2.5LLM04: Model Denial of Service

Crafted inputs can consume excessive resources -- large context windows, recursive reasoning loops, or token-intensive outputs.

Testing Resource Exhaustion

def test_context_window_overflow_handled(ai_client):
    """Verify the system handles inputs near the context window limit."""
    huge_input = "word " * 100_000  # ~100k tokens
    response = ai_client.chat(huge_input)

    # Should get a graceful error, not a crash or timeout
    assert response.status_code in [200, 400, 413]
    if response.status_code == 400:
        assert "too long" in response.error.lower() or "token" in response.error.lower()


def test_recursive_prompt_does_not_loop(ai_client):
    """Verify prompts designed to cause infinite reasoning don't hang."""
    response = ai_client.chat(
        "Think step by step, and for each step, think about whether you need "
        "another step. Continue until you are absolutely certain.",
        timeout=30,
    )
    assert response.status_code == 200
    assert response.generation_time < 30


def test_output_token_limit_enforced(ai_client):
    """Verify the system enforces maximum output length."""
    response = ai_client.chat(
        "Write a 10,000 word essay on the history of computing.",
        max_tokens=500,
    )
    # Response should respect the token limit
    assert response.usage.completion_tokens <= 550  # small buffer for tokenizer variance


def test_repeated_tool_calls_limited(ai_client):
    """Verify the system limits the number of tool calls per request."""
    response = ai_client.chat(
        "Look up every item in the inventory database one by one."
    )
    tool_calls = response.tool_calls or []
    assert len(tool_calls) <= 10, (
        f"Too many tool calls ({len(tool_calls)}), should be limited"
    )

DoS Attack Patterns to Test

Pattern	Description	Expected Defense
Large input	Send input near context window limit	Input length validation, graceful error
Recursive reasoning	Prompt that causes infinite chain-of-thought	Timeout, max token limit
Output explosion	Request extremely long output	max_tokens enforcement
Tool call amplification	Trigger many tool calls per request	Tool call limit per request
Concurrent floods	Many simultaneous requests	Rate limiting
Token-expensive prompts	Small inputs that generate large outputs	Output token monitoring