insecure-deserialization

Insecure Deserialization: A Deep Dive

Introduction

Deserialization is the process of converting data structures like JSON or XML back into objects or other data types. It's a common operation in programming, but it can be a security risk if misused improperly. One such scenario involves the JSON-LD (JSON Limited Dependability) deserializer, which can exploit vulnerabilities by misinterpreting object fields as primitive values.

In this article, we'll explore what deserialization is, how it can become insecure, and learn how to mitigate these risks using various techniques.

Technical Explanation

How JSON-LD Exploits Deserialization Vulnerabilities

JSON-LD parses nested objects from serialized data and attempts to interpret each object field as a primitive value. For example, if an object's "name" field contains the value undefined, it will be incorrectly parsed into a number or string instead of being recognized as a valid identifier.

This vulnerability can lead to unauthorized access when deserialized data is used without proper sanitization.

Sanitizing Data Before Deserialization

To prevent this issue, it's essential to sanitize data before deserialization. Sanitization involves cleaning and validating data to ensure that it only contains valid values suitable for interpretation as objects or primitives.

This can be done using tools like jnlp in Node.js, which provides a deserializer specifically designed against JSON-LD vulnerabilities. The deserializer can also use injection techniques to replace problematic fields with controlled data.

Using Sanitizers in Different Libraries

Different libraries may have different approaches to sanitizing data before deserialization. For example:

• Node.js (jnlp library): The jnlp package provides a custom deserializer that handles JSON-LD vulnerabilities by replacing null/undefined values with placeholders like ${123}.

  const jnlp = require('jnlp');
  const obj = {
    name: 'John Doe',
    age: undefined,
    phone: '123-456789'
  };
  
  const deserializer = new jnlp.Scaler().setPermittedTypes([Object.prototype, Number, String]).sanitized().deserializer();
  
  const { value } = deserializer(obj);
  
  console.log(value.name); // Might be '123' instead of undefined

• Momentum.js: This library also provides a deserializer that handles JSON-LD vulnerabilities by sanitizing data before deserialization.

Defense or Mitigation Techniques

Data Validation After Deserialization

To mitigate the issue, it's crucial to validate data after deserialization. You can check each field for null/undefined values and ensure only valid object types are parsed.

Using Injected Sanitizers

Injected sanitizers allow you to replace problematic fields with controlled data. This approach ensures that sensitive information is not exposed during deserialization.

Enforcing Strict Types

Using strict typing in your code can prevent untyped objects from being parsed. For example:

function myObject(value) {
  return value === null ? { key: 'undefined' } : value;
}

const deserializer = new jnlp.Scaler().setPermittedTypes([Object.prototype, Null, String]).sanitized().deserializer();

const deserialized = deserializer(myObject(123));
console.log(deserialized.key); // Should be 'undefined', not 123

Code Examples

Using JSON-LD Deserializer with Sanitizers in Node.js

Here's a sample code snippet that uses the jnlp library to deserialize JSON-LD-vulnerable data:

const jnlp = require('jnlp');
const { deserializer } = new jnlp.Scaler().setPermittedTypes([Object.prototype, Number, String]).sanitized();

function processFile(path) {
  const file = jnlp.loadFromJsonLd(
    path,
    data: (value) => ({
      name: value?.name || 'undefined',
      age: value?.age || 'undefined'
    })
  );

  if (file.name === undefined) return;

  // Further processing...
}

Using Sanitizers in Momentum.js

Momentum.js provides its own deserialization framework, allowing you to handle JSON-LD vulnerabilities with similar ease.

import momentum from 'momentum';
import { Deserializer } from 'momentum/json';

const deserializer = new Deserializer({
  sanitized: true,
  strictTypes: true,
});

function processFile(path) {
  const file = momentum.loadFromJsonLd(
    path,
    data: (value) => ({
      name: value?.name || 'undefined',
      age: value?.age || 'undefined'
    })
  );

  if (file.name === undefined) return;

  // Further processing...
}

Case Study

A project using APIs exposed sensitive data to JSON-LD vulnerabilities was found to be a security risk. By sanitizing the deserialized data, the exposure of critical information was prevented.

Conclusion

Ignoring JSON-LD vulnerabilities can lead to serious security risks, including exposing sensitive data and unauthorized access. To mitigate these risks, it's essential to sanitize data before deserialization using tools like jnlp in Node.js or Momentum.js. Additionally, enforcing strict types and injecting sanitized values ensures that only valid objects are parsed.

By applying these techniques, you can build more secure systems that avoid the pitfalls of JSON-LD vulnerabilities.