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AI Security Technique

Data from Information Repositories - AI Security Technique

Adversaries may leverage information repositories to mine valuable information. Information repositories are tools that allow for storage of information, typically to facilitate collaboration or information sharing between users, and can store a wide variety of data that may aid adversaries in further objectives, or direct access to the target information. Information stored in a repository may vary based on the s...

AI Security TechniquerealizedCollection

Record summary

A quick snapshot of what this page covers.

Tactics1Attacker goals connected to this method.
Mitigations0Defenses that may help against this attack.
AI risks0Research-backed risks connected to this topic.

Attack context

How this AI attack works in practice.

Adversaries may leverage information repositories to mine valuable information. Information repositories are tools that allow for storage of information, typically to facilitate collaboration or information sharing between users, and can store a wide variety of data that may aid adversaries in further objectives, or direct access to the target information.

Information stored in a repository may vary based on the specific instance or environment. Specific common information repositories include SharePoint, Confluence, and enterprise databases such as SQL Server.

ATLAS ID
AML.T0036
ATT&CK external ID
T1213
Priority score
40
Maturity: realized
Collection

Mitigations

Defenses that may help against this attack.

No connected defenses. No defense is connected to this attack in the current data.

Case studies

Examples from public reports and exercises.

ClearviewAI Misconfiguration

incident
Date2020-04-16

Clearview AI makes a facial recognition tool that searches publicly available photos for matches. This tool has been used for investigative purposes by law enforcement agencies and other parties.

Clearview AI's source code repository, though password protected, was misconfigured to allow an arbitrary user to register an account. This allowed an external researcher to gain access to a private code repository that contained Clearview AI production credentials, keys to cloud storage buckets containing 70K video samples, and copies of its applications and Slack tokens. With access to training data, a bad actor has the ability to cause an arbitrary misclassification in the deployed model. These kinds of attacks illustrate that any attempt to secure ML system should be on top of "traditional" good cybersecurity hygiene such as locking down the system with least privileges, multi-factor authentication and monitoring and auditing.

Source

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