SubTechniqueimpactATLAS

AML.T0034.001Resource-Intensive Queries

What it is

Adversaries may craft inputs specifically designed to increase the compute resources required for processing. For generative AI models, adversaries may use long input sequences, requests for extremely long outputs, or prompts that require complex reasoning as strategies for increasing compute costs [\[1\]][1]. For vision and language models, "sponge examples" [\[2\]][2] can be used to maximize energy consumption and decision latency. Utilizing fewer resource-intensive queries instead of simply flooding the model with excessive queries may be more difficult to detect and block or limit. [1]: https://genai.owasp.org/resource/owasp-top-10-for-llm-applications-2025/ [2]: https://arxiv.org/abs/2006.03463

References

  1. https://atlas.mitre.org/techniques/AML.T0034.001

Related by meaning· 6

Nearest entities by semantic similarity across the cs-graph corpus.

ATLAS
Cost Harvesting
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Denial of AI Service
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LLM Prompt Crafting
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Data from AI Services
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LLM Data Leakage
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Retrieval Content Crafting
Sourced from MITRE ATLAS — Adversarial Threat Landscape for AI Systems. Curated by Adam Lundqvist, SQUR.