Overcoming the Security Challenges of Using GPT-4 with your internal data 

6 Jul, 2023 •

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The power of AI with OpenAI’s GPT-4 for your internal analysis and reporting requirements is quite alluring. It can serve as an easy chat interface to your data. However, there are a number of security challenges of using GPT-4 with your internal data that need to be considered. For example: 

  1. Data Privacy: Your internal data contains sensitive and confidential information. Sharing this data with GPT-4 raises concerns about data privacy. You need to ensure that appropriate measures are in place to protect the privacy and confidentiality of your internal data. 
  1. Data Leakage: There is a risk of data leakage if GPT-4’s model inadvertently includes sensitive information from the internal data in its responses. You need to consider how to manage the outputs generated by GPT-4 to prevent any unintended disclosure of confidential information. 
  1. Unauthorized Access: Strong access controls are required to prevent unauthorized access. The model and the data should be protected from unauthorized individuals who may attempt to exploit or misuse the information. Robust authentication mechanisms and role-based access controls should be implemented to restrict access to the model and the internal data. 
  1. Adversarial Attacks: GPT-4 can be susceptible to adversarial attacks. Adversaries may attempt to manipulate or deceive the model by feeding it malicious input to produce incorrect or biased outputs. Protecting against such attacks requires implementing robust input validation and monitoring techniques to detect and mitigate potential threats. 
  1. Model Bias: If trained on biased data, GPT-4 can perpetuate or amplify existing biases present in the internal data of a company. This can lead to biased or discriminatory responses, which can have legal and ethical implications. Companies need to carefully evaluate the training data and implement techniques to address and mitigate bias in the model’s responses. 
  1. Model Ownership and Control: When using GPT-4 with internal data, there may be concerns regarding the ownership and control of the model. Companies need to have clear agreements and contracts in place with the model provider to ensure that they retain ownership and control over their internal data and any derived models. 
  1. Compliance and Regulatory Requirements: Depending on the industry and the type of internal data involved, there may be specific compliance and regulatory requirements that need to be adhered to. Companies should ensure that the use of GPT-4 with internal data aligns with applicable regulations, such as data protection laws, industry-specific regulations, and intellectual property rights.  

Addressing these security challenges requires a combination of technical measures, such as encryption, access controls, and auditing, as well as organizational policies and practices, including data governance, employee training, and incident response plans. It is crucial to conduct thorough risk assessments and engage security professionals to ensure the appropriate security measures are in place when utilizing GPT-4 with internal company data. 

Taking these items one by one, here’s how DvSum helps: 

  1. Data Privacy:  

a. Your data never leaves your network 

With cloud solutions, you typically have to give your data to vendors, and the vendor cloud security becomes a critical requirement. The first step in overcoming security challenges of using GPT-4 with internal data would be getting a demo with DvSum, where the data scanning happens inside your network and only metadata is sent outside your network to DvSum Cloud. Get the benefit of a SaaS solution without an increased data protection footprint. 

b. Industry-accepted best practices and frameworks 

Our security approach focuses on security governance, risk management, and compliance. This includes encryption at rest and in transit, network security and server hardening, administrative access control, system monitoring, logging and alerting, and more. 

  1. Data Leakage:  

 a. Automatic PII data masking and filtering 

DvSum only harvests metadata from your data sources. Even so, DvSum uses PII identification and masking algorithms when scanning data. So you can be sure that any PII information in your data is not extracted in the data catalog. Continue to maintain GDPR, HIPAA, and other data privacy compliances while using DvSum. 

  1. Unauthorized Access:  

a. Single Sign-On 

If you use Single Sign-on for user access (like Azure ADFS, Okta or any SAML supported Provider), you can configure DvSum to use the same Identity Provider. If you do not use SSO, you can let DvSum manage user authentication powered by AWS Cognito. 

b. Role-based access control (RBAC) 

Allow for the separation of privileges by user role. Built-in Admin, Editor, User roles. Create your own specific roles and user groups to create finer control to your Data Intelligence platform. 

  1. Adversarial Attacks, Model Bias, and Model Ownership and Control 

Your data and use of DvSum with GPT-4 is isolated from the rest of the world. DvSum licenses GPT-4 through Microsoft Azure OpenAI Service for your internal use at your company. This provides elevated SLAs both for performance as well as for security and privacy. Your data is never sent to GPT-4 but remains within your own network. The metadata and questions which are sent to GPT-4 are never shared with others and never used to train the foundational AI models. The charts and data sets returned to your users are the results of queries run against your enterprise databases, not unfiltered data from GPT-4. This way the results are repeatable, reliable, and explainable. 

Only your own internal data, within your own network, is used. External people and entities do not have access to your data or GPT-4’s usage context with your data. 

  1. Compliance and Regulatory Requirements:  

DvSum has achieved SOC2 Type 2 compliance which provides organizations with a tangible validation of their data security practices. By undergoing rigorous audits and assessments, organizations can identify vulnerabilities, implement necessary safeguards, and establish robust security controls to protect against potential threats. This certification assures customers and partners that DvSum has implemented comprehensive security measures to protect their valuable data assets.  

Customers can now have complete confidence in DvSum, knowing that their data is handled in accordance with industry-leading standards. SOC2 Type 2 compliance not only instills trust but also helps organizations meet regulatory requirements and mitigate the risks associated with data breaches and unauthorized access. 


Ultimately, DvSum securely combines GPT-4 with a powerful underlying data infrastructure that makes all the data appropriately and easily accessible. This empowers a data-driven culture and ultimately drives data democracy ensuring that decisions are based upon trusted, real-time data. 

Explore how DvSum helps overcome these pitfalls

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