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Resource-Intensive Queries - AI Security Technique

AI Security Technique

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]. For vision and language models, "sponge examples" [2] can be used to maximize energy consumption a...

Overview

A source-backed snapshot of this AI security technique.

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]. For vision and language models, "sponge examples" [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.

References

  1. [1] https://genai.owasp.org/resource/owasp-top-10-for-llm-applications-2025/
  2. [2] https://arxiv.org/abs/2006.03463
Tactics0Attacker goals connected to this method.
Mitigations0Defenses that may help against this attack.
AI risks0Research-backed risks connected to this topic.

Technique details

Identifiers, maturity, and source taxonomy for this technique.

ATLAS ID
AML.T0034.001
Maturity
feasible
Priority score
10

Attack flow

How to read the public records connected to this technique.

1. TechniqueRead the ATLAS description and evidence level.
2. TacticsSee which attacker goals this method supports.
3. ExamplesCheck whether public case studies mention it.
4. DefensesReview safeguards mapped by ATLAS.
5. SourcesOpen the original public records and references.

Impact

Why this technique may deserve attention in the current dataset.

  • Evidence levelfeasible
  • Mapped defenses0 ATLAS mitigation records
  • Public examples0 linked case study records
  • Research risks0 related MIT AI Risk records above the confidence threshold
  • Vulnerabilities0 linked CVE records

Mitigations

Defenses that may help against this attack.

No connected defenses. No defense is connected to this attack in the current data.

Case studies

Examples from public reports and exercises.

No case studies found. No public example is connected to this attack in the current data.

Source evidence

Original public records and references for this page.