Tag Archives: MFA

The 10 Most Viewed Security-Related AWS Knowledge Center Articles and Videos for November 2017

Post Syndicated from Maggie Burke original https://aws.amazon.com/blogs/security/the-10-most-viewed-security-related-aws-knowledge-center-articles-and-videos-for-november-2017/

AWS Knowledge Center image

The AWS Knowledge Center helps answer the questions most frequently asked by AWS Support customers. The following 10 Knowledge Center security articles and videos have been the most viewed this month. It’s likely you’ve wondered about a few of these topics yourself, so here’s a chance to learn the answers!

  1. How do I create an AWS Identity and Access Management (IAM) policy to restrict access for an IAM user, group, or role to a particular Amazon Virtual Private Cloud (VPC)?
    Learn how to apply a custom IAM policy to restrict IAM user, group, or role permissions for creating and managing Amazon EC2 instances in a specified VPC.
  2. How do I use an MFA token to authenticate access to my AWS resources through the AWS CLI?
    One IAM best practice is to protect your account and its resources by using a multi-factor authentication (MFA) device. If you plan use the AWS Command Line Interface (CLI) while using an MFA device, you must create a temporary session token.
  3. Can I restrict an IAM user’s EC2 access to specific resources?
    This article demonstrates how to link multiple AWS accounts through AWS Organizations and isolate IAM user groups in their own accounts.
  4. I didn’t receive a validation email for the SSL certificate I requested through AWS Certificate Manager (ACM)—where is it?
    Can’t find your ACM validation emails? Be sure to check the email address to which you requested that ACM send validation emails.
  5. How do I create an IAM policy that has a source IP restriction but still allows users to switch roles in the AWS Management Console?
    Learn how to write an IAM policy that not only includes a source IP restriction but also lets your users switch roles in the console.
  6. How do I allow users from another account to access resources in my account through IAM?
    If you have the 12-digit account number and permissions to create and edit IAM roles and users for both accounts, you can permit specific IAM users to access resources in your account.
  7. What are the differences between a service control policy (SCP) and an IAM policy?
    Learn how to distinguish an SCP from an IAM policy.
  8. How do I share my customer master keys (CMKs) across multiple AWS accounts?
    To grant another account access to your CMKs, create an IAM policy on the secondary account that grants access to use your CMKs.
  9. How do I set up AWS Trusted Advisor notifications?
    Learn how to receive free weekly email notifications from Trusted Advisor.
  10. How do I use AWS Key Management Service (AWS KMS) encryption context to protect the integrity of encrypted data?
    Encryption context name-value pairs used with AWS KMS encryption and decryption operations provide a method for checking ciphertext authenticity. Learn how to use encryption context to help protect your encrypted data.

The AWS Security Blog will publish an updated version of this list regularly going forward. You also can subscribe to the AWS Knowledge Center Videos playlist on YouTube.

– Maggie

Visualize AWS Cloudtrail Logs using AWS Glue and Amazon Quicksight

Post Syndicated from Luis Caro Perez original https://aws.amazon.com/blogs/big-data/streamline-aws-cloudtrail-log-visualization-using-aws-glue-and-amazon-quicksight/

Being able to easily visualize AWS CloudTrail logs gives you a better understanding of how your AWS infrastructure is being used. It can also help you audit and review AWS API calls and detect security anomalies inside your AWS account. To do this, you must be able to perform analytics based on your CloudTrail logs.

In this post, I walk through using AWS Glue and AWS Lambda to convert AWS CloudTrail logs from JSON to a query-optimized format dataset in Amazon S3. I then use Amazon Athena and Amazon QuickSight to query and visualize the data.

Solution overview

To process CloudTrail logs, you must implement the following architecture:

CloudTrail delivers log files in an Amazon S3 bucket folder. To correctly crawl these logs, you modify the file contents and folder structure using an Amazon S3-triggered Lambda function that stores the transformed files in an S3 bucket single folder. When the files are in a single folder, AWS Glue scans the data, converts it into Apache Parquet format, and catalogs it to allow for querying and visualization using Amazon Athena and Amazon QuickSight.

Walkthrough

Let’s look at the steps that are required to build the solution.

Set up CloudTrail logs

First, you need to set up a trail that delivers log files to an S3 bucket. To create a trail in CloudTrail, follow the instructions in Creating a Trail.

When you finish, the trail settings page should look like the following screenshot:

In this example, I set up log files to be delivered to the cloudtraillfcaro bucket.

Consolidate CloudTrail reports into a single folder using Lambda

AWS CloudTrail delivers log files using the following folder structure inside the configured Amazon S3 bucket:

AWSLogs/ACCOUNTID/CloudTrail/REGION/YEAR/MONTH/HOUR/filename.json.gz

Additionally, log files have the following structure:

{
    "Records": [{
        "eventVersion": "1.01",
        "userIdentity": {
            "type": "IAMUser",
            "principalId": "AIDAJDPLRKLG7UEXAMPLE",
            "arn": "arn:aws:iam::123456789012:user/Alice",
            "accountId": "123456789012",
            "accessKeyId": "AKIAIOSFODNN7EXAMPLE",
            "userName": "Alice",
            "sessionContext": {
                "attributes": {
                    "mfaAuthenticated": "false",
                    "creationDate": "2014-03-18T14:29:23Z"
                }
            }
        },
        "eventTime": "2014-03-18T14:30:07Z",
        "eventSource": "cloudtrail.amazonaws.com",
        "eventName": "StartLogging",
        "awsRegion": "us-west-2",
        "sourceIPAddress": "72.21.198.64",
        "userAgent": "signin.amazonaws.com",
        "requestParameters": {
            "name": "Default"
        },
        "responseElements": null,
        "requestID": "cdc73f9d-aea9-11e3-9d5a-835b769c0d9c",
        "eventID": "3074414d-c626-42aa-984b-68ff152d6ab7"
    },
    ... additional entries ...
    ]

If AWS Glue crawlers are used to catalog these files as they are written, the following obstacles arise:

  1. AWS Glue identifies different tables per different folders because they don’t follow a traditional partition format.
  2. Based on the structure of the file content, AWS Glue identifies the tables as having a single column of type array.
  3. CloudTrail logs have JSON attributes that use uppercase letters. According to the Best Practices When Using Athena with AWS Glue, it is recommended that you convert these to lowercase.

To have AWS Glue catalog all log files in a single table with all the columns describing each event, implement the following Lambda function:

from __future__ import print_function
import json
import urllib
import boto3
import gzip

s3 = boto3.resource('s3')
client = boto3.client('s3')

def convertColumntoLowwerCaps(obj):
    for key in obj.keys():
        new_key = key.lower()
        if new_key != key:
            obj[new_key] = obj[key]
            del obj[key]
    return obj


def lambda_handler(event, context):

    bucket = event['Records'][0]['s3']['bucket']['name']
    key = urllib.unquote_plus(event['Records'][0]['s3']['object']['key'].encode('utf8'))
    print(bucket)
    print(key)
    try:
        newKey = 'flatfiles/' + key.replace("/", "")
        client.download_file(bucket, key, '/tmp/file.json.gz')
        with gzip.open('/tmp/out.json.gz', 'w') as output, gzip.open('/tmp/file.json.gz', 'rb') as file:
            i = 0
            for line in file: 
                for record in json.loads(line,object_hook=convertColumntoLowwerCaps)['records']:
            		if i != 0:
            		    output.write("\n")
            		output.write(json.dumps(record))
            		i += 1
        client.upload_file('/tmp/out.json.gz', bucket,newKey)
        return "success"
    except Exception as e:
        print(e)
        print('Error processing object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket))
        raise e

The function goes over each element of the records array, changes uppercase letters to lowercase in column names, and inserts each element of the array as a single line of a new file. The new file is saved inside a flatfiles folder created by the function without any subfolders in the S3 bucket.

The function should have a role containing a policy with at least the following permissions:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": [
                "s3:*"
            ],
            "Resource": [
                "arn:aws:s3:::cloudtraillfcaro/*",
                "arn:aws:s3:::cloudtraillfcaro"
            ],
            "Effect": "Allow"
        }
    ]
}

In this example, CloudTrail delivers logs to the cloudtraillfcaro bucket. Make sure that you replace this name with your bucket name in the policy. For more information about how to work with inline policies, see Working with Inline Policies.

After the Lambda function is created, you can set up the following trigger using the Triggers tab on the AWS Lambda console.

Choose Add trigger, and choose S3 as a source of the trigger.

After choosing the source, configure the following settings:

In the trigger, any file that is written to the path for the log files—which in this case is AWSLogs/119582755581/CloudTrail/—is processed. Make sure that the Enable trigger check box is selected and that the bucket and prefix parameters match your use case.

After you set up the function and receive log files, the bucket (in this case cloudtraillfcaro) should contain the processed files inside the flatfiles folder.

Catalog source data

Once the files are processed by the Lambda function, set up a crawler named cloudtrail to catalog them.

The crawler must point to the flatfiles folder.

All the crawlers and AWS Glue jobs created for this solution must have a role with the AWSGlueServiceRole managed policy and an inline policy with permissions to modify the S3 buckets used on the Lambda function. For more information, see Working with Managed Policies.

The role should look like the following:

In this example, the inline policy named s3perms contains the permissions to modify the S3 buckets.

After you choose the role, you can schedule the crawler to run on demand.

A new database is created, and the crawler is set to use it. In this case, the cloudtrail database is used for all the tables.

After the crawler runs, a single table should be created in the catalog with the following structure:

The table should contain the following columns:

Create and run the AWS Glue job

To convert all the CloudTrail logs to a columnar store in Parquet, set up an AWS Glue job by following these steps.

Upload the following script into a bucket in Amazon S3:

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
import boto3
import time

## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv, ['JOB_NAME'])

sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)

datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "cloudtrail", table_name = "flatfiles", transformation_ctx = "datasource0")
resolvechoice1 = ResolveChoice.apply(frame = datasource0, choice = "make_struct", transformation_ctx = "resolvechoice1")
relationalized1 = resolvechoice1.relationalize("trail", args["TempDir"]).select("trail")
datasink = glueContext.write_dynamic_frame.from_options(frame = relationalized1, connection_type = "s3", connection_options = {"path": "s3://cloudtraillfcaro/parquettrails"}, format = "parquet", transformation_ctx = "datasink4")
job.commit()

In the example, you load the script as a file named cloudtrailtoparquet.py. Make sure that you modify the script and update the “{"path": "s3://cloudtraillfcaro/parquettrails"}” with the destination in which you want to store your results.

After uploading the script, add a new AWS Glue job. Choose a name and role for the job, and choose the option of running the job from An existing script that you provide.

To avoid processing the same data twice, enable the Job bookmark setting in the Advanced properties section of the job properties.

Choose Next twice, and then choose Finish.

If logs are already in the flatfiles folder, you can run the job on demand to generate the first set of results.

Once the job starts running, wait for it to complete.

When the job is finished, its Run status should be Succeeded. After that, you can verify that the Parquet files are written to the Amazon S3 location.

Catalog results

To be able to process results from Athena, you can use an AWS Glue crawler to catalog the results of the AWS Glue job.

In this example, the crawler is set to use the same database as the source named cloudtrail.

You can run the crawler using the console. When the crawler finishes running and has processed the Parquet results, a new table should be created in the AWS Glue Data Catalog. In this example, it’s named parquettrails.

The table should have the classification set to parquet.

It should have the same columns as the flatfiles table, with the exception of the struct type columns, which should be relationalized into several columns:

In this example, notice how the requestparameters column, which was a struct in the original table (flatfiles), was transformed to several columns—one for each key value inside it. This is done using a transformation native to AWS Glue called relationalize.

Query results with Athena

After crawling the results, you can query them using Athena. For example, to query what events took place in the time frame between 2017-10-23t12:00:00 and 2017-10-23t13:00, use the following select statement:

select *
from cloudtrail.parquettrails
where eventtime > '2017-10-23T12:00:00Z' AND eventtime < '2017-10-23T13:00:00Z'
order by eventtime asc;

Be sure to replace cloudtrail.parquettrails with the names of your database and table that references the Parquet results. Replace the datetimes with an hour when your account had activity and was processed by the AWS Glue job.

Visualize results using Amazon QuickSight

Once you can query the data using Athena, you can visualize it using Amazon QuickSight. Before connecting Amazon QuickSight to Athena, be sure to grant QuickSight access to Athena and the associated S3 buckets in your account. For more information, see Managing Amazon QuickSight Permissions to AWS Resources. You can then create a new data set in Amazon QuickSight based on the Athena table that you created.

After setting up permissions, you can create a new analysis in Amazon QuickSight by choosing New analysis.

Then add a new data set.

Choose Athena as the source.

Give the data source a name (in this case, I named it cloudtrail).

Choose the name of the database and the table referencing the Parquet results.

Then choose Visualize.

After that, you should see the following screen:

Now you can create some visualizations. First, search for the sourceipaddress column, and drag it to the AutoGraph section.

You can see a list of the IP addresses that you have used to interact with AWS. To review whether these IP addresses have been used from IAM users, internal AWS services, or roles, use the type value that is inside the useridentity field of the original log files. Thanks to the relationalize transformation, this value is available as the useridentity.type column. After the column is added into the Group/Color box, the visualization should look like the following:

You can now see and distinguish the most used IPs and whether they are used from roles, AWS services, or IAM users.

After following all these steps, you can use Amazon QuickSight to add different columns from CloudTrail and perform different types of visualizations. You can build operational dashboards that continuously monitor AWS infrastructure usage and access. You can share those dashboards with others in your organization who might need to see this data.

Summary

In this post, you saw how you can use a simple Lambda function and an AWS Glue script to convert text files into Parquet to improve Athena query performance and data compression. The post also demonstrated how to use AWS Lambda to preprocess files in Amazon S3 and transform them into a format that is recognizable by AWS Glue crawlers.

This example, used AWS CloudTrail logs, but you can apply the proposed solution to any set of files that after preprocessing, can be cataloged by AWS Glue.


Additional Reading

Learn how to Harmonize, Query, and Visualize Data from Various Providers using AWS Glue, Amazon Athena, and Amazon QuickSight.


About the Authors

Luis Caro is a Big Data Consultant for AWS Professional Services. He works with our customers to provide guidance and technical assistance on big data projects, helping them improving the value of their solutions when using AWS.

 

 

 

Introducing AWS Directory Service for Microsoft Active Directory (Standard Edition)

Post Syndicated from Peter Pereira original https://aws.amazon.com/blogs/security/introducing-aws-directory-service-for-microsoft-active-directory-standard-edition/

Today, AWS introduced AWS Directory Service for Microsoft Active Directory (Standard Edition), also known as AWS Microsoft AD (Standard Edition), which is managed Microsoft Active Directory (AD) that is performance optimized for small and midsize businesses. AWS Microsoft AD (Standard Edition) offers you a highly available and cost-effective primary directory in the AWS Cloud that you can use to manage users, groups, and computers. It enables you to join Amazon EC2 instances to your domain easily and supports many AWS and third-party applications and services. It also can support most of the common use cases of small and midsize businesses. When you use AWS Microsoft AD (Standard Edition) as your primary directory, you can manage access and provide single sign-on (SSO) to cloud applications such as Microsoft Office 365. If you have an existing Microsoft AD directory, you can also use AWS Microsoft AD (Standard Edition) as a resource forest that contains primarily computers and groups, allowing you to migrate your AD-aware applications to the AWS Cloud while using existing on-premises AD credentials.

In this blog post, I help you get started by answering three main questions about AWS Microsoft AD (Standard Edition):

  1. What do I get?
  2. How can I use it?
  3. What are the key features?

After answering these questions, I show how you can get started with creating and using your own AWS Microsoft AD (Standard Edition) directory.

1. What do I get?

When you create an AWS Microsoft AD (Standard Edition) directory, AWS deploys two Microsoft AD domain controllers powered by Microsoft Windows Server 2012 R2 in your Amazon Virtual Private Cloud (VPC). To help deliver high availability, the domain controllers run in different Availability Zones in the AWS Region of your choice.

As a managed service, AWS Microsoft AD (Standard Edition) configures directory replication, automates daily snapshots, and handles all patching and software updates. In addition, AWS Microsoft AD (Standard Edition) monitors and automatically recovers domain controllers in the event of a failure.

AWS Microsoft AD (Standard Edition) has been optimized as a primary directory for small and midsize businesses with the capacity to support approximately 5,000 employees. With 1 GB of directory object storage, AWS Microsoft AD (Standard Edition) has the capacity to store 30,000 or more total directory objects (users, groups, and computers). AWS Microsoft AD (Standard Edition) also gives you the option to add domain controllers to meet the specific performance demands of your applications. You also can use AWS Microsoft AD (Standard Edition) as a resource forest with a trust relationship to your on-premises directory.

2. How can I use it?

With AWS Microsoft AD (Standard Edition), you can share a single directory for multiple use cases. For example, you can share a directory to authenticate and authorize access for .NET applications, Amazon RDS for SQL Server with Windows Authentication enabled, and Amazon Chime for messaging and video conferencing.

The following diagram shows some of the use cases for your AWS Microsoft AD (Standard Edition) directory, including the ability to grant your users access to external cloud applications and allow your on-premises AD users to manage and have access to resources in the AWS Cloud. Click the diagram to see a larger version.

Diagram showing some ways you can use AWS Microsoft AD (Standard Edition)--click the diagram to see a larger version

Use case 1: Sign in to AWS applications and services with AD credentials

You can enable multiple AWS applications and services such as the AWS Management Console, Amazon WorkSpaces, and Amazon RDS for SQL Server to use your AWS Microsoft AD (Standard Edition) directory. When you enable an AWS application or service in your directory, your users can access the application or service with their AD credentials.

For example, you can enable your users to sign in to the AWS Management Console with their AD credentials. To do this, you enable the AWS Management Console as an application in your directory, and then assign your AD users and groups to IAM roles. When your users sign in to the AWS Management Console, they assume an IAM role to manage AWS resources. This makes it easy for you to grant your users access to the AWS Management Console without needing to configure and manage a separate SAML infrastructure.

Use case 2: Manage Amazon EC2 instances

Using familiar AD administration tools, you can apply AD Group Policy objects (GPOs) to centrally manage your Amazon EC2 for Windows or Linux instances by joining your instances to your AWS Microsoft AD (Standard Edition) domain.

In addition, your users can sign in to your instances with their AD credentials. This eliminates the need to use individual instance credentials or distribute private key (PEM) files. This makes it easier for you to instantly grant or revoke access to users by using AD user administration tools you already use.

Use case 3: Provide directory services to your AD-aware workloads

AWS Microsoft AD (Standard Edition) is an actual Microsoft AD that enables you to run traditional AD-aware workloads such as Remote Desktop Licensing Manager, Microsoft SharePoint, and Microsoft SQL Server Always On in the AWS Cloud. AWS Microsoft AD (Standard Edition) also helps you to simplify and improve the security of AD-integrated .NET applications by using group Managed Service Accounts (gMSAs) and Kerberos constrained delegation (KCD).

Use case 4: SSO to Office 365 and other cloud applications

You can use AWS Microsoft AD (Standard Edition) to provide SSO for cloud applications. You can use Azure AD Connect to synchronize your users into Azure AD, and then use Active Directory Federation Services (AD FS) so that your users can access Microsoft Office 365 and other SAML 2.0 cloud applications by using their AD credentials.

Use case 5: Extend your on-premises AD to the AWS Cloud

If you already have an AD infrastructure and want to use it when migrating AD-aware workloads to the AWS Cloud, AWS Microsoft AD (Standard Edition) can help. You can use AD trusts to connect AWS Microsoft AD (Standard Edition) to your existing AD. This means your users can access AD-aware and AWS applications with their on-premises AD credentials, without needing you to synchronize users, groups, or passwords.

For example, your users can sign in to the AWS Management Console and Amazon WorkSpaces by using their existing AD user names and passwords. Also, when you use AD-aware applications such as SharePoint with AWS Microsoft AD (Standard Edition), your logged-in Windows users can access these applications without needing to enter credentials again.

3. What are the key features?

AWS Microsoft AD (Standard Edition) includes the features detailed in this section.

Extend your AD schema

With AWS Microsoft AD, you can run customized AD-integrated applications that require changes to your directory schema, which defines the structures of your directory. The schema is composed of object classes such as user objects, which contain attributes such as user names. AWS Microsoft AD lets you extend the schema by adding new AD attributes or object classes that are not present in the core AD attributes and classes.

For example, if you have a human resources application that uses employee badge color to assign specific benefits, you can extend the schema to include a badge color attribute in the user object class of your directory. To learn more, see How to Move More Custom Applications to the AWS Cloud with AWS Directory Service.

Create user-specific password policies

With user-specific password policies, you can apply specific restrictions and account lockout policies to different types of users in your AWS Microsoft AD (Standard Edition) domain. For example, you can enforce strong passwords and frequent password change policies for administrators, and use less-restrictive policies with moderate account lockout policies for general users.

Add domain controllers

You can increase the performance and redundancy of your directory by adding domain controllers. This can help improve application performance by enabling directory clients to load-balance their requests across a larger number of domain controllers.

Encrypt directory traffic

You can use AWS Microsoft AD (Standard Edition) to encrypt Lightweight Directory Access Protocol (LDAP) communication between your applications and your directory. By enabling LDAP over Secure Sockets Layer (SSL)/Transport Layer Security (TLS), also called LDAPS, you encrypt your LDAP communications end to end. This helps you to protect sensitive information you keep in your directory when it is accessed over untrusted networks.

Improve the security of signing in to AWS services by using multi-factor authentication (MFA)

You can improve the security of signing in to AWS services, such as Amazon WorkSpaces and Amazon QuickSight, by enabling MFA in your AWS Microsoft AD (Standard Edition) directory. With MFA, your users must enter a one-time passcode (OTP) in addition to their AD user names and passwords to access AWS applications and services you enable in AWS Microsoft AD (Standard Edition).

Get started

To get started, use the Directory Service console to create your first directory with just a few clicks. If you have not used Directory Service before, you may be eligible for a 30-day limited free trial.

Summary

In this blog post, I explained what AWS Microsoft AD (Standard Edition) is and how you can use it. With a single directory, you can address many use cases for your business, making it easier to migrate and run your AD-aware workloads in the AWS Cloud, provide access to AWS applications and services, and connect to other cloud applications. To learn more about AWS Microsoft AD, see the Directory Service home page.

If you have comments about this post, submit them in the “Comments” section below. If you have questions about this blog post, start a new thread on the Directory Service forum.

– Peter

Greater Transparency into Actions AWS Services Perform on Your Behalf by Using AWS CloudTrail

Post Syndicated from Ujjwal Pugalia original https://aws.amazon.com/blogs/security/get-greater-transparency-into-actions-aws-services-perform-on-your-behalf-by-using-aws-cloudtrail/

To make managing your AWS account easier, some AWS services perform actions on your behalf, including the creation and management of AWS resources. For example, AWS Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring. To make these AWS actions more transparent, AWS adds an AWS Identity and Access Management (IAM) service-linked roles to your account for each linked service you use. Service-linked roles let you view all actions an AWS service performs on your behalf by using AWS CloudTrail logs. This helps you monitor and audit the actions AWS services perform on your behalf. No additional actions are required from you and you can continue using AWS services the way you do today.

To learn more about which AWS services use service-linked roles and log actions on your behalf to CloudTrail, see AWS Services That Work with IAM. Over time, more AWS services will support service-linked roles. For more information about service-linked roles, see Role Terms and Concepts.

In this blog post, I demonstrate how to view CloudTrail logs so that you can more easily monitor and audit AWS services performing actions on your behalf. First, I show how AWS creates a service-linked role in your account automatically when you configure an AWS service that supports service-linked roles. Next, I show how you can view the policies of a service-linked role that grants an AWS service permission to perform actions on your behalf. Finally, I  use the configured AWS service to perform an action and show you how the action appears in your CloudTrail logs.

How AWS creates a service-linked role in your account automatically

I will use Amazon Lex as the AWS service that performs actions on your behalf for this post. You can use Amazon Lex to create chatbots that allow for highly engaging conversational experiences through voice and text. You also can use chatbots on mobile devices, web browsers, and popular chat platform channels such as Slack. Amazon Lex uses Amazon Polly on your behalf to synthesize speech that sounds like a human voice.

Amazon Lex uses two IAM service-linked roles:

  • AWSServiceRoleForLexBots — Amazon Lex uses this service-linked role to invoke Amazon Polly to synthesize speech responses for your chatbot.
  • AWSServiceRoleForLexChannels — Amazon Lex uses this service-linked role to post text to your chatbot when managing channels such as Slack.

You don’t need to create either of these roles manually. When you create your first chatbot using the Amazon Lex console, Amazon Lex creates the AWSServiceRoleForLexBots role for you. When you first associate a chatbot with a messaging channel, Amazon Lex creates the AWSServiceRoleForLexChannels role in your account.

1. Start configuring the AWS service that supports service-linked roles

Navigate to the Amazon Lex console, and choose Get Started to navigate to the Create your Lex bot page. For this example, I choose a sample chatbot called OrderFlowers. To learn how to create a custom chatbot, see Create a Custom Amazon Lex Bot.

Screenshot of making the choice to create an OrderFlowers chatbot

2. Complete the configuration for the AWS service

When you scroll down, you will see the settings for the OrderFlowers chatbot. Notice the field for the IAM role with the value, AWSServiceRoleForLexBots. This service-linked role is “Automatically created on your behalf.” After you have entered all details, choose Create to build your sample chatbot.

Screenshot of the automatically created service-linked role

AWS has created the AWSServiceRoleForLexBots service-linked role in your account. I will return to using the chatbot later in this post when I discuss how Amazon Lex performs actions on your behalf and how CloudTrail logs these actions. First, I will show how you can view the permissions for the AWSServiceRoleForLexBots service-linked role by using the IAM console.

How to view actions in the IAM console that AWS services perform on your behalf

When you configure an AWS service that supports service-linked roles, AWS creates a service-linked role in your account automatically. You can view the service-linked role by using the IAM console.

1. View the AWSServiceRoleForLexBots service-linked role on the IAM console

Go to the IAM console, and choose AWSServiceRoleForLexBots on the Roles page. You can confirm that this role is a service-linked role by viewing the Trusted entities column.

Screenshot of the service-linked role

2.View the trusted entities that can assume the AWSServiceRoleForLexBots service-linked role

Choose the Trust relationships tab on the AWSServiceRoleForLexBots role page. You can view the trusted entities that can assume the AWSServiceRoleForLexBots service-linked role to perform actions on your behalf. In this example, the trusted entity is lex.amazonaws.com.

Screenshot of the trusted entities that can assume the service-linked role

3. View the policy attached to the AWSServiceRoleForLexBots service-linked role

Choose AmazonLexBotPolicy on the Permissions tab to view the policy attached to the AWSServiceRoleForLexBots service-linked role. You can view the policy summary to see that AmazonLexBotPolicy grants permission to Amazon Lex to use Amazon Polly.

Screenshot showing that AmazonLexBotPolicy grants permission to Amazon Lex to use Amazon Polly

4. View the actions that the service-linked role grants permissions to use

Choose Polly to view the action, SynthesizeSpeech, that the AmazonLexBotPolicy grants permission to Amazon Lex to perform on your behalf. Amazon Lex uses this permission to synthesize speech responses for your chatbot. I show later in this post how you can monitor this SynthesizeSpeech action in your CloudTrail logs.

Screenshot showing the the action, SynthesizeSpeech, that the AmazonLexBotPolicy grants permission to Amazon Lex to perform on your behalf

Now that I know the trusted entity and the policy attached to the service-linked role, let’s go back to the chatbot I created earlier and see how CloudTrail logs the actions that Amazon Lex performs on my behalf.

How to use CloudTrail to view actions that AWS services perform on your behalf

As discussed already, I created an OrderFlowers chatbot on the Amazon Lex console. I will use the chatbot and display how the AWSServiceRoleForLexBots service-linked role helps me track actions in CloudTrail. First, though, I must have an active CloudTrail trail created that stores the logs in an Amazon S3 bucket. I will use a trail called TestTrail and an S3 bucket called account-ids-slr.

1. Use the Amazon Lex chatbot via the Amazon Lex console

In Step 2 in the first section of this post, when I chose Create, Amazon Lex built the OrderFlowers chatbot. After the chatbot was built, the right pane showed that a Test Bot was created. Now, I choose the microphone symbol in the right pane and provide voice input to test the OrderFlowers chatbot. In this example, I tell the chatbot, “I would like to order some flowers.” The bot replies to me by asking, “What type of flowers would you like to order?”

Screenshot of voice input to test the OrderFlowers chatbot

When the chatbot replies using voice, Amazon Lex uses Amazon Polly to synthesize speech from text to voice. Amazon Lex assumes the AWSServiceRoleForLexBots service-linked role to perform the SynthesizeSpeech action.

2. Check CloudTrail to view actions performed on your behalf

Now that I have created the chatbot, let’s see which actions were logged in CloudTrail. Choose CloudTrail from the Services drop-down menu to reach the CloudTrail console. Choose Trails and choose the S3 bucket in which you are storing your CloudTrail logs.

Screenshot of the TestTrail trail

In the S3 bucket, you will find log entries for the SynthesizeSpeech event. This means that CloudTrail logged the action when Amazon Lex assumed the AWSServiceRoleForLexBots service-linked role to invoke Amazon Polly to synthesize speech responses for your chatbot. You can monitor and audit this invocation, and it provides you with transparency into Amazon Polly’s SynthesizeSpeech action that Amazon Lex invoked on your behalf. The applicable CloudTrail log section follows and I have emphasized the key lines.

{  
         "eventVersion":"1.05",
         "userIdentity":{  
           "type":"AssumedRole",
            "principalId":"{principal-id}:OrderFlowers",
            "arn":"arn:aws:sts::{account-id}:assumed-role/AWSServiceRoleForLexBots/OrderFlowers",
            "accountId":"{account-id}",
            "accessKeyId":"{access-key-id}",
            "sessionContext":{  
               "attributes":{  
                  "mfaAuthenticated":"false",
                  "creationDate":"2017-09-17T17:30:05Z"
               },
               "sessionIssuer":{  
                  "type":"Role",
                  "principalId":"{principal-id}",
                  "arn":"arn:aws:iam:: {account-id}:role/aws-service-role/lex.amazonaws.com/AWSServiceRoleForLexBots",
                  "accountId":"{account-id",
                  "userName":"AWSServiceRoleForLexBots"
               }
            },
            "invokedBy":"lex.amazonaws.com"
         },
         "eventTime":"2017-09-17T17:30:05Z",
         "eventSource":"polly.amazonaws.com",
         "eventName":"SynthesizeSpeech",
         "awsRegion":"us-east-1",
         "sourceIPAddress":"lex.amazonaws.com",
         "userAgent":"lex.amazonaws.com",
         "requestParameters":{  
            "outputFormat":"mp3",
            "textType":"text",
            "voiceId":"Salli",
            "text":"**********"
         },
         "responseElements":{  
            "requestCharacters":45,
            "contentType":"audio/mpeg"
         },
         "requestID":"{request-id}",
         "eventID":"{event-id}",
         "eventType":"AwsApiCall",
         "recipientAccountId":"{account-id}"
      }

Conclusion

Service-linked roles make it easier for you to track and view actions that linked AWS services perform on your behalf by using CloudTrail. When an AWS service supports service-linked roles to enable this additional logging, you will see a service-linked role added to your account.

If you have comments about this post, submit a comment in the “Comments” section below. If you have questions about working with service-linked roles, start a new thread on the IAM forum or contact AWS Support.

– Ujjwal

Драмата по вадене на паспорт в чужбина

Post Syndicated from Боян Юруков original https://yurukov.net/blog/2017/dramata-pasport-v-chujbina/

През май се усетих, че ми изтича паспорта. До сега винаги съм го обновявал в България, но този път пропуснах. Изчетох изискванията на сайта на Външно, направих си час през online системата и зачаках. Беше за след два месеца, но имах време.

На 10-ти юни в 8:50 бях пред консулството във Франкфурт. Часът ми беше за 9:00, когато отваря и консулството. Вече имаше опашка от към 40-тина души. Поне 5-6 бяха бебета, за които родителите се опитваха да извадят документи. Тъй като сградата е малка и никога не е била строена за консулство, опашката беше отвън и преливаше на тротоара. Естествено, минаващите на път за работа негодуваха.

Пробих си път през тълпата, тъй като бях един от малкото с час и се качих горе. Имаше две гишета. Тогава осъзнах, че съм забравил заявлението попълнено на сайта и го попълних наново за няколко минути. Когато го предадох на консулския служител, последва спор за детайли по заявлението, както защо не си нося стария паспорт. Оказа се, че въпреки практиката в България, написаното на сайта на Външно и на новия консулски портал, МВР изисквали паспортът да се предаде в консулството при подаването на заявлението. Абсурдно е, но „така искали и може да върнат заявлението, вие си знаете“. Като посочих, че в портала пише друго, последва отговор „Ако можеше през интернет, щяха всички да го правят там, нали?“ Отговорих, че по принцип може, ама…

Тогава ми светна, че всъщност има един друг портал, за който Външно похарчи стотици хиляди. Бях забравил за него (въобще много забравяне в тази история). Идеята му е да си подадеш заявлението изцяло online и така да олекоти работата на консулствата. Уловката е, че изисква електронен подпис, което е доста рядко все още.

Е, аз имам електронен подпис. Вече бях доста изнервен на служителката, събрах си документите и си тръгнах. Вечерта седнах и отворих e-services.mfa.bg. Прие електронния ми подпис и започнах да попълвам детайлите. Любопитно е, че ми показа снимката съхранявана от МВР, но се наложи на ръка да въведа почти всичко останало.

Пуснах заявлението и съвсем очаквано сайтът се счупи. Това всъщност е известно отдавана. Пробвах в случай, че имам някакъв късмет. Само един човек е успял да подаде заявление така малко след пускането на проекта. От тогава насам прескъпият портал просто не работи. Опитах се на няколко различни конфигурации, но резултатът беше същия.

Върнах се към консулския портал consulatebg.eu, попълних отново електронното заявление и си направих нов час за след месец и половина. Толкова се чака. Ако днес се опитате да си направите час във Франкфурт, най-скорошният е на 14-ти септември. Може да се пробвате в съседните консулства, но и там чакането не е по-малко. След като подадете заявлението, може да се наложи да чакате между един и шест месеца за самия паспорт. Зависи от натоварването и бързината на чиновниците в България.

Иронията тук е, че ако подам заявление за немско гражданство, процедурата може да мине дори по-бързо от обновяването на българския. Това, както и лошите консулски услуги са сред основните причини толкова българи да взимат немски паспорт. Аз съм решил, че просто не ми трябва. Същото, впрочем, важи и за децата на български родители родени в чужбина – процедурата е сравнително лесна, но трябва да се върнеш в България. Има разписан в закона вариант български акт за раждане да се вади и през консулствата. Според отговора, който получих от Външно, няма данни някой някога да го е правил. Консулите дори имат задължение да вадят служебно български акт за българчета, за които знаят, че са родени в региона им. Нямат обаче капацитета и също не се е случвало.

За нищо от това не виня хората работещи в консулството. Колкото и да ме изнерви отношението на служителката тогава, разбирам я напълно предвид наплива пред сградата и ѝ го казах. Истината е, че точно консулството във Франкфурт работи с 2-3-ма консулски служители. Още няколко помагат с възспирането на тълпата и организацията, макар да не им е това работата. Консулството отговаря вече за близо 120 хиляди българи в съседните провинции. Това е все едно град като Плевен или Стара Загора да бъде обслужван от кметството на малко родопско село.

За проблемите на консулствата ни и недостига на служители и материално осигуряване съм писал вече. Министерството на външните работи отказа да ми предостави данните за финансовите отчети на всяко от тях. Съдих ги, спечелих на първа инстанция, но те обжалваха пред ВАС. Делото е насрочено за средата на февруари. Опърничавостта им ме кара да мисля, че явно има резон в неофициалната информация, която имам от познати във Външно, че от такси и услуги министерството излиза на печалба, а не се инвестира почти нищо. Само данните ще покажат дали емиграцията ни не издържа дипломацията ни.

Целият процес е изнервящ за всички участници. Нищо ново за бюрокрацията ни, ще кажете. Интернет платформите, електронната идентичност, електронните услуги и гласуване ще олекотят много нещата, но няма да изместят нуждата от адекватни консулства. Дори да не подаваме ухо на фалшивите бомбастични твърдения за броя на българите в чужбина, емиграцията ни е доста голяма. Всички говорят как ще бъдат върнати с една или друга мярка, но никой не се сеща, че често допирът до държавата България са именно тези консулства. През тях всички виждат, че малко от причините да напуснат да се подобрили – бюрокрация, неясни изисквания, липса на обучен персонал, изнервени служители и опашки. Ако искаме да променим нещо, това е добро място да започнем.

А иначе, аз паспорт ще си изкарам. Ще ми излезе по-евтино и по-бързо да се вдигна на самолета и да изкарам по бързата процедура в Пловдив. Ще загубя ден-два отпуска, но не ми е проблем. За доста обаче това не е вариант. Особено, когато са с дете.

New Information in the AWS IAM Console Helps You Follow IAM Best Practices

Post Syndicated from Rob Moncur original https://aws.amazon.com/blogs/security/newly-updated-features-in-the-aws-iam-console-help-you-adhere-to-iam-best-practices/

Today, we added new information to the Users section of the AWS Identity and Access Management (IAM) console to make it easier for you to follow IAM best practices. With this new information, you can more easily monitor users’ activity in your AWS account and identify access keys and passwords that you should rotate regularly. You can also better audit users’ MFA device usage and keep track of their group memberships. In this post, I show how you can use this new information to help you follow IAM best practices.

Monitor activity in your AWS account

The IAM best practice, monitor activity in your AWS account, encourages you to monitor user activity in your AWS account by using services such as AWS CloudTrail and AWS Config. In addition to monitoring usage in your AWS account, you should be aware of inactive users so that you can remove them from your account. By only retaining necessary users, you can help maintain the security of your AWS account.

To help you find users that are inactive, we added three new columns to the IAM user table: Last activity, Console last sign-in, and Access key last used.
Screenshot showing three new columns in the IAM user table

  1. Last activity – This column tells you how long it has been since the user has either signed in to the AWS Management Console or accessed AWS programmatically with their access keys. Use this column to find users who might be inactive, and consider removing them from your AWS account.
  2. Console last sign-in – This column displays the time since the user’s most recent console sign-in. Consider removing passwords from users who are not signing in to the console.
  3. Access key last used – This column displays the time since a user last used access keys. Use this column to find any access keys that are not being used, and deactivate or remove them.

Rotate credentials regularly

The IAM best practice, rotate credentials regularly, recommends that all users in your AWS account change passwords and access keys regularly. With this practice, if a password or access key is compromised without your knowledge, you can limit how long the credentials can be used to access your resources. To help your management efforts, we added three new columns to the IAM user table: Access key age, Password age, and Access key ID.

Screenshot showing three new columns in the IAM user table

  1. Access key age – This column shows how many days it has been since the oldest active access key was created for a user. With this information, you can audit access keys easily across all your users and identify the access keys that may need to be rotated.

Based on the number of days since the access key has been rotated, a green, yellow, or red icon is displayed. To see the corresponding time frame for each icon, pause your mouse pointer on the Access key age column heading to see the tooltip, as shown in the following screenshot.

Icons showing days since the oldest active access key was created

  1. Password age – This column shows the number of days since a user last changed their password. With this information, you can audit password rotation and identify users who have not changed their password recently. The easiest way to make sure that your users are rotating their password often is to establish an account password policy that requires users to change their password after a specified time period.
  2. Access key ID – This column displays the access key IDs for users and the current status (Active/Inactive) of those access key IDs. This column makes it easier for you to locate and see the state of access keys for each user, which is useful for auditing. To find a specific access key ID, use the search box above the table.

Enable MFA for privileged users

Another IAM best practice is to enable multi-factor authentication (MFA) for privileged IAM users. With MFA, users have a device that generates a unique authentication code (a one-time password [OTP]). Users must provide both their normal credentials (such as their user name and password) and the OTP when signing in.

To help you see if MFA has been enabled for your users, we’ve improved the MFA column to show you if MFA is enabled and which type of MFA (hardware, virtual, or SMS) is enabled for each user, where applicable.

Screenshot showing the improved "MFA" column

Use groups to assign permissions to IAM users

Instead of defining permissions for individual IAM users, it’s usually more convenient to create groups that relate to job functions (such as administrators, developers, and accountants), define the relevant permissions for each group, and then assign IAM users to those groups. All the users in an IAM group inherit the permissions assigned to the group. This way, if you need to modify permissions, you can make the change once for everyone in a group instead of making the change one time for each user. As people move around in your company, you can change the group membership of the IAM user.

To better understand which groups your users belong to, we’ve made updates:

  1. Groups – This column now lists the groups of which a user is a member. This information makes it easier to understand and compare multiple users’ permissions at once.
  2. Group count – This column shows the number of groups to which each user belongs.Screenshot showing the updated "Groups" and "Group count" columns

Customize your view

Choosing which columns you see in the User table is easy to do. When you click the button with the gear icon in the upper right corner of the table, you can choose the columns you want to see, as shown in the following screenshots.

Screenshot showing gear icon  Screenshot of "Manage columns" dialog box

Conclusion

We made these improvements to the Users section of the IAM console to make it easier for you to follow IAM best practices in your AWS account. Following these best practices can help you improve the security of your AWS resources and make your account easier to manage.

If you have comments about this post, submit them in the “Comments” section below. If you have questions or suggestions, please start a new thread on the IAM forum.

– Rob

Announcing the Availability of Hardware Multi-Factor Authentication in the AWS GovCloud (US) Region

Post Syndicated from Craig Liebendorfer original https://aws.amazon.com/blogs/security/announcing-the-availability-of-hardware-multi-factor-authentication-in-the-aws-govcloud-us-region/

AWS GovCloud (US) Region image

Hardware multi-factor authentication (MFA) is now available in the AWS GovCloud (US) Region to help strengthen data security while giving you control over token keys that have access to your data. MFA is a best practice that adds an extra layer of protection on top of users’ user names and passwords.

These token keys that are specific to the AWS GovCloud (US) Region are distributed by SurePassID, a third-party digital security company, and implement the Initiative for Open Authentication Time-Based One-Time Password (OATH TOTP) standard. SurePassID tokens are available for purchase on Amazon.com.

For more information about hardware MFA in the AWS GovCloud (US) Region, see the AWS Public Sector Blog post.

– Craig