| agent: | Auto Exec |
Troubleshooting: Server is not reachable or unable to connect
Add credentials for various integrations
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
Audit of AWS IAM Users for MFA Compliance
The workflow involves listing AWS IAM users who have console passwords and checking if they have Multi-Factor Authentication (MFA) enabled. Users are then categorized based on whether MFA is enabled or not. The categorization helps in identifying users who are compliant with the security rule of having MFA enabled. This process ensures that all users with console access are adhering to security best practices. The outcome is a clear understanding of the current compliance status regarding MFA among IAM users.
- 1pojmnY6j9Wk8nca6JkglList AWS IAM users with console passwords which do not have Multi-Factor Authentication (MFA) enabled, categorize them based on MFA Enabled or not and if they are compliant or not based on this rule.
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There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.This script lists AWS IAM users with console passwords and checks if they have MFA enabled, categorizing them based on compliance.
inputsoutputsimport boto3 import json # Initialize boto3 client for IAM client = boto3.client( 'iam', aws_access_key_id=getEnvVar('AWS_ACCESS_KEY_ID'), aws_secret_access_key=getEnvVar('AWS_SECRET_ACCESS_KEY'), region_name='us-west-2' ) # Get all IAM users users = client.list_users()['Users'] users_with_mfa_status = {} for user in users: username = user['UserName'] # Check if the user has a console password login_profile = None try: login_profile = client.get_login_profile(UserName=username) except client.exceptions.NoSuchEntityException: # User does not have a console password continue # Get MFA devices for the user mfa_devices = client.list_mfa_devices(UserName=username)['MFADevices'] # Determine MFA status mfa_enabled = len(mfa_devices) > 0 compliance_status = 'Compliant' if mfa_enabled else 'Non-Compliant' users_with_mfa_status[username] = { 'MFAEnabled': mfa_enabled, 'ComplianceStatus': compliance_status } # Print the categorized users print(json.dumps(users_with_mfa_status, indent=4, default=str))copied1