AML.T0024: Exfiltration via AI Inference API
Adversaries may exfiltrate private information via AI Model Inference API Access. AI Models have been shown leak private information about their training data (e.g. Infer Training Data Membership, Invert AI Model). The model itself may also be extracted (Extract AI Model) for the purposes of AI Intellectual Property Theft.
Exfiltration of information relating to private training data raises privacy concerns. Private training data may include personally identifiable information, or other protected data.
Sub-techniques
AML.T0024.000: Infer Training Data Membership
Adversaries may infer the membership of a data sample or global characteristics of the data in its training set, which raises privacy concerns. Some strategies make use of a shadow model that could be obtained via Train Proxy via Replication, others use statistics of model prediction scores. This can cause the victim model to leak private information, such as PII of those in the training set or other forms of protected IP.
AML.T0024.001: Invert AI Model
AI models' training data could be reconstructed by exploiting the confidence scores that are available via an inference API. By querying the inference API strategically, adversaries can back out potentially private information embedded within the training data. This could lead to privacy violations if the attacker can reconstruct the data of sensitive features used in the algorithm.
AML.T0024.002: Extract AI Model
Adversaries may extract a functional copy of a private model. By repeatedly querying the victim's AI Model Inference API Access, the adversary can collect the target model's inferences into a dataset. The inferences are used as labels for training a separate model offline that will mimic the behavior and performance of the target model. Adversaries may extract the model to avoid paying per query in an artificial-intelligence-as-a-service (AIaaS) setting. Model extraction is used for AI Intellectual Property Theft.
Standards mapping
Where this fits in a TurboPentest engagement
This weakness is not covered by the automated black-box pentest. IntegSec pentesters cover it in a manual engagement.
Frequently asked questions
What is AML.T0024 Exfiltration via AI Inference API?
Adversaries may exfiltrate private information via AI Model Inference API Access. AI Models have been shown leak private information about their training data (e.g. Infer Training Data Membership, Invert AI Model). The model itself may also be extracted (Extract AI Model) for the purposes of AI Intellectual Property Theft. Exfiltration of information relating to private training data raises privacy concerns. Private training data may include personally identifiable information, or other protected data.
Which tactics does AML.T0024 belong to?
AML.T0024 maps to the Exfiltration tactic.
Does TurboPentest test for Exfiltration via AI Inference API?
This weakness is not covered by the automated black-box pentest. IntegSec pentesters cover it in a manual engagement.
Related MITRE ATLAS techniques
About this reference
These security references are maintained by IntegSec, an offensive-security firm whose team holds CISSP, OSCP, and OSCE certifications and has run thousands of penetration tests. Content is kept current as tools, standards, and attack techniques evolve.
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