Impact

The adversary is trying to manipulate, interrupt, or destroy your AI system.

7 Techniques
MITRE ATLAS Framework

Attack Techniques

Explore the specific techniques adversaries use during the impact phase of AI attacks.

1
AML.T0015

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
2
AML.T0029

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
3
AML.T0031

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
4
AML.T0034

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
5
AML.T0046

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
6
AML.T0048

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits
7
AML.T0059

Data Manipulation

Adversaries may manipulate data to impact AI system integrity.

Examples:

  • Corrupting training data
  • Manipulating model outputs
  • Poisoning AI systems

Mitigations:

  • Data validation
  • Model integrity checks
  • Regular audits