credopy 1.0.8

A Python 3 tool to fetch secure strings from aws parameter store and injecting those into environment variables.

CredoPy aka pydo!

No passwords in code!

Make your company more secure using the "troy password credo"!

Easier said than done working with credentials can get very messy and leed to huge security and data protection problems. So while working at troy gmbh it became clear that we had do define some fundamental rules to maintain a high level of security while fast growth phases. This brought up the "troy password credo".

troy password credo:

You may ask what "What is the famous troy password credo?" It's very simple: Never store credentials unencrypted!

Let's get started

Working with Credentials can be fun, but from a security perspective, most of the time it isn't! Especially if you have multiple systems and different environments.

If you're using the AWS cloud you found the right repository!

Pydo is a tool that injects aws parameter store strings and secure strings into your memory as an environment variable. With this, your important credentials/security keys/... never have to touch your disk again.

And because the parameter store supports paths you can define different services with different environments.

For example:

/<Environment>/<KotlinApp1>/

#which could look like:
/Prod/CustomerManagement/DB/USER

#or
/Prod/CustomerManagement/DB/PASSWORD

Output these example data (The database password for CustomerManagement in production ):

pydo -e Prod -s CustomerManagement echo '$SECRET_CUSTOMERMANAGEMENT_DB_PASSWORD'

With both parameters, your "CustomerManagement" application/service (launched with pydo) could now access the database with the provided username and password.

Details at: How to access the environment variables

Usage

pydo [-s <service/application>] [-i] [-n] [-e <env>] [-t <2fa key>] [-T] [-Y] [-u <aws username>] [-a <account number>] [-p <aws profile>] [-r <region>] <command>

Options:

Option	explination	sample	comment
-h	Shows help	pydo -h
-i	Starts pydo in interactive mode	pydo -i	Gives you a command line that you can interact with
-s <service/application>	For which service should the environment variables be loaded?	pydo -s CustomerService
-S	Sets a default service for pydo and writes it to a config file	pydo -S CustomerService	from now on "CustomerService" is the default service which means "-s CustomerService" is redundant
-n	do not query credentials at all	pydo -n
-e <env>	For which environment should the environment variables be loaded? For example Dev, Test or Prod (permission required)	pydo -e Prod
-t <2fa key>	Takes the 2FA key from your aws account	pydo -t 987123
-T	Lets you type in the 2FA key from your aws account during runtime	pydo -T	When you run your command pydo will ask for the token
-Y	Uses Yubikey for MFA auth	pydo -Y	During runtime pydo will use ykman to fetch the MFA-Key from your yubikey
-r <region>	Overwrites temporary the awscli default region	pydo -r eu-central-1	Pydo will use the given region for example Frankfurt
-q	Quiet mode (less output)	pydo -q
-u <aws username>	Sets a specific username combined with -a gives you a faster runtime (otherwise this data needs to be retrieved via aws)	pydo -u [e-mail]
-a <account number>	Sets a specific account number combined with -u gives you a faster runtime (otherwise this data needs to be retrieved via aws)	pydo -a 999999999999
-p <aws profile>	If multiple aws profiles are available you can choose the profile otherwise pydo will use the default profile	pydo -p testUser1
<command>	Is the command to execute with environment variables injected.	pydo code	Will run VS Code with access to given environment variables

Note: It may be required to double escaping.

Examples:

Linux:

pydo echo '$SECRET_CUSTOMERSERVICE_UI_URL'

or

Windows:

pydo echo %SECRET_CUSTOMERSERVICE_UI_URL%

Mac:

pydo "/Applications/IntelliJ\ IDEA\ CE.app/Contents/MacOS/idea"

Note the quoting of the variable.

Format for these environment variables:

Every environment variable that is loaded with pydo starts with "SECRET_".

Then the service-name and path, separated by underliners.

(of course in upper case)

For example:

SECRET_CUSTOMERMANAGEMENT_DB_USER

More about environment variables: Guide to Unix/Environment Variables

This is maybe made more clear by the following example:

/Prod/CustomerManagement/DB/USER

would be accessible with:

SECRET_CUSTOMERMANAGEMENT_DB_USER

or

/Prod/CustomerManagement/DB/PASSWORD

would be accessible with:

SECRET_CUSTOMERMANAGEMENT_DB_PASSWORD

Environments

We now talked a lot about environments, but how can pydo differ between different environments like dev, test, or prod?

Quite simply, you tell it!

Parameterstore:

As already mentioned you Define the environment as the first section.

Let's take the previous example:

/Prod/CustomerManagement/DB/PASSWORD

here "Prod" is our environment for the database(DB) password (PASSWORD) of our CustomerManagement service/application, but we could easily also set this for our test environment like this:

/Test/CustomerManagement/DB/PASSWORD

(When creating new parameters don't forget to create them as "SecureString's" ;) )

Bonus content:

Converting parameter store strings to secure strings Found this in my old files, before using this test and make sure it really works but with this snippet, you should be able to convert every normal parameter store string to a secure string.

No guarantee for functionality, make sure you have a backup of the parameter store variables

import boto3
client = boto3.client('ssm')
response = client.describe_parameters()
nameList = []
dic = {}
dic_descr = {}

for p in response['Parameters']:
    nameList.append(p['Name'])
    dic_descr[p['Name']] = p.get('Description')

nextToken_Str = response['NextToken']

while nextToken_Str:
    response = client.describe_parameters(NextToken=nextToken_Str)
    
    for p in response['Parameters']:
        nameList.append(p['Name'])
        dic_descr[p['Name']] = p.get('Description')
    
    nextToken_Str = response.get('NextToken', None)
        
for name in nameList:
    response = client.get_parameter(Name=name, WithDecryption=True)
    dic[name] = response.get('Parameter').get('Value')


for name in dic:
    if dic_descr[name] is not None:
        print(client.put_parameter(
            Name=name,
            Description=dic_descr[name],
            Value=dic[name],
            Type='SecureString',
            Overwrite=True
        ))
    else:
        print(client.put_parameter(
            Name=name,
            Value=dic[name],
            Type='SecureString',
            Overwrite=True
        ))

Client/You

With

pydo -e <env>

you can launch pydo for every in the parameterstore defined environment.

If you don't set any pydo swtiches to "Dev"

AWS Server

when pydo runs on an aws machine you could run it with "-e <env>" but this is rather inconvenient. So pydo queries the instance tags and searches for the key "environment" and uses its value as the current environment. If the environment tag is not set and you did not provide an environment with "-e" pydo automatically defaults to "Dev"

How to access the environment variables

To access those environment variables you have to run your application/service with pydo.

pydo java -jar service.jar
//or
pydo python service2.py

Now these two services have all environment variables for their service and environment available and can work with them here are two easy examples:

Python:

import os
os.getenv('SECRET_CUSTOMERMANAGEMENT_DB_PASSWORD')

#or let's say you want to fetch an API, but need an API token in a header request:
....

header = { 'Api-Key' : os.getenv('SECRET_CUSTOMERMANAGEMENT_API_KEY') }
....

Kotlin:

val envVar : String? = System.getenv("varname")
//there are some other examples feel free to look into https://stackoverflow.com/ but I like this approach because environment variables can be null, bus null handling probably comes down to your use-case/coding style.

Authentication

AWS Server:

Easy! Done by boto3 automatically uses in instance role defined permissions.

(Details "Permissions" section)

Developer:

boto3 uses the aws CLI's authentication so make sure you set this up before ;)

AWS CLI

By default, pydo uses the aws CLI default profile, but of course, you can choose the profile, that you want to use, simply do:

pydo -p <awscli profile name>
#or 
pydo -h 
#to see more configuration options

(More details in the "Usage" section)

MFA

First of all multi-factor authentication is highly suggested!

https://lmgtfy.com/?q=why+mfa+is+important

Ok, all jokes aside especially for production parameters your IAM users should require MFA authentication at least for production parameters.

So even when a password/account from one of your users gets compromised and let's be realistic here, this will definitely happen to your company/project so better prepare for that event!

"How can we mitigate the damage"

At least in my humble opinion, this should be a "better be safe than sorry" point.

Especially for your production systems!

Pydo supports multiple MFA options, details in the "Usage" section, here the short overview:

# normal virtual mfa token:
pydo -t <TOKEN>

#askt for the token during runtime:
pydo -T

# leads to:
$ pydo -T
$ Please enter token: 

#Yubikey Authenticator:
pydo -Y

At the moment aws-CLI only supports virtual MFA devices(so the -Y option uses the virtual MFA function of your yubikey (ykman) as a workaround until awscli supports hardware tokens ), but feel free to drop a comment or investigate here:

https://github.com/aws/aws-cli/issues/3607

Permissions: IAM policies / Instance roles

Permission	Used in the code	Documentation	Comment
"ec2:DescribeTags"	clientEC2.describe_tags()	https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_DescribeTags.html
"sts:GetCallerIdentity"	clientSTS.get_caller_identity()	https://docs.aws.amazon.com/STS/latest/APIReference/API_GetCallerIdentity.html	Optional(No permissions are required to perform this operation.)
"sts:GetSessionToken"	clientSTS.get_session_token()	https://docs.aws.amazon.com/STS/latest/APIReference/API_GetSessionToken.html
"ssm:GetParametersByPath"	clientSSMMFA.get_parameters_by_path()	https://docs.aws.amazon.com/systems-manager/latest/userguide/sysman-paramstore-access.html
"iam:ListMFADevices"	boto3.client('iam').list_mfa_devices()	https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_examples_iam_mfa-selfmanage.html	Optional! (At the moment not in use but as soon aws API supports hardware tokens this can be enabled to let pydo support hardware MFA's)

tldr Minimal permissions:

“ec2:DescribeTags”

“sts:GetSessionToken”

“ssm:GetParametersByPath”

Setup

1. Define environment variables as described in Format for these environment variables
2. Set environment tag's for your instances as described in AWS Server
3. Create/adjust your instance roles/IAM roles with proper permissions as described in

Permissions

Installation

• Install python3 and pip
• install and setup boto3:

pip install awscli --user

• Install pydo:

pip install credopy

Todo

• Load service name also from aws tags
• Enhance local profile/config setup/usage
• Describe how to make prod parameters only accessible with MFS auth and the rest without
• Load multiple services at once instead of concatenating multiple pydo calls ( "pydo -s Service1 pydo -s Service2 ")
• Load environment tags for ECS container
• Describe the "troy credential credo"

Acknowledgments

Inspired by:

• Gunnar Zarncke - LinkedIn and his/troy gmbh's opensource credo projekt - Git Credo

Bug reports:

• Arif PEHLİVAN

• Carlos Freund

Donations

If you want to tip me or simply want to say thanks:

Paypal

License

MIT Link