Zero trust shared api proposal #20
Comments
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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: In this simplified sequence diagram:
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. |
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Certainly! Here's a sequence of steps from the null session to sharing with emojis:
This sequence outlines the steps from a null session to secure sharing, incorporating emojis to represent various actions and concepts. |
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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:
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. |
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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:
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. |
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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:
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. |
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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:
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. |
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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:
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 |
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:
2. Password Protection:
3. Storage of Encrypted Blobs:
4. User Interface:
5. Extensible Security Model:
6. Zero Trust Principles:
Benefits:
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.
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