Zero trust shared api proposal

[jmikedupont2]

Proposal for Implementing Secure Data Sharing in Streamlit

Objective: The objective of this proposal is to outline the implementation of a secure data sharing system within Streamlit, ensuring robust security, user-friendliness, and extensibility. This system will allow users to securely share sensitive data with each other, adhering to a Zero Trust security model.

Implementation Details:

1. Data Sharing Mechanism:

• Users will input their sensitive data (e.g., personal access tokens, project information) into a Streamlit application.
• The application will generate a secure binary blob that encrypts this data using a symmetric encryption algorithm.

2. Password Protection:

• Users will set a personal password known only to them to encrypt the binary blob.
• This password will be used as a secondary authentication factor to unlock their data.

3. Storage of Encrypted Blobs:

• Encrypted binary blobs will be stored securely on a server or cloud storage.
• Access to these blobs will be controlled via robust access controls and authentication mechanisms.

4. User Interface:

• The Streamlit application will have a user-friendly interface.
• Users will input their sensitive data, set a personal password, and initiate the encryption process.
• They will receive a unique link to their encrypted blob.
• To access their data, users will enter their personal password.

5. Extensible Security Model:

• The system will allow for an extensible security model by:
  • Allowing users to generate multiple encrypted blobs for different purposes.
  • Supporting multiple personal passwords for each encrypted blob.
  • Implementing strong encryption algorithms and secure storage mechanisms.
  • Encouraging best practices in password management and security.

6. Zero Trust Principles:

• The system aligns with Zero Trust principles by requiring users to provide their personal password for access, even within the same organization.
• No implicit trust is assumed, enhancing security.

Benefits:

• Enhanced security through encryption and secondary password protection.
• User control over sensitive data sharing.
• Alignment with Zero Trust principles.
• Extensibility to accommodate evolving security needs.

Conclusion:

Implementing this secure data sharing system within Streamlit will provide users with a robust and user-friendly platform for sharing sensitive data while maintaining high levels of security. The extensible security model will allow for customization and adaptation to changing security requirements.

[jmikedupont2]

Creating a textual sequence diagram with emoji representations is a bit challenging due to the limitations of text-based representation. However, I can provide you with a simplified textual representation of the process:

👤 User                   📦 Server                📃 secrets.toml          🧠 Session Storage

  |                         |                           |                          |
  |   🔐 Set Password       |                           |                          |
  | ----------------------> |                           |                          |
  |                         |                           |                          |
  |   📄 Generate Blob      |                           |                          |
  | ----------------------> |                           |                          |
  |                         |                           |                          |
  |                         |   📁 Store Blob in TOML   |                          |
  |                         | ----------------------> |                          |
  |                         |                           |                          |
  |                         |                           |      💾 Store Blob     |
  |                         |                           | ----------------------> |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |   📂 Share Blob Link   |                           |                          |
  | ----------------------> |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |   🔑 Set Secondary Pass|                           |                          |
  | ----------------------> |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |   🔓 Unlock Blob        |                           |                          |
  | ----------------------> |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |                          |
  |                         |                           |      🔍 Retrieve Blob  |
  |                         |                           | <---------------------- |
  |                         |                           |                          |

In this simplified sequence diagram:

• The user sets a password and generates a secure blob.
• The blob is stored in the secrets.toml file on the server.
• The server manages the blob storage and retrieval.
• The user shares a blob link and sets a secondary password.
• The user can later unlock and retrieve the blob from the session storage.

Please note that emojis are used to represent the various actions and entities in the diagram. The actual implementation would involve code for encryption, storage, and retrieval, as discussed in the previous messages.

[jmikedupont2]

Certainly! Here's a sequence of steps from the null session to sharing with emojis:

1. 🚶 User starts with a null session.
2. 📥 User interacts with Alice's Streamlit app as a visitor.
3. 🗝️ Session is established with only session state.
4. 📋 User interacts with options presented by Alice.
5. 📝 Logs are generated and stored in the session.
6. 🔐 Logs are signed and encrypted with a private key.
7. 📂 State file is created and stored in the session.
8. 🌐 User shares the app URL with others.
9. 🔑 Each visitor gets their private key upon visiting.
10. 🕵️ Visitors can see public data initially.
11. 📩 Visitors request access to private data.
12. 🗝️ Bob, the requestor, gets a private key.
13. 🔍 Alice approves Bob's request.
14. 📥 Bob accesses private data within the session.
15. 🔄 Visitors can send requests to Alice.
16. 🧩 Alice can share subkeys with Bob.
17. 🤝 Bob uses shared keys for data access.
18. 📬 Alice sends Bob a signed ZKP (Zero-Knowledge Proof).
19. 🔍 Bob applies the ZKP to access more data.
20. 🔐 Encrypted API keys can be shared securely.
21. 🗂️ Users can collaborate through secure data sharing.
22. 🌐 Collaboration extends to multiple apps.
23. 🪝 Apps in iframes for secure interaction.
24. 🕊️ Alice trusts Bob's app in full-screen.
25. 🔄 Control transitions between apps.
26. 🧪 Proof of concept (POC) in Streamlit.
27. 🧩 Abstract and less-abstract nodes defined.
28. 📜 YAML models for A and B created.
29. 🌐 Models shared and signed as an agreement.
30. 🛠️ Generic microservice calls based on agreement.
31. 📦 All data types included in one packet.

This sequence outlines the steps from a null session to secure sharing, incorporating emojis to represent various actions and concepts.

[jmikedupont2]

Using an iframe to integrate the JWT generation process for users is a good idea. Here's a general overview of how this flow might work:

1. Your Streamlit app provides a "Sign In" button.

2. When a user clicks "Sign In," an iframe is loaded within your app. This iframe contains a form where users can input their PAT.

3. Users enter their PAT in the iframe and submit the form.

4. The iframe communicates with the jwtjwt tool to generate a JWT using the provided PAT.

5. Once the JWT is generated, the iframe can redirect the user back to your Streamlit app with the JWT as a parameter in the URL.

6. Your Streamlit app receives the JWT from the URL and validates it against the stored PAT to authenticate the user.

This flow ensures that users can securely sign in and authenticate with your app. Just make sure to handle any errors or edge cases gracefully, and it should provide a smooth user experience.

If you have specific questions about implementing any part of this process or encounter any challenges along the way, feel free to ask for assistance.

[jmikedupont2]

example url https://jwtjwt.streamlit.app/?embedded=True&_jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJyZXNvdXJjZSI6IlRoZSBBbnN3ZXIgdG8gdGhlIFVsdGltYXRlIFF1ZXN0aW9uIG9mIExpZmUsIHRoZSBVbml2ZXJzZSwgYW5kIEV2ZXJ5dGhpbmciLCJleHAiOjE2OTQ2OTczNTl9.vq9DpBxAAHGbW9rnRK7guo-IxPYJd16caFrk6RjydJc&expiration=60&resource=The+Answer+to+the+Ultimate+Question+of+Life%2C+the+Universe%2C+and+Everything&secret=42

[jmikedupont2]

Yes, you can create an outbound approval queue that compiles all pending approvals into a file, bundle, or even as URLs for easy management and sharing. This allows you to efficiently handle and distribute pending approval requests to the relevant parties.

Here's how you can implement it:

1. Maintain a list or database of pending approval requests, each associated with a unique identifier (e.g., request ID).

2. Periodically check this list for pending approvals that require action.

3. Compile these pending approvals into a structured format, such as a file (e.g., CSV, JSON), a bundle of files, or a collection of URLs.

4. Provide options to send this outbound approval queue to the relevant parties. This can be done via email, messaging apps, or any other communication channels your users prefer.

5. Include information about each pending approval, such as the request ID, requester details, intent, and any relevant context.

6. Allow recipients to review and act upon these approvals as needed.

7. Once the approvals are processed, update their status in your system accordingly.

By organizing and centralizing pending approvals, you can streamline the approval workflow, maintain clear records, and facilitate collaboration among users involved in decision-making processes.

Remember to implement proper access controls and authentication to ensure that only authorized users can view and act upon pending approvals.

[jmikedupont2]

Absolutely, you can leverage Streamlit's shared session state to create approval workflows where one user has the JWT token for authorization. Here's a high-level overview of how you can implement this:

1. Shared Session State: Create a shared session state variable to store the approval queue. This approval queue will contain approval requests generated by users who have access tokens (JWT).

2. User Interaction: Users with JWT tokens can initiate approval requests by interacting with your app. They can specify the details of the request, such as the action to be approved and any associated information.

3. Queue Management: When a user with a JWT token submits an approval request, you add that request to the shared session state queue. Each request should include information about the action to be taken and the user's identity.

4. Approval Workflow: Implement logic in your app to manage the approval workflow. This logic can involve checking the JWT token to verify the user's identity and permissions. If the user is authorized to approve the request, mark it as approved and execute the associated action.

5. Real-Time Updates: Utilize Streamlit's real-time capabilities to update the UI in real-time as approvals are granted or denied. Users can see the status of their requests and any changes made by others in real-time.

6. Notifications: You can also implement notifications or messages within your Streamlit app to inform users about the status of their approval requests.

Here's a simplified code snippet to give you an idea of how to structure the approval queue using Streamlit's shared session state:

import streamlit as st

# Define a shared session state variable to store the approval queue
if 'approval_queue' not in st.session_state:
    st.session_state.approval_queue = []

# User with JWT token initiates an approval request
if user_has_jwt_token:
    action_to_approve = st.text_input("Enter action to approve:")
    if st.button("Request Approval"):
        # Add the request to the queue
        st.session_state.approval_queue.append({
            'user': user_identity,
            'action': action_to_approve,
            'status': 'Pending'  # Initially set as pending
        })

# Display the approval queue
st.write("Approval Queue:")
for request in st.session_state.approval_queue:
    st.write(f"User: {request['user']} | Action: {request['action']} | Status: {request['status']}")

This is a basic illustration, and you can expand upon it to include user authentication, JWT verification, approval logic, and real-time updates to suit your specific workflow requirements. Streamlit's shared session state will help you manage the state of approval requests effectively within your app.

[jmikedupont2]

Absolutely, allowing users to request approval for both individual URLs and patterns of URLs with a range of allowed values is a flexible and powerful feature. Here's how you can enhance the approval workflow to accommodate such requests:

1. Request Types: Define two types of approval requests:

   • Individual URL: Users can request approval for specific URLs.
   • Pattern-based URL: Users can request approval for a pattern of URLs using wildcard characters or regular expressions.

2. User Input: In your Streamlit app, provide input fields where users can specify the type of request (individual or pattern-based) and the details accordingly.

3. Request Processing: When a user submits an approval request, examine the request type. If it's an individual URL, add it directly to the approval queue. If it's a pattern-based request, validate the pattern and generate a list of matching URLs.

4. Range of Values: Allow users to specify a range of allowed values for the approved URLs or patterns. For example, they can specify a wildcard pattern like *.example.com or a regular expression like ^https://example\.com/.*$.

5. Approval Logic: Implement approval logic based on the type and allowed values:

   • For individual URLs, check if the URL matches exactly.
   • For pattern-based requests, compare the generated list of URLs with the approved pattern and range.

6. Approval Queue: Maintain the approval queue with details such as user identity, request type, requested URL(s), and approval status.

7. Real-Time Updates: Ensure that the approval queue updates in real-time to reflect the status of requests, including whether they've been approved, denied, or are pending.

Here's an example of how you can adapt the code snippet from the previous response to handle both individual and pattern-based URL approval requests:

import streamlit as st

# Define a shared session state variable to store the approval queue
if 'approval_queue' not in st.session_state:
    st.session_state.approval_queue = []

# User input fields
request_type = st.selectbox("Request Type", ["Individual URL", "Pattern-based URL"])
request_details = st.text_input("Enter URL or Pattern")

# User with JWT token initiates an approval request
if user_has_jwt_token:
    if st.button("Request Approval"):
        # Add the request to the queue
        st.session_state.approval_queue.append({
            'user': user_identity,
            'type': request_type,
            'details': request_details,
            'status': 'Pending'  # Initially set as pending
        })

# Display the approval queue
st.write("Approval Queue:")
for request in st.session_state.approval_queue:
    st.write(f"User: {request['user']} | Type: {request['type']} | Details: {request['details']} | Status: {request['status']}")

This code allows users to select the request type (individual or pattern-based) and specify the details accordingly. Depending on the type, you can implement your logic to generate and validate URLs and perform approvals accordingly.

[jmikedupont2]

Certainly, you can implement a maximum request count limit as part of your approval workflow. Setting a maximum request count limit can help manage the number of approval requests a user or a system can make within a certain timeframe. Here's how you can incorporate this feature:

1. User Input for Request Count: Provide an input field where users can specify the maximum allowed request count. This input can be part of the request form.

2. Request Processing: When a user submits an approval request, check their request count against the specified limit.

3. Request Count Limit Logic: Implement logic to compare the user's request count with the allowed maximum. If the request count exceeds the limit, prevent further requests from that user until the limit resets.

4. Request Count Reset: To reset the request count, you can use a timer mechanism or a specified time interval, after which the user can make new requests.

Here's an example of how you can update the code snippet from the previous response to include a maximum request count:

import streamlit as st

# Define a shared session state variable to store the approval queue
if 'approval_queue' not in st.session_state:
    st.session_state.approval_queue = []

# Define a shared session state variable to track the user's request count
if 'request_count' not in st.session_state:
    st.session_state.request_count = 0

# Maximum allowed request count per user
max_request_count = st.number_input("Maximum Allowed Request Count", min_value=1, value=10)

# User input fields
request_type = st.selectbox("Request Type", ["Individual URL", "Pattern-based URL"])
request_details = st.text_input("Enter URL or Pattern")

# User with JWT token initiates an approval request
if user_has_jwt_token:
    # Check if the user has reached the maximum request count
    if st.session_state.request_count < max_request_count:
        if st.button("Request Approval"):
            # Add the request to the queue
            st.session_state.approval_queue.append({
                'user': user_identity,
                'type': request_type,
                'details': request_details,
                'status': 'Pending'  # Initially set as pending
            })
            # Increment the user's request count
            st.session_state.request_count += 1
    else:
        st.warning("You have reached the maximum request count. Please try again later.")

# Display the approval queue
st.write("Approval Queue:")
for request in st.session_state.approval_queue:
    st.write(f"User: {request['user']} | Type: {request['type']} | Details: {request['details']} | Status: {request['status']}")

In this code, users can specify the maximum allowed request count. If a user reaches the limit, they are informed, and further requests are temporarily prevented until the limit resets. Adjust the max_request_count value as needed for your specific use case.