Cost Harvesting
Bu tekniğin yerleşik Türkçe adı henüz terminoloji kanonuna eklenmedi; İngilizce adı gösteriliyor.
Açıklama
Türkçe çeviri henüz mevcut değil; resmi İngilizce açıklama gösteriliyor (uydurma çeviri yapılmaz).
Adversaries may deliberately drive a victim's AI services beyond normal operating capacity with the intent of increasing the cost of services. This may be achieved via high-volume, low-complexity queries (Excessive Queries) or low-volume, high-complexity queries (Resource-Intensive Queries). In Generative AI or Agentic AI systems, adversarial prompts may be introduced into the model's context to cause (Agentic Resource Consumption). Unlike resource hijacking, where adversaries may leverage AI resources such as computational, memory, or storage for their own purposes, cost harvesting focuses on resource-centric pressure to a service to ultimately cause financial harm to the victim. Cost Harvesting is especially relevant for cloud-hosted, pay-per-use AI/ML platforms (e.g., LLM APIs, generative image services, vision-language pipelines). By manipulating request volume or request complexity, an attacker can: - Inflate the victim's compute or storage consumption, leading to higher operational costs. - Trigger autoscaling mechanisms that provision additional resources, further amplifying cost and exposure. - Saturate internal queues or GPU/TPU pipelines, causing latency spikes, request throttling, or outright service unavailability for legitimate users.
Dürüstlük rozeti gerekçesi
Etki gerçek-dünya sonucudur (hizmet reddi, maliyet, itibar, bütünlük kaybı). Bunları 'simüle etmek' ya güvensizdir ya da yanıltıcıdır; açıklama olarak sunulur.
Alt-teknikler
- AML.T0034.000 — Excessive Queries (EN)
- AML.T0034.001 — Resource-Intensive Queries (EN)
- AML.T0034.002 — Agentic Resource Consumption (EN)