From f360f53648dd267755b05abf8c7f8b843705ad02 Mon Sep 17 00:00:00 2001 From: Ads Dawson <104169244+GangGreenTemperTatum@users.noreply.github.com> Date: Thu, 26 Sep 2024 09:18:21 -0400 Subject: [PATCH] chore: rename to unbounded consumption (#407) --- ...nrestrictedModelInference.md => UnboundedConsumption.md} | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) rename 2_0_vulns/emerging_candidates/{UnrestrictedModelInference.md => UnboundedConsumption.md} (92%) diff --git a/2_0_vulns/emerging_candidates/UnrestrictedModelInference.md b/2_0_vulns/emerging_candidates/UnboundedConsumption.md similarity index 92% rename from 2_0_vulns/emerging_candidates/UnrestrictedModelInference.md rename to 2_0_vulns/emerging_candidates/UnboundedConsumption.md index 1d697bb5..7f5c7a18 100644 --- a/2_0_vulns/emerging_candidates/UnrestrictedModelInference.md +++ b/2_0_vulns/emerging_candidates/UnboundedConsumption.md @@ -1,4 +1,4 @@ -## Unrestricted Model Inference +## Unbounded Consumption **Author(s):** [Ads - GangGreenTemperTatum](https://github.com/GangGreenTemperTatum)
@@ -10,9 +10,9 @@ ### Description -Unrestricted Model Inference refers to the process where a Large Language Model (LLM) generates outputs based on input queries or prompts. Inference is a critical function of LLMs, involving the application of learned patterns and knowledge to produce relevant responses or predictions. +Unbounded Consumption refers to the process where a Large Language Model (LLM) generates outputs based on input queries or prompts. Inference is a critical function of LLMs, involving the application of learned patterns and knowledge to produce relevant responses or predictions. -Unrestricted Model Inference occurs when a Large Language Model (LLM) application allows users to conduct excessive and uncontrolled inferences, leading to potential risks such as denial of service (DoS), economic losses, model or intellectual property theft theft, and degradation of service. This vulnerability is exacerbated by the high computational demands of LLMs, often deployed in cloud environments, making them susceptible to various forms of resource exploitation and unauthorized usage. +Unbounded Consumption occurs when a Large Language Model (LLM) application allows users to conduct excessive and uncontrolled inferences, leading to potential risks such as denial of service (DoS), economic losses, model or intellectual property theft theft, and degradation of service. This vulnerability is exacerbated by the high computational demands of LLMs, often deployed in cloud environments, making them susceptible to various forms of resource exploitation and unauthorized usage. ### Common Examples of Vulnerability