Critical form-data Vulnerability CVE-2025-7783: How Predictable Random Numbers Enable Parameter Injection Attacks

The JavaScript ecosystem faces another significant security challenge with the discovery of CVE-2025-7783, a critical vulnerability in the widely-used form-data library. This vulnerability demonstrates how seemingly innocuous coding practices can create serious security holes that attackers can exploit to inject malicious parameters into multipart form requests.

What is the Vulnerability?

The vulnerability lies in how the form-data library generates boundary values for multipart form-encoded data. Instead of using a cryptographically secure random number generator, the library relies on JavaScript's Math.random() function, which produces pseudo-random values that are predictable once an attacker can observe the pattern.

The Root Cause

The problematic code can be found in the form-data library where Math.random() is used to generate boundary strings that separate different parts of multipart form data. Since Math.random() uses a linear congruential generator (LCG) algorithm, its output follows a predictable pattern that can be reverse-engineered.

When an attacker can observe several sequential Math.random() values from an application, they can:

1. Determine the current state of the pseudo-random number generator (PRNG)

2. Predict future values, including those used for form boundary generation

3. Craft malicious payloads that contain the predicted boundary value

4. Inject additional parameters into requests that weren't intended to be user-controlled

How the Attack Works

The attack scenario requires two key conditions:

1. Observable Math.random() Values: The attacker must be able to observe other values produced by Math.random() in the target application. Common sources include:

   • Request ID headers (like x-request-id)

   • Session tokens

   • CSRF tokens

   • Any client-side generated identifiers

2. User-Controlled Input: The attacker must be able to control at least one field in a request that uses the vulnerable form-data library.

Once these conditions are met, the attacker can:

• Monitor the application's Math.random() outputs through various side channels

• Calculate the PRNG state using the observed values

• Predict the next boundary value that will be used by form-data

• Craft a payload that includes this boundary, effectively "breaking out" of their controlled field

• Inject additional form parameters that the application didn't intend to accept

Real-World Impact

This vulnerability is particularly dangerous because:

Parameter Injection

Attackers can inject arbitrary parameters into requests sent to internal systems, potentially:

• Bypassing authentication checks

• Modifying sensitive configuration values

• Accessing restricted functionality

• Escalating privileges

Internal System Compromise

Since many applications use form-data to communicate with internal APIs or services, successful exploitation could lead to:

• Unauthorized access to backend systems

• Data manipulation or theft

• Service disruption

• Lateral movement within the network

Scale of Exposure

The form-data library is extremely popular in the Node.js ecosystem, used by countless applications for handling file uploads and API communications. This means the potential impact extends across a vast number of applications and services.

Who Is at Risk?

Applications are vulnerable if they meet both of these criteria:

1. Use form-data with user input: The application uses the form-data library to send requests containing user-controlled data to other systems

2. Expose Math.random() values: The application reveals Math.random() outputs through headers, responses, or other observable channels

Common vulnerable scenarios include:

• File upload services that proxy uploads to cloud storage

• Webhook systems that forward user data to external APIs

• Microservices architectures using form-data for inter-service communication

• Applications with request tracing that use Math.random() for correlation IDs

Mitigation Strategies

Immediate Actions

1. Update Dependencies: Check if your version of form-data is affected and update to a patched version as soon as one becomes available

2. Audit Math.random() Usage: Review your codebase for places where Math.random() values might be exposed to users:

   • HTTP headers

   • API responses

   • Client-side code

   • Log files accessible to users

3. Input Validation: Implement strict validation on user inputs that are processed by form-data to prevent boundary injection attempts

Long-term Solutions

1. Use Cryptographically Secure Random Sources: Replace Math.random() with cryptographically secure alternatives:

   • Node.js: crypto.randomBytes() or crypto.randomUUID()

   • Browser: crypto.getRandomValues()

2. Implement Defense in Depth:

   • Sanitize and validate all user inputs

   • Use allowlists for acceptable parameter names

   • Implement request signing or authentication for internal API calls

3. Security Headers: Avoid exposing random values in HTTP headers when possible, or use secure random sources for any exposed values

Detection and Monitoring

To detect potential exploitation attempts:

1. Monitor for suspicious form data: Look for requests with unusual boundary patterns or unexpected parameter combinations

2. Log analysis: Watch for requests that contain form boundaries in user-controlled fields

3. Anomaly detection: Implement monitoring for unusual parameter patterns in requests to internal APIs

The Broader Lesson

This vulnerability highlights several important security principles:

Cryptographic Randomness Matters

The use of Math.random() for security-sensitive operations is a common antipattern. Developers should always use cryptographically secure random number generators when randomness has security implications.

Side Channel Attacks

Even seemingly harmless information leakage (like request IDs) can become powerful attack vectors when combined with other vulnerabilities. This emphasizes the importance of considering the broader security implications of any data exposure.

Supply Chain Security

Popular libraries like form-data are used by millions of applications. A single vulnerability can have massive downstream effects, highlighting the critical importance of secure coding practices in open-source dependencies.

Conclusion

CVE-2025-7783 serves as a stark reminder that security vulnerabilities can lurk in the most unexpected places. What appears to be a simple random number generation issue can become a critical security flaw when combined with the right conditions.

Development teams should:

• Immediately assess their exposure to this vulnerability

• Review their use of Math.random() throughout their applications

• Implement proper input validation and sanitization

• Consider the security implications of any data they expose to users

As the JavaScript ecosystem continues to evolve, incidents like this underscore the importance of security-first development practices and the need for ongoing vigilance in managing our software supply chains.

The security community's quick response to identifying and documenting this vulnerability demonstrates the value of collaborative security research. By sharing knowledge and maintaining transparency about security issues, we can work together to build a more secure web for everyone.