Spamming AI System with Chaff Data - AI Security Technique
AI Security TechniqueAdversaries may spam the AI system with chaff data that causes increase in the number of detections. This can cause analysts at the victim organization to waste time reviewing and correcting incorrect inferences. Adversaries may also spam AI agents with excessive low-severity auditable events or agentic actions that require a human-in-the-loop, wasting time for the victim organization in human review of the agenti...
Overview
A source-backed snapshot of this AI security technique.
Adversaries may spam the AI system with chaff data that causes increase in the number of detections. This can cause analysts at the victim organization to waste time reviewing and correcting incorrect inferences.
Adversaries may also spam AI agents with excessive low-severity auditable events or agentic actions that require a human-in-the-loop, wasting time for the victim organization in human review of the agentic AI system.
Technique details
Identifiers, maturity, and source taxonomy for this technique.
- ATLAS ID
- AML.T0046
- Maturity
- feasible
- Priority score
- 16
Attack flow
How to read the public records connected to this technique.
Impact
Why this technique may deserve attention in the current dataset.
- Evidence levelfeasible
- Mapped defenses2 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.
AML.M0019 - Control Access to AI Models and Data in Production
Authentication on production models can help prevent anonymous chaff data spam.
AML.M0004 - Restrict Number of AI Model Queries
Limit the number of queries users can perform in a given interval to protect the system from chaff data spam.
Case studies
Examples from public reports and exercises.
Source evidence
Original public records and references for this page.
Original source
Original source links
Open the public records and source datasets used for this page.