Tag: amazon web services

I’m using an Amazon Web Services Security Group as a way to allow traffic into an EC2 instance for the instance’s users. The users can give themselves access through a web interface that I wrote for them. Maybe I’ll cover that in a different post.

I found recently that the Security Group was nearing its maximum rule list. So I decided to start purging rules which would ultimately force them to re-add their IP addresses to the group.

Going in and manually removing rules is rather time-consuming. I figured I could write a script that would handle it for me. The first step was to update my previous script that inserts the rule to add a tag to the rule. The function below takes input of Security Group Id’s as a list and returns all of the rules.

def get_sg_rules(sg_id):
    client = boto3.client('ec2')
    response = client.describe_security_group_rules(
    Filters=[
        {
            'Name': 'group-id',
            'Values': sg_id
        }
    ],
    )
    return response

The script below iterates through each of the rules returned and will append the tag of “dateAdded” and a stringified date code.

for sg_rule in get_sg_rules(sg_list)['SecurityGroupRules']:
        try:
            client = boto3.client('ec2')
            response = client.create_tags(
            DryRun=False,
            Resources=[
                sg_rule['SecurityGroupRuleId'],
            ],
            Tags=[
                {
                    'Key': 'dateAdded',
                    'Value': '2022-11-05'
                },
            ]
        )
        except ClientError as e:
            print(e)

I then wrote the following Lambda function that runs every day and checks for any expired rules. The schedule is set up by a Cloudwatch Event’s rule.

import boto3
from datetime import datetime, timedelta
from botocore.exceptions import ClientError
def return_today():
    now = datetime.now()
    return now
def get_sg_rules(sg_id, old_date):
    client = boto3.client('ec2')
    response = client.describe_security_group_rules(
    Filters=[
        {
            'Name': 'group-id',
            'Values': sg_id
        },
        {
            'Name': 'tag:dateAdded',
            'Values': [old_date]
        }
    ],
    )
    
    return response

def lambda_handler(event, context):
    sg_list = ["xxxx", "xxx"]
    old_date = datetime.strftime(return_today() - timedelta(days=30), "%Y-%m-%d")
    print(old_date)
    for sg_rule in get_sg_rules(sg_list, old_date)['SecurityGroupRules']:
        try:
            client = boto3.client("ec2")
            response = client.revoke_security_group_ingress(
                GroupId=sg_rule['GroupId'],
                SecurityGroupRuleIds=[sg_rule['SecurityGroupRuleId']]
                )
            print(response)
            print("Successfully deleted the rule")
        except ClientError as e:
            print(e)
            print("Failed to delete rule")

You’ll see that the code has a list of Security Groups to check. It compares the current date to that of 30 days previous. If the tag of “dateAdded” matches that previous date then we will go ahead and remove the rule.

I hope this helps you automate your AWS Accounts. Below are links to the code repository so you can edit the code as needed. Please share it with your friends if this helps you!

Github