CWE-436: Interpretation Conflict

What is Interpretation Conflict?

• Overview: Interpretation Conflict occurs when two systems (e.g., Product A and Product B) interpret inputs or actions differently, leading to mismatched expectations and incorrect actions. This often affects intermediary devices like proxies and firewalls.

• Exploitation Methods:

• Attackers can exploit this by crafting inputs that are handled differently by the two systems, manipulating the outcome.
• Common techniques include sending ambiguous or malformed data that one system accepts and another rejects, leading to bypassing security controls.

• Security Impact:

• Direct consequences include unauthorized access or actions being performed, as systems may incorrectly validate or process the data.
• Potential cascading effects involve further security breaches if one system's misinterpretation results in downstream vulnerabilities.
• Business impact can include data breaches, service disruptions, and loss of customer trust.

• Prevention Guidelines:

• Ensure consistent interpretation of data and actions across all systems by aligning the handling of inputs and responses.
• Implement security best practices such as input validation and sanitization to reduce discrepancies.
• Use recommended tools and frameworks that provide consistent and secure handling of data across different platforms.

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Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

// This code attempts to load configuration settings from a JSON file, 
// but there's an interpretation conflict due to inconsistent data handling.

const fs = require('fs');

function loadConfig(filePath) {
    const configContent = fs.readFileSync(filePath, 'utf-8');
    const config = JSON.parse(configContent); // Directly parsing user-supplied content
    return config;
}

const config = loadConfig('config.json');
console.log(config);

Explanation

The vulnerability arises from the interpretation conflict between how the file content is loaded and how JSON parsing is expected to handle it. If the config.json file contains unexpected or malicious content, it can cause the application to behave in unintended ways. For example, if the JSON contains unexpected data types or additional fields, it might lead to security issues or application misbehavior.

How to fix Interpretation Conflict?

To fix this issue, we must ensure that the file content is validated and sanitized before being parsed. This requires implementing checks to ensure the data conforms to expected formats and constraints, preventing malicious data from being processed. Additionally, using a schema validation library can further enhance security by enforcing strict data structure rules.

Fixed Code Example

const fs = require('fs');
const Ajv = require('ajv'); // JSON schema validator library

function loadConfig(filePath) {
    const configContent = fs.readFileSync(filePath, 'utf-8');

    // Validate the JSON format before parsing
    let config;
    try {
        config = JSON.parse(configContent);
    } catch (e) {
        throw new Error('Invalid JSON format'); // Handle JSON parsing errors
    }

    // Define a JSON schema for validation
    const schema = { // Schema definition for expected data structure
        type: 'object',
        properties: {
            host: { type: 'string' },
            port: { type: 'integer' }
        },
        required: ['host', 'port'],
        additionalProperties: false
    };

    const ajv = new Ajv();
    const validate = ajv.compile(schema);

    if (!validate(config)) { // Validate the parsed JSON against the schema
        throw new Error('Configuration does not match schema');
    }

    return config;
}

const config = loadConfig('config.json');
console.log(config);

Explanation

1. JSON Parsing Error Handling: By wrapping the JSON.parse call in a try-catch block, we can effectively handle any parsing errors and prevent crashes due to malformed JSON.

2. Schema Validation: Using a library like Ajv, we define a JSON schema that specifies the expected structure and types of configuration data. This adds a layer of validation to ensure the data meets the application's requirements.

3. Rejecting Invalid Data: The schema validation step ensures that only valid configurations are accepted, thus preventing interpretation conflicts and ensuring consistent behavior across different components of the application.

By implementing these changes, the code becomes more robust against malformed or malicious JSON data, ensuring the application behaves as expected and reducing potential security risks.