AI Red

OWASP LLM10 Unbounded Consumption: Testing YandexGPT Lite 5 and GigaChat Lite on Resource-Intensive Prompts

The article examines OWASP LLM10: Unbounded Consumption, a category focused on attacks that force large language models to perform computationally expensive tasks without traditional denial-of-service traffic. Researchers used the AI Red Team platform to evaluate two flagship Russian models, YandexGPT Lite 5 and GigaChat Lite, against prompts designed to trigger recursive context expansion, fractal nesting, combinatorial explosions, and multi-agent simulations. The study highlights how a single carefully crafted prompt can generate disproportionate token consumption, GPU load, and API costs compared with conventional DoS methods. Both models demonstrated defensive strategies including hard generation limits at 512 tokens, graceful degradation by summarizing instead of expanding, and early refusal with alternative suggestions. The work was supported by the Foundation for Assistance to Innovations and aims to improve architectural protections for LLM applications. Examples of tested prompts and observed model behaviors are provided for research and educational purposes only.