AML.T0029
Denial of AI Service

MITRE source definition

Adversaries may target AI-enabled systems with a flood of requests for the purpose of degrading or shutting down the service. Since many AI systems require significant amounts of specialized compute, they are often expensive bottlenecks that can become overloaded. Adversaries can intentionally craft inputs that require heavy amounts of useless compute from the AI system.

Source modified 2026-05-27. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.

Parent, sub-techniques and ATT&CK references

No explicit relationship in this pinned source.

Source-backed defensive context

MITRE mitigations

• AML.M0004 Limit AI Service Query Volume and Rate
• AML.M0015 Predictive AI Adversarial Input Detection
• AML.M0019 Control Access to AI Models and Data in Production
• AML.M0035 AI Red Team
• AML.M0036 Limit AI Workload Resource Consumption

MITRE case studies

• AML.CS0016 Achieving Code Execution in MathGPT via Prompt Injection · Exercise
• AML.CS0036 AIKatz: Attacking LLM Desktop Applications · Exercise

These are explicit source relationships, not independently reproduced incidents or validated detection coverage.

Simulation and telemetry boundary

This is a technique reference page, not a runnable simulation. No ATLAS-specific telemetry mapping, local attack execution or detector validation is asserted. MITRE maturity describes its source evidence, not a 1200km lab result.

For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.

Provenance and attribution

Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0

Copyright 2021-2026 MITRE. Source text and explicit relationships are retained; navigation, formatting and local links are provided by 1200km.

No explicit relationship in this pinned source.