AWS S3 Alias Records are vulnerable

Using Console

Using CLI

Identify Vulnerable S3 Alias Records:
- List all Route 53 hosted zones and alias records pointing to S3 buckets.
```
aws route53 list-hosted-zones
```
```
aws route53 list-resource-record-sets --hosted-zone-id HOSTED_ZONE_ID
```
Replace HOSTED_ZONE_ID with the ID of each hosted zone.

Update S3 Bucket Policies:

For each S3 bucket referenced in the alias record, ensure that the bucket is not publicly accessible or misconfigured. You can update the bucket policy to deny access from all principals using the AWS CLI. Here’s an example command:

aws s3api put-bucket-policy --bucket BUCKET_NAME --policy '{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Deny",
            "Principal": "*",
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::BUCKET_NAME/*"
        }
    ]
}'

Replace BUCKET_NAME with the name of the S3 bucket.

Verify Remediation:
- After updating the bucket policy, verify that the S3 buckets are not publicly accessible or misconfigured.
```
aws s3api get-bucket-policy --bucket BUCKET_NAME
```
Replace BUCKET_NAME with the name of the S3 bucket.
Repeat for Other Vulnerable Records:
- Repeat the above steps for each vulnerable S3 alias record identified.

By updating the bucket policy to deny access from all principals, you effectively remove public access to the S3 bucket. Make sure to review and adjust the bucket policy according to your specific requirements and access control needs. Also, ensure that you have the necessary permissions to update S3 bucket policies.This remediation assumes that the S3 buckets should not be publicly accessible. If public access is required, ensure that appropriate security measures are in place to protect the data.

Using Python

Here’s a Python script to identify and remediate vulnerable DNS Alias records:

import boto3

class DNSAliasChecker:
    def __init__(self):
        self.route53_client = boto3.client('route53')
        self.s3_client = boto3.client('s3')

    def get_vulnerable_alias_records(self):
        failures = []
        response = self.route53_client.list_hosted_zones()
        for hosted_zone in response['HostedZones']:
            hosted_zone_id = hosted_zone['Id'].split('/')[-1]
            records = self.route53_client.list_resource_record_sets(HostedZoneId=hosted_zone_id)
            for record in records['ResourceRecordSets']:
                if self.is_record_vulnerable(record):
                    failures.append(record)
        return failures

    def is_record_vulnerable(self, record):
        alias_target = record.get("AliasTarget", {})
        if "amazonaws.com" in alias_target.get("DNSName", "") and "s3-website" in alias_target.get("DNSName", ""):
            return True
        return False

    def remediate_vulnerable_record(self, record_name):
        # Implement remediation logic here
        print(f"Record {record_name} has been remediated.")

# Instantiate the class
checker = DNSAliasChecker()

# Get vulnerable alias records
vulnerable_records = checker.get_vulnerable_alias_records()

# Remediate vulnerable records
for record in vulnerable_records:
    checker.remediate_vulnerable_record(record['Name'])

This Python script identifies DNS Alias records vulnerable to S3 buckets and provides a placeholder for the remediation logic. You would need to implement the logic to secure the referenced S3 buckets.Make sure to have appropriate IAM permissions for managing Route 53 hosted zones and S3 buckets if you’re using AWS CLI or Python script.

AWS Introduction

AWS Pricing

AWS Threats

AWS Misconfigurations

AWS S3 Alias Records are vulnerable

More Info:

Risk Level

Address

Compliance Standards

Triage and Remediation

Remediation

AWS Introduction

AWS Pricing

AWS Threats

AWS Misconfigurations

​More Info:

​Risk Level

​Address

​Compliance Standards

​Triage and Remediation