Deserialization of Untrusted Data: Unpacking a Remote Code Execution Vulnerability

Introduction

In the evolving landscape of cybersecurity threats, few vulnerabilities pose as significant a risk as insecure deserialization. This critical security flaw has consistently ranked among the most dangerous attack vectors, earning its place in OWASP’s Top 10 vulnerabilities list. Recent incidents in 2025, including the ViewState deserialization zero-day vulnerability in Sitecore products (CVE-2025-53690) and Microsoft SharePoint’s CVE-2025-30382, demonstrate that deserialization attacks remain a persistent and evolving threat.

Deserialization vulnerabilities can result in remote code execution when exploited, potentially allowing attackers to gain complete control over affected systems. Understanding the mechanics, risks, and prevention strategies for these vulnerabilities is crucial for developers, security professionals, and organizations seeking to protect their digital assets.

What is Serialization and Deserialization?

Before diving into the vulnerability itself, it’s essential to understand the fundamental concepts of serialization and deserialization.

Serialization is the process of converting an object or data structure into a format that can be stored or transmitted. This might involve converting objects into JSON, XML, binary formats, or other structured representations. Serialization enables applications to save object states to files, databases, or send them across networks.

Deserialization is the reverse process—reconstructing objects from their serialized form. During deserialization, the application reads the serialized data and recreates the original object structure in memory, complete with its properties, methods, and state.

While these processes are fundamental to modern application development, they become dangerous when untrusted data enters the equation.

The Anatomy of Insecure Deserialization

Deserialization can be dangerous since it can open applications to attacks such as remote code execution (RCE) if the data to deserialize originates from an untrusted source. The vulnerability occurs when applications deserialize data from sources they cannot trust without proper validation or security controls.

Why Deserialization is Inherently Risky

The fundamental risk lies in the deserialization process itself. When an application deserializes data, it doesn’t just recreate passive data structures—it can execute code. Many serialization formats and libraries support complex object graphs, including executable code, constructors, and method calls that run during the deserialization process.

Insecure deserialization enables attackers to manipulate serialized objects to pass harmful data into application code, potentially replacing serialized objects with objects of entirely different types.

Attack Vectors and Impact

Insecure deserialization vulnerabilities can lead to remote code execution if attackers can control the serialized object, allowing them to execute arbitrary code on the server when deserialized. The impact extends beyond RCE to include:

Complete System Compromise: Attackers can gain full control over vulnerable systems
Data Exfiltration: Sensitive information can be accessed and stolen
Lateral Movement: Compromised systems can serve as launching points for further attacks
Denial of Service: Resource-intensive deserialization operations can overwhelm systems
Authentication Bypass: Manipulated session objects can bypass security controls

Real-World Examples and Recent Incidents

The threat landscape in 2025 continues to demonstrate the severity of deserialization vulnerabilities:

Sitecore ViewState Vulnerability (CVE-2025-53690)

The ViewState deserialization vulnerability resulted in remote code execution on affected internet-facing Sitecore instances, with attackers deploying WEEPSTEEL malware for internal reconnaissance.

Microsoft SharePoint Deserialization (CVE-2025-30382)

This deserialization vulnerability, rated at a CVSS score of 7.8, enables remote attackers to execute arbitrary code, potentially allowing full system compromise and lateral network movement.

These recent incidents underscore that deserialization vulnerabilities remain actively exploited and pose ongoing risks to organizations worldwide.

Technical Deep Dive: Java Deserialization Attack

To illustrate how deserialization attacks work in practice, let’s examine a common scenario using Java—one of the most frequently targeted languages for these attacks.

Vulnerable Java Code Example

// Vulnerable deserialization code
public class VulnerableServer {
    public void handleRequest(Socket socket) throws Exception {
        ObjectInputStream ois = new ObjectInputStream(socket.getInputStream());
        Object obj = ois.readObject(); // DANGEROUS: Accepts untrusted input
        
        // Process the deserialized object
        if (obj instanceof UserData) {
            UserData userData = (UserData) obj;
            processUserData(userData);
        }
    }
}

If a malicious object graph crafted with a gadget chain from Commons Collections is sent over the socket, readObject() can lead to remote code execution.

The Attack Chain

Gadget Chain Construction: Attackers identify “gadget chains”—sequences of existing classes in the application’s classpath that can be chained together to achieve code execution.
Payload Crafting: A malicious serialized object is constructed that exploits these gadget chains. For example, using Apache Commons Collections:

// Simplified example of a gadget chain payload
Transformer[] transformers = new Transformer[] {
    new ConstantTransformer(Runtime.class),
    new InvokerTransformer("getMethod", 
        new Class[] {String.class, Class[].class}, 
        new Object[] {"getRuntime", new Class[0]}),
    new InvokerTransformer("invoke", 
        new Class[] {Object.class, Object[].class}, 
        new Object[] {null, new Object[0]}),
    new InvokerTransformer("exec", 
        new Class[] {String.class}, 
        new Object[] {"calc.exe"}) // Execute calculator
};

Transformer transformerChain = new ChainedTransformer(transformers);
Map map = new HashMap();
map.put("value", "value");
Map transformedMap = TransformedMap.decorate(map, null, transformerChain);

Payload Delivery: The malicious serialized object is sent to the vulnerable application through various channels (HTTP requests, network sockets, message queues, etc.).
Code Execution: When the application deserializes the payload, the gadget chain executes, running the attacker’s code with the privileges of the application.

Python Pickle Vulnerabilities

Python’s pickle module presents similar risks. Consider this vulnerable code:

import pickle
import socket

def handle_request(conn):
    data = conn.recv(4096)
    obj = pickle.loads(data)  # DANGEROUS: Deserializes untrusted data
    return obj

An attacker could craft a malicious pickle payload:

import pickle
import subprocess

class MaliciousPayload:
    def __reduce__(self):
        return (subprocess.call, (['calc.exe'],))

# Serialize the malicious payload
payload = pickle.dumps(MaliciousPayload())
# Send payload to vulnerable server...

When the vulnerable application deserializes this payload, it executes the subprocess.call function, launching the calculator application (or any other command specified by the attacker).

Advanced Attack Techniques

Property-Oriented Programming (POP)

Attackers use Property-Oriented Programming to construct gadget chains that leverage existing code paths in applications. By carefully crafting object properties, they can trigger method calls during deserialization that lead to code execution.

Blind Deserialization Attacks

Even when applications don’t directly use deserialized objects, attackers can still achieve code execution through side effects during the deserialization process itself, such as constructor calls or static initializers.

Polymorphic Payloads

Advanced attackers create payloads that can adapt to different environments and classpaths, increasing their success rate across diverse target systems.

Detection and Identification

Identifying deserialization vulnerabilities requires both code analysis and runtime testing:

Static Code Analysis

Look for deserialization methods accepting untrusted input
Identify usage of dangerous libraries (ObjectInputStream, pickle, etc.)
Review input validation and sanitization procedures

Dynamic Testing

Monitor network traffic for serialized data patterns
Test applications with malicious payloads
Use specialized security testing tools designed for deserialization flaws

Runtime Monitoring

Implement logging for deserialization operations
Monitor for suspicious object instantiations
Track unusual system calls during deserialization

Comprehensive Prevention Strategies

Prevention strategies include not allowing the datastream to define the type of object that will be deserialized, using safer alternatives like DataContractSerializer or XmlSerializer where possible.

1. Avoid Deserializing Untrusted Data

The most effective defense is simple: never deserialize data from untrusted sources. This fundamental principle eliminates the attack vector entirely.

// Safe approach: Use structured data formats
public class SecureHandler {
    public void handleRequest(HttpServletRequest request) {
        // Use JSON instead of Java serialization
        String jsonData = request.getParameter("data");
        ObjectMapper mapper = new ObjectMapper();
        UserData userData = mapper.readValue(jsonData, UserData.class);
    }
}

2. Implement Strict Input Validation

When deserialization is unavoidable, implement comprehensive validation:

public class ValidatingObjectInputStream extends ObjectInputStream {
    private Set<String> allowedClasses;
    
    public ValidatingObjectInputStream(InputStream in, Set<String> allowedClasses) {
        super(in);
        this.allowedClasses = allowedClasses;
    }
    
    @Override
    protected Class<?> resolveClass(ObjectStreamClass desc) throws IOException, ClassNotFoundException {
        String className = desc.getName();
        if (!allowedClasses.contains(className)) {
            throw new InvalidObjectException("Unauthorized deserialization attempt: " + className);
        }
        return super.resolveClass(desc);
    }
}

3. Use Whitelisting Approaches

Restrict deserialization to only classes or objects that are explicitly trusted and necessary for application functionality by maintaining a whitelist of allowed classes.

4. Implement Sandboxing

Run deserialization operations in restricted environments with limited privileges:

// Example: Restrict permissions during deserialization
AccessController.doPrivileged(new PrivilegedAction<Object>() {
    public Object run() {
        // Perform deserialization with restricted permissions
        return deserializeWithLimitedPrivileges(data);
    }
}, restrictedAccessControlContext);

5. Use Safer Alternatives

Replace native serialization with safer formats:

JSON: Human-readable and doesn’t execute code during parsing
Protocol Buffers: Binary format with strict schema validation
MessagePack: Efficient binary format without code execution risks
XML with schema validation: Structured format with validation capabilities

6. Implement Runtime Protections

# Python example: Restrict pickle operations
import pickle
import builtins

class RestrictedUnpickler(pickle.Unpickler):
    def find_class(self, module, name):
        # Only allow safe builtins
        if module == "builtins" and name in ["list", "dict", "str", "int"]:
            return getattr(builtins, name)
        raise pickle.UnpicklingError(f"Forbidden class: {module}.{name}")

def safe_loads(data):
    return RestrictedUnpickler(io.BytesIO(data)).load()

Industry Best Practices and Standards

OWASP Guidelines

Follow OWASP’s comprehensive guidance on preventing insecure deserialization, which includes architectural recommendations, secure coding practices, and testing methodologies.

Security by Design

Integrate security considerations into the software development lifecycle from the beginning, rather than treating them as an afterthought.

Regular Security Assessments

Conduct periodic security reviews and penetration testing to identify potential deserialization vulnerabilities before attackers do.

Monitoring and Incident Response

Logging and Alerting

Implement comprehensive logging for deserialization operations:

logger.info("Deserialization attempted for class: {} from source: {}", 
    className, requestSource);

Incident Response Procedures

Develop specific incident response procedures for deserialization attacks, including: - Immediate containment strategies - Forensic analysis procedures - Recovery and remediation steps - Communication protocols

Future Considerations and Emerging Threats

As demonstrated by the recent vulnerabilities in 2025, deserialization attacks continue to evolve. Organizations must stay vigilant and adapt their security strategies to address:

New attack vectors and techniques
Emerging serialization formats and libraries
Cloud-native and microservice architectures
AI and machine learning applications that process serialized data

Conclusion

Deserialization of untrusted data remains one of the most critical vulnerability classes in modern application security. By injecting malicious serialized data, attackers can execute arbitrary code on servers, gaining complete control over systems. The recent high-profile incidents in 2025 serve as stark reminders that this threat is both persistent and evolving.

The fundamental principle for protecting against these attacks is straightforward: never deserialize data you don’t control. When deserialization is necessary, implement multiple layers of defense including strict input validation, whitelisting, sandboxing, and comprehensive monitoring.

Organizations must prioritize addressing deserialization vulnerabilities through a combination of secure coding practices, architecture decisions that minimize risk, and ongoing security assessments. By understanding the mechanics of these attacks and implementing robust prevention strategies, developers and security teams can significantly reduce their exposure to this critical vulnerability class.

The cost of prevention is invariably lower than the cost of compromise. In an era where a single successful deserialization attack can lead to complete system compromise and significant business impact, investing in proper security measures is not just recommended—it’s essential for organizational survival in the digital landscape.