are constantly being discovered, so this alone is not a sufficient mitigation.
+ Memberships
This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
+ Notes


The relationships between CWE-502 and CWE-915 need further exploration. CWE-915 is more narrowly scoped to object modification, and is not necessarily used for deserialization.
+ Taxonomy Mappings
Mapped Taxonomy NameNode IDFitMapped Node Name
CLASPDeserialization of untrusted data
CERT Java Secure CodingSER01-JDo not deviate from the proper signatures of serialization methods
CERT Java Secure CodingSER03-JDo not serialize unencrypted, sensitive data
CERT Java Secure CodingSER06-JMake defensive copies of private mutable components during deserialization
CERT Java Secure CodingSER08-JDo not use the default serialized form for implementation defined invariants
Software Fault PatternsSFP25Tainted input to variable
+ References
[REF-461] Matthias Kaiser. "Exploiting Deserialization Vulnerabilities in Java". 2015-10-28. <>.
[REF-462] Sam Thomas. "PHP unserialization vulnerabilities: What are we missing?". 2015-08-27. <>.
[REF-463] Gabriel Lawrence and Chris Frohoff. "Marshalling Pickles: How deserializing objects can ruin your day". 2015-01-28. <>.
[REF-464] Heine Deelstra. "Unserializing user-supplied data, a bad idea". 2010-08-25. <>.
[REF-465] Manish S. Saindane. "Black Hat EU 2010 - Attacking Java Serialized Communication". 2010-04-26. <>.
[REF-466] Nadia Alramli. "Why Python Pickle is Insecure". 2009-09-09. <>.
[REF-467] Nelson Elhage. "Exploiting misuse of Python's "pickle"". 2011-03-20. <>.
[REF-468] Chris Frohoff. "Deserialize My Shorts: Or How I Learned to Start Worrying and Hate Java Object Deserialization". 2016-03-21. <>.
+ Content History
Submission DateSubmitterOrganization
Modification DateModifierOrganization
2008-07-01Eric DalciCigital
updated Time_of_Introduction
2008-09-08CWE Content TeamMITRE
updated Common_Consequences, Description, Relationships, Other_Notes, Taxonomy_Mappings
2009-10-29CWE Content TeamMITRE
updated Description, Other_Notes, Potential_Mitigations
2011-06-01CWE Content TeamMITRE
updated Common_Consequences, Relationships, Taxonomy_Mappings
2012-05-11CWE Content TeamMITRE
updated Relationships, Taxonomy_Mappings
2012-10-30CWE Content TeamMITRE
updated Demonstrative_Examples
2013-02-21CWE Content TeamMITRE
updated Alternate_Terms, Applicable_Platforms, Background_Details, Common_Consequences, Maintenance_Notes, Observed_Examples, Potential_Mitigations, References, Relationships
2014-07-30CWE Content TeamMITRE
updated Relationships, Taxonomy_Mappings
2015-12-07CWE Content TeamMITRE
updated Observed_Examples, References, Relationships
2017-05-03CWE Content TeamMITRE
updated Applicable_Platforms, Demonstrative_Examples, Description, Potential_Mitigations, References
2017-11-08CWE Content TeamMITRE
updated Applicable_Platforms, Common_Consequences, Demonstrative_Examples, Modes_of_Introduction, Potential_Mitigations, References, Relationships

More information is available — Please select a different filter.
Page Last Updated: January 18, 2018