Best To Know The Correct Method To Oversee Mysteries With AWS

The way companies manage the secrets of applications is essential. Even today, mismanagement of secrets has led to a staggering number of high profile offenses. Having credentials of internet access is like leaving your key home under a rug that millions of people visit daily.

Even though the secrets are hard to find, it's a shell game that you'll eventually lose. En Segment, centrally manage and protect our secrets with AWS parameter store, many Terraform configurations and camera. While tools like Vault, Credstash and Confident there have been many rumors recently store parameter constantly neglected when it comes to the administration of secrets. Having then used the store parameter for several months has come to a different conclusion: if you are running your entire infrastructure in AWS and you are not using Store Parameter to manage your secrets , then you're crazy! This publication has all the information you need to run with the Parameter Store in production.Identidad de servicioAntes Dive Shop Parameter, it pays to briefly discuss how the service identity works within an AWS.

En account thread, we run hundreds of services They communicate with each other, AWS APIs, and third-party APIs. The services we carry out have different needs and should only have access to the strictly necessary systems. This is called the "minimum privilege principle." As an example, our primary Web server should never have access to reading security audit logs. Without giving the containers and identity services it is not possible to protect and restrict access to services of secret access control policies. Our identities are identified using IAM papers.

AWS documents: An IAM role ... is an AWS identity with license policies that determine what identity can and can not do on AWS roles. The IAM can be assumed by almost anything: AWS users, running programs, lambdas, or instances of ec2. All of them describe what the user or service can or can not do. For example, our IAM functions for instances have write-only access to a group of s3 to add audit records but prevent the deletion and reading of those records.

How did they manage to bring their paper containers safely? The requirement to use ECS is that all containers must run the EC2 service container agent (DFT-agent). The agent runs as a container that organizes and provides an API with which the containers can communicate.

The agent is the central nervous system, which are programmed containers in which the instances and IAM role credentials to be supplied to a given function. To properly container, the ECS-agent performs an HTTP API which must be accessible to the other containers running in the agglomerated. The API itself is used for health exams and to insert credentials into each container.

So that this API is available in a host container in an iptables rule established in the host request. This iptables rule forwards traffic destined for a magical IP address agent.

iptables ecs-t container nat \ -A OUT \ -d 169.254.170.2 \ -p tcp \ -m tcp \ - dport 80 \ -J REDIRECT \ - ports 51679By that ECS starting a container-agent first obtains the credentials for the task container paper service from AWS credentials. The ecs-agent then sets the ID key credentials, a UUID, as the AWS_CONTAINER_CREDENTIALS_RELATIVE_URI environment variable inside the container when the inside of the container is started. Since, this variable looks like: $ env ...

AWS_CONTAINER_CREDENTIALS_RELATIVE_URI = / v2 / credentials / 53875b56-621a-4b07-8ab6-02ea315b5693 ... using the UUID URI and relative containers obtained AWS credentials from DFT-agent via HTTP $ 169.254.170.2 $ AWS_CONTAINER_CREDENTIALS_RELATIVE_URI curl. | jq

{

"RoleArn". "ARA: AWS: iam :: 111111111111: paper / test-service", "AccessKeyId" "ASIAIYLSOW5USUQCZAAQ" "SecretAccessKey" "REDACTRED", "token", "Done", "Expiry": "2017-08-10T02: 01 : 43Z "

}

A container can not access the authentication credentials to represent another container because the UUID is difficult enough to guess security. Additional ECS tabs As heavy users find security functions weapons associated with the ECS task.

First, it is very important realize that any container that can access the EC2 service metadata can turn into any other task role in the system. If you do not take care, it is easy to forget that a given container can circumvent the access control policies and authorized access systems there are two ways in which a container can access the service metadata are a) using b host networks) through container docker. When bridge runs with --network = host, they can connect to network EC2 service metadata using their host. ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST configuration variable in the fake ecs.config prevents containers running under this privilege.

In addition, it is important to block access to the IP address of the metadata service through the bridge of the docking window via iptables. Function documentation Task IAM recommends avoiding access to service metadata with this specific EC2 $ iptables rule. Insert FRONT 1 - in the dockable interface window + --destination 169.254.169.254/32 --jump DROPE The principle of minimum privilege is always important to consider when creating a security system. ECS_DISABLE_PRIVILEGED set the truth in ecs.config the host can prevent privileged Docker containers to run and cause other problems throughout complexes.Now security have established as recipients to establish identity and exchange secret keys, which leads us to the second part of the equation: Parameter Store The AWSParameter Store parameter store is an AWS service that stores strings. It can store secret data and non-secret data alike. The secrets stored in the store parameters are "secure channels" and encrypted with a KMS-specific client key. Under the hood, a service requesting secure parameter store AWS chains has many things going on behind the scenes.ecs- agent requesting temporary host credentials. example ecs continuously generates temporary credentials for each and every ecs function running on ECS by using a service called undocumented agent ECS ECS ACS.

When it starts each task, it establishes a secret UUID in the container environs. When the task requires role credentials, the API requests and authenticates with the UUID secret task. The ecs requests store parameters by using the credentials of the task function. The parameter repository transparently decrypts these strings before returning them to the task.

 The use of functions with The Paramete The Store is especially good because it does not require maintenance of aute tokens additional information. This would create additional headache and additional secrets to handle policy parameters.

IAM paper store Each accessing the store parameters requires SSM permission: getParameters. "SSM" stands for "simple system administrator" and is denoted AWS operations and store parameters. The ssm: getParameters permission is the policy used to enforce access control and protect the secrets of one service from another. Segment provides all services of an IAM role that gives access to the secrets that correspond to the

{{service_name}} / * {"Sid" format. "", "Effect", "Allow", "Action", "SSM: getParameters" "resource": ["ARN: AWS: SSM: *: *: parameter / {{service_name}} / Access control policy, Segment uses an AWS KMS key Dedicated to encrypting secure strings within the parameter repository. Each IAM function it is given a small set of KMS permissions to uncover the secrets stored in the store parameter {"Sid" "," Effect "," Allow "," Action ": [" Kms: ListKeys "" kms: ListAliases "," kms: * Describe "," kms: Deciphering "]" resource ":" parameters_store_key "}

Of course, creating all these boiler parts by hand quickly becomes tedious. Instead, automate the creation and configuration of these roles through Terraform.Automatization modules and identity service policy. Segment has a small Terraform module abstracting the creation of a single IAM function, load balancers, DNS records, automatic escalation and CloudWatch alarms . Here we show how our nginx load balancer is defined using our service module.

Module "nginx"

{

source = "../modules/service"name =" nginx "image =" thread / nginx "product_area =" foudation- security "health_check_path = "/ healthcheck" environment = "$ {var.environment}"

}

Under the hood, the role of the task assigned to each service has all the IAM policies listed previously, restricting access to store parameters for value in the name field. It does not require any configuration # Create our rolearea "aws_iam_role" "task_role"

{

name = "$ {var.cluster} - $ {var.name}" assumption_role_policy = "$ {data.aws_iam_policy_document.ecs_assume_role_policy.json}"}. # let our task take on the role of ecs.datos "aws_iam_policy_document" "ecs_assume_role_policy" {{Action statement = ["STS: AssumeRole"] directors {type = "Service" identifier = ["ecs-tasks.amazonaws. com "]}}} # Allow this access paper to store parameters" aws_iam_role_policy_attachment "" parameters_store "{role =" $ {aws_iam_role.task_role.name} "policy_arn =" $ {aws_iam_policy.parameter_store_policy.arn} "} In addition, developers are opting to cancel the secrets that have access to their service by providing a "consumer secret." This secret tag will replace your service name in your IAM policy. If you need the same nginx secrets as an HAProxy instance, the two services can share credentials using the same secret label.module "nginx" {source = "../modules/service"name =" nginx 'image =' thread / nginx "product_area = "foudation-security" health_check_path = "/ healthcheck" environment = "$ {var.environment}" # share secrets with loadbalancerssecret_label = "loadbalancers"} store parameters productionAll employees authenticate with AWS by aws-vault, which can store credentials in the AWS MacOS or encryption key for Linux users.

The thread file has multiple AWS accounts. Engineers can interact with each account using the AWS-vault command and run commands locally with AWS credentials in their environment exec $ AWS-vault development. AWS s3 s3 ls // bucket segment This is great for AWS APIs but AWS CLI leaves a lot to be desired when it comes to interacting with store parameters. To do this, we use the Camera with the StoreChamber Camera parameter. Using is a built-in CLI tool to allow developers and codes to communicate with store consistent parameter.

Thus allowing developers to use the same tools that are run in production, reduce the amount of differences between code running in development with the staging and camera production. It works immediately with the AWS-vault and has only a few key subcommands: exec - command after loading secrets in surroundings.history - changes a secret in store parameters.list - the names of all secrets in a secret namespace.escribir - a secret store parameters.

Chamber uses search engines and history built into the Parameter Store to implement the list and history subcommands. All strings stored in the Store parameter also with version automatically, so we have an integrated track subcommand. The audit used to get store secrets is exec parameters. When developers use the exec subcommand, use it with exec development AWS-vault $ AWS-vault -. LoadBalancers Camera exec - nginxIn the above command, the camera works credentials and permissions used in the Development Account and retrieves the secrets associated with the Parameter Store load balancers. After the camera completes the environment, it will run the nginx server.

Cameraman in production To fill in the secrets in production, the camera is packaged inside our docker containers as a binary and is established as the entry point of the container.

The camera will signal the program running the program to allow the drive gracefully.Here is a difference of what is needed for our webcam is list.- EntryPoint [["node", "server / boot.js"] EntryPoint + "camera", "exec", "app", "-", "node", "server / boot.js"] unused containers docking window can also use the camera to fill the environment before creating configuration files from of models, run daemons, etc. We simply need to wrap up your command with the executable camera, and we are ready for carreras.Revisión de cuentasAs last part of our security record, we want to ensure that every action we described previously recorded and audited.

Fortunately for us, all accesses to the AWS Parameter Store are recorded in CloudTrail, which makes a complete audit trail for all the parameters simple and economical. It also makes creating custom alerts and audit logging is simple .... "eventTime": "2017-08-02T18: 54: 06Z", "Eventsource": "ssm.amazonaws.com", "eventName" " getParameters "" awsRegion "" US-west-2 "," SourceIPAddress "" 127.0.0.1 "," userAgent "" aws-sdk-go / 1.8.1 (go1.8.3; linux; amd64) "" requestParameters ": { "withDecryption" true "names": ["test-service.secretname"]} "responseElements" null "requestID" "88888888-4444-4444-4444-121212121212", "EventId" "88888888-4444-4444-4444-121212121212 "readOnly": true, ... CloudTrail to determine exactly what secrets are used and can make uncover secrets of access unused or unauthorized possible secrets.

AWS log all access to the Parameter Store for free as a CloudTrail management event . Most security information and event management (SIEM) solutions can be configured to display and read S3 data. To takeAlthough using the Store and IAM parameter, we have built a small tool that gives us all the properties that were most important for us into a secret management system without the overhead of management. In particular, we provide: protects secrets from strong cryptographic control policies.Apply rest access fuertes.Create authentication audit logs and access history.Gran developer. The best experience of all is that these functions are possible with only a small configuration and without administration of services, the management of secrets is very difficult to be achieved. They have created many products to manage secrets, but none fits the use cases that need Segment better than Store Parameter.

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