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Merge pull request #200 from NextGenSec-Github/documentation-fix
Fixed Typo
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‎docs/ML04_2023-Membership_Inference_Attack.md‎

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| Threat Agents/Attack Vectors | Security Weakness | Impact |
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| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| Exploitability: 4 (Moderate) <br><br> _ML Application Specific: 5_ <br> _ML Operations Specific: 3_ | Detectability: 3 (Moderate) | Technical: 4 (Moderate) |
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| Threat Actors: Hackers or malicious actors who have access to the data and the model. <br> Insiders who have malicious intent or are bribed to interfere with the data. <br><br> Attact Vectors: Unsecured data transmission channels that allow unauthorized access to the data. | Lack of proper data access controls. <br><br> Lack of proper data validation and sanitization techniques. <br><br> Lack of proper data encryption. <br><br> Lack of proper data backup and recovery techniques. | Unreliable or incorrect model predictions. <br><br> Loss of confidentiality and privacy of sensitive data. <br><br> Legal and regulatory compliance violations. <br><br> Reputational damage. |
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| Threat Actors: Hackers or malicious actors who have access to the data and the model. <br> Insiders who have malicious intent or are bribed to interfere with the data. <br><br> Attack Vectors: Unsecured data transmission channels that allow unauthorized access to the data. | Lack of proper data access controls. <br><br> Lack of proper data validation and sanitization techniques. <br><br> Lack of proper data encryption. <br><br> Lack of proper data backup and recovery techniques. | Unreliable or incorrect model predictions. <br><br> Loss of confidentiality and privacy of sensitive data. <br><br> Legal and regulatory compliance violations. <br><br> Reputational damage. |
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It is important to note that this chart is only a sample based on
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[the scenario below](#scenario1) only. The actual risk assessment will depend on

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