# Uncontrolled Resource Consumption (CWE-400)

The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.

**Stack:** JavaScript

- Prevalence: High Frequently exploited
- Impact: Medium Review recommended
- Prevention: Documented 8 fix examples

**OWASP:** Security Misconfiguration (A05:2021-Security Misconfiguration) - #5

## Description

Limited resources include memory, file system storage, database connection pool entries, and CPU. If an attacker can trigger the allocation of these limited resources, but the number or size of the resources is not controlled, then the attacker could cause a denial of service.

## Prevention

Prevention strategies for Resource Exhaustion based on 2 Shoulder detection rules.

### JavaScript

Set max_tokens limits and validate input length before LLM API calls

Configure timeout and maxBuffer for child process execution to prevent resource exhaustion

## Warning Signs

- [MEDIUM] LLM API call lacks resource limits (...)
- [MEDIUM] AI/LLM API calls that lack token limits, potentially enabling denial
of service attacks
- [MEDIUM] child process execution (exec, spawn) without proper resource limits

## Consequences

- DoS: Resource Consumption
- DoS: Crash/Exit/Restart

## Mitigations

- Implement rate limiting
- Use resource quotas
- Implement timeouts for operations

## Detection

- Total rules: 8
- Languages: go, javascript, typescript, yaml, python

## Rules by Language

### Javascript (2 rules)

- **LLM Denial of Service** [MEDIUM]: Detects AI/LLM API calls that lack token limits, potentially enabling denial
of service attacks. OWASP LLM04 - Model Denial of Service.

DoS attacks against LLMs can:
- Exhaust API quotas through unbounded token generation
- Cause excessive costs via high token usage
- Degrade service availability

This rule detects:
- Missing max_tokens limits on completions
- Missing input length validation
- Unbounded streaming responses

NOTE: Rate limiting is covered separately by the Express rate-limiting rule.
See: rules/javascript/projects/express/security/rate-limiting.yaml
  - Remediation: Set max_tokens limits and validate input length before LLM calls.

```javascript
const response = await openai.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: message.substring(0, 2000) }],
  max_tokens: 500
});
```

Learn more: https://shoulder.dev/learn/javascript/cwe-400/llm-denial-of-service
- **Denial of Service via Unbounded Child Processes** [MEDIUM]: Detects child process execution (exec, spawn) without proper resource limits.
Without timeout or maxBuffer configuration, these processes can:
- Hang indefinitely, consuming server resources
- Flood memory with unbounded output
- Enable DoS attacks through resource exhaustion

This is especially critical when the command can be influenced by user input
or interacts with external resources (network requests, git operations, etc.).
  - Remediation: Configure timeout and maxBuffer for child process execution:

```javascript
const { exec } = require('child_process');
const { promisify } = require('util');
const execPromise = promisify(exec);

const { stdout } = await execPromise(`ping -c 4 ${domain}`, {
  timeout: 5000,
  maxBuffer: 1024 * 100
});
```

Learn more: https://shoulder.dev/learn/javascript/cwe-400/unbounded-exec-dos

### Typescript (2 rules)

- **LLM Denial of Service** [MEDIUM]: Detects AI/LLM API calls that lack token limits, potentially enabling denial
of service attacks. OWASP LLM04 - Model Denial of Service.

DoS attacks against LLMs can:
- Exhaust API quotas through unbounded token generation
- Cause excessive costs via high token usage
- Degrade service availability

This rule detects:
- Missing max_tokens limits on completions
- Missing input length validation
- Unbounded streaming responses

NOTE: Rate limiting is covered separately by the Express rate-limiting rule.
See: rules/javascript/projects/express/security/rate-limiting.yaml
  - Remediation: Set max_tokens limits and validate input length before LLM calls.

```javascript
const response = await openai.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: message.substring(0, 2000) }],
  max_tokens: 500
});
```

Learn more: https://shoulder.dev/learn/javascript/cwe-400/llm-denial-of-service
- **Denial of Service via Unbounded Child Processes** [MEDIUM]: Detects child process execution (exec, spawn) without proper resource limits.
Without timeout or maxBuffer configuration, these processes can:
- Hang indefinitely, consuming server resources
- Flood memory with unbounded output
- Enable DoS attacks through resource exhaustion

This is especially critical when the command can be influenced by user input
or interacts with external resources (network requests, git operations, etc.).
  - Remediation: Configure timeout and maxBuffer for child process execution:

```javascript
const { exec } = require('child_process');
const { promisify } = require('util');
const execPromise = promisify(exec);

const { stdout } = await execPromise(`ping -c 4 ${domain}`, {
  timeout: 5000,
  maxBuffer: 1024 * 100
});
```

Learn more: https://shoulder.dev/learn/javascript/cwe-400/unbounded-exec-dos