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
Filter out Unused Secrets from AWS Secrets Manager
This task aims to pinpoint secrets within AWS Secrets Manager that haven't been accessed for a specified duration, such as the past 90 days. Over time, certain secrets may not be referenced or utilized, indicating they may no longer be needed. By identifying these inactive secrets, organizations can assess their continued relevance, streamline their secrets inventory, and enhance security by minimizing potential exposure points. Before taking any action based on the results, it's crucial to review the list and ensure no critical secrets are mistakenly categorized as "unused."
- 1fOUMq7LdcxtI7gnnRTqIDelete Secret from AWS Secrets Manager
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Delete Secret from AWS Secrets Manager
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.This task focuses on securely removing a specified secret from AWS Secrets Manager. Deleting secrets can be an essential step in managing sensitive information, especially if a secret is no longer in use or has been compromised. By executing this task, the targeted secret will be permanently erased from AWS Secrets Manager, ensuring it can't be accessed or retrieved. It's crucial to double-check the secret's relevance and backup any necessary data before deletion to prevent any unintended data loss or service disruptions.
inputsoutputsimport boto3 from botocore.exceptions import ClientError, NoCredentialsError, PartialCredentialsError creds = _get_creds(cred_label)['creds'] access_key = creds['username'] secret_key = creds['password'] def delete_secret(secrets_client, secret_name): try: secrets_client.delete_secret(SecretId=secret_name) print(f"Deleted secret: {secret_name}") return True except ClientError as e: # Handle specific known errors if e.response['Error']['Code'] == 'ResourceNotFoundException': print(f"Secret {secret_name} not found. Skipping.") else: print(f"Error deleting secret {secret_name}: {e}") return False # To handle any other boto3 specific errors except (NoCredentialsError, PartialCredentialsError): print("Authentication error. Please check your AWS credentials.") return False # A catch-all for other exceptions which we may not anticipate except Exception as e: print(f"An unexpected error occurred: {e}") return False # Main block # Check if all_unused_secrets is defined and is not None; if not, initialize as an empty list # all_unused_secrets passed down from get_all_secrets task all_unused_secrets = all_unused_secrets if 'all_unused_secrets' in locals() and all_unused_secrets is not None else [] ''' # Sample data for testing purposes. This will be passed from the upstream task. all_unused_secrets = [ {'region': 'us-east-1', 'secret': 'sample_secret_1'}, {'region': 'us-east-2', 'secret': 'sample_secret_2'}, # ... add more secrets and regions as needed ] # Example data ''' if all_unused_secrets: for secret_data in all_unused_secrets: region = secret_data['region'] secret_name = secret_data['secret'] try: # Initialize the secrets client for the given region secrets_client = boto3.client('secretsmanager',aws_access_key_id=access_key,aws_secret_access_key=secret_key, region_name=region) # Attempt to delete the secret delete_secret(secrets_client, secret_name) except Exception as e: print(f"An unexpected error occurred in {region}: {e}") else: print("No secrets provided. Exiting.")copied1