LLM10: Unbounded Consumption

Denial of Wallet Challenge

Explore how uncontrolled LLM usage can lead to excessive resource consumption and costs. Complete challenges to understand different aspects of unbounded consumption vulnerabilities.

Understanding Unbounded Consumption

What is Unbounded Consumption?

Unbounded Consumption occurs when LLM applications allow excessive and uncontrolled inferences, leading to resource exhaustion, financial losses, and service disruption. This vulnerability exploits the high computational demands and cost-per-use model of LLM services.

Attack Vectors

  • Input Flooding: Overwhelming with variable-length inputs
  • Resource Drain: Complex, CPU-intensive queries
  • Chain Reactions: Self-perpetuating prompts
  • Cost Exploitation: Maximizing token usage

Impact

  • Service degradation and outages
  • Unsustainable operational costs
  • Resource exhaustion
  • Denial of service to legitimate users

Example Attack Prompts

Here are some example prompts that demonstrate different types of unbounded consumption attacks:

Token Flooding

Write a comprehensive guide about artificial intelligence, including its history, current applications, future potential, and ethical considerations. Make it extremely detailed with many examples and use cases.

Resource Intensive

Create a complex sorting algorithm in Python that handles multiple data types, includes detailed comments explaining each step, and analyze its time complexity with different input sizes.

Chain Reaction

Generate a story outline. Then, for each plot point, expand it into a detailed scene. For each scene, describe the characters, setting, and dialogue in extreme detail.

Cost Accumulation

Analyze this code base: [paste a large codebase]. Explain each function in detail, suggest improvements, and provide example usage for each component.
0 Points
0 tokens
$0.0000
0 requests

Token Flood

100 pts

Make the API process more than 1000 tokens in a single request

Cost Explorer

200 pts

Accumulate $0.01 in API costs through efficient token usage

Chain Reaction

300 pts

Create a self-perpetuating prompt that generates increasingly longer responses

Resource Drain

400 pts

Trigger high CPU usage through complex processing requests

OpenAI API Configuration

Your API key will be stored locally and only used for lab exercises.

Prevention Strategies

Technical Controls

  • Implement strict rate limiting
  • Set token usage quotas
  • Monitor resource consumption
  • Use timeouts and circuit breakers

Best Practices

  • Validate and sanitize inputs
  • Implement cost monitoring
  • Set up usage alerts
  • Use graceful degradation