| agent: | Auto Exec |
What is an "Expert"? How do we create our own expert?
Add credentials for various integrations
Managing workspaces and access control
DagKnows Architecture Overview
Setting up SSO via Azure AD for Dagknows
Enable "Auto Exec" and "Send Execution Result to LLM" in "Adjust Settings" if desired
(Optionally) Add ubuntu user to docker group and refresh group membership
Deployment of an EKS Cluster with Worker Nodes in AWS
Adding, Deleting, Listing DagKnows Proxy credentials or key-value pairs
Comprehensive AWS Security and Compliance Evaluation Workflow (SOC2 Super Runbook)
AWS EKS Version Update 1.29 to 1.30 via terraform
Instruction to allow WinRM connection
MSP Usecase: User Onboarding Azure + M365
Post a message to a Slack channel
How to debug a kafka cluster and kafka topics?
Open VPN Troubleshooting (Powershell)
Execute a simple task on the proxy
Assign the proxy role to a user
Create roles to access credentials in proxy
Install OpenVPN client on Windows laptop
Setup Kubernetes kubectl and Minikube on Ubuntu 22.04 LTS
Install Prometheus and Grafana on the minikube cluster on EC2 instance in the monitoring namespace
update the EKS versions in different clusters
AI agent session 2024-09-12T09:36:14-07:00 by Sarang Dharmapurikar
Parse EDN content and give a JSON out
Check whether a user is there on Azure AD and if the user account status is enabled
Get the input parameters of a Jenkins pipeline
Audit of AWS S3 Buckets for Server Access Logging
The workflow involves checking AWS S3 buckets to determine if Server Access Logging is enabled. The results are organized by region, highlighting the number of buckets lacking this feature. This process helps in identifying potential security and compliance gaps. By tabulating the data, it provides a clear overview of the current logging status across different regions. The outcome aids in prioritizing actions to enable logging where necessary.
- 1ed86wPL2sDzC5dd22dCGList all AWS S3 buckets across all regions.
1
List all AWS S3 buckets across all regions.
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.The script lists all AWS S3 buckets using the provided AWS credentials.
inputsoutputsimport boto3 # Retrieve AWS credentials aws_access_key_id = getEnvVar('AWS_ACCESS_KEY_ID') aws_secret_access_key = getEnvVar('AWS_SECRET_ACCESS_KEY') # Initialize a session using Boto3 session = boto3.Session( aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key ) # Create an S3 client s3_client = session.client('s3') # List all buckets try: response = s3_client.list_buckets() buckets_list = [bucket['Name'] for bucket in response['Buckets']] print("Buckets List:", buckets_list) except Exception as e: print(f"Error listing buckets: {e}")copied1 - 2cbhL3PgpnoNlPcfgA6RNCheck each S3 bucket to determine if Server Access Logging is enabled.
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Check each S3 bucket to determine if Server Access Logging is enabled.
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.The script checks each S3 bucket to determine if Server Access Logging is enabled and outputs the status.
inputsoutputsimport boto3 import json # Retrieve AWS credentials aws_access_key_id = getEnvVar('AWS_ACCESS_KEY_ID') aws_secret_access_key = getEnvVar('AWS_SECRET_ACCESS_KEY') # Initialize a session using Boto3 session = boto3.Session( aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key ) # Create an S3 client s3_client = session.client('s3') logging_status = {} # Check each bucket for server access logging for bucket in buckets_list: try: response = s3_client.get_bucket_logging(Bucket=bucket) if 'LoggingEnabled' in response: logging_status[bucket] = 'Enabled' else: logging_status[bucket] = 'Not Enabled' except Exception as e: logging_status[bucket] = f'Error: {str(e)}' # Print the logging status print("Logging Status:", json.dumps(logging_status, indent=4, default=str))copied2