Whisper provides a simple way to share secret information with someone else, such as passwords, credentials, keys, or other sensitive data.
How it works:
A user has a secret to send to someone else. Instead of using insecure means such as email or instant messenger, they enter the secret text or file along with a password used to encrypt the secret. The secret can be text or a file and an expiration time is chosen for the secret such as one time, hour, day, or week. The user receives a link from the server which can be shared with the other person as well as the shared password used for retrieval. The password should be shared separately from the link, such as sending the link by email and telling them the password via txt message. The other person can retrieve the secret by browsing to the link and entering the shared password.
All AES encryption and decryption is handled on the client-side, so no data is transmitted in plaintext. The backend stores the encrypted data and salted password hash, but because the client creates a salted SHA512 hash from the password before sending it to the server, even if the server is compromised or the administrator is a malicious actor, they will be unable to decrypt the secret data.
To get up and running:
- Copy the default config file to config.yaml
- Set the secret_key
- Create a volume (optional, if persistent disk storage is needed)
- Set up cloud credentials (required only if a cloud storage backend is used)
- Run the container
Copy the default config file to a new config.yaml as a starting point.
Change the storage backend settings if needed, by default it will use local disk storage so you will need to mount a volume path when you run the container if you want secrets to persist.
At a minimum, set the secret_key to a random string. A simple way to generate a secret key is by running the following command:
head /dev/urandom | LC_ALL=C tr -dc 'A-Za-z0-9' | head -c 32 && echo
Save the output as the "secret_key" configuration parameter in the new config.yaml file.
If using memory, S3, or GCS, no storage volume is needed. If using local disk storage, then a volume will need to be created and mounted to persist data between application executions.
To create a docker volume:
docker volume create whisper-storage
If using S3 or GCS, credentials are needed in order to access the backend. Each of these providers has multiple ways of automatically providing credentials to the backend.
See the cloud provider specific documentation in the installation section below.
After the above steps, the container can be run:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
-v whisper-storage:/tmp/whisper \
viyh/whisper:0.1.0
Once it is running, you can use Whisper by browsing to: http://localhost:8000
Whisper is meant to be run as a Docker container so this documentation assumes that. It can certainly be run outside of Docker, however that is left up as an exercise to the reader because there are many advantages to running as a simple container.
The installation process depends upon a few things:
- configuration file
- storage backend
- credentials for access to the storage backend (if necessary)
- env vars
The configuration file allows the customization of many runtime parameters, including most importantly the server secret key, and the storage backend.
The code repository contains a config.default.yaml that can be copied and used as a starting point. Your configuration file will need to be mounted into the container to /usr/src/app/config.yaml. All examples of running Whisper below include this.
The server secret key is used for encrypting the secret password as an extra layer of protection. If the storage backend is compromised and the stored secrets are stolen, the password hashes cannot be decrypted without the server secret key. This also means that if a secret is created and then the server secret key is changed, the secret cannot be decrypted.
The other important part of the configuration is selecting a storage backend. There are four options provided: local disk, in-memory, AWS S3, and GCP Cloud Storage (GCS). A custom storage backend can also be written and used. Each store has a different set of configuration options which are outlined in detail within their section of the documentation below.
The configuration file location can be overridden by setting the CONFIG_FILE env var which must contain the path of the configuration file inside the container.
A storage backend is used to store the secrets.
The default storage backend is local disk. Whisper will store secrets within the container in the /tmp/whisper path, so any volume mounted at that location will persist. If no volume is mounted, the secrets will not perist between application runs. Other than a volume mount, no other external dependencies are required, so this is a great way to get started if you want persistent data.
An example command to get started assuming that you have a storage directory of /home/whisper on your host machine would be:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
-v /home/whisper/data:/tmp/whisper \
viyh/whisper:0.1.0
In-memory storage is the simplest storage method and most secure, however it will not persist any data between application runs, so all secrets will be lost once the application stops. Since the typical usage of Whisper is ephemeral secrets being sent quickly between collegues, this may be sufficient and a tolerable loss with the added benefit of simplicity of setup.
Within the configuration file, make sure any other storage backends are commented out, and then make sure to uncomment the section for the in-memory store backend. An example command to run Whisper would look something like this, assuming that the configuration file is stored at /home/whisper/config.yaml on the local host:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
viyh/whisper:0.1.0
Cloud storage such as S3 is a fairly straigh-forward switch to make for any
application that requires persistent storage and also wants to gain the ability
to become scalable. However, the one additional caveat to cloud storage is that
there may be an additional cost to both store the data (very minimal) and
retreive the data. Whisper has a storage cleaner which periodically checks for
expired secrets. To accomplish this with S3 without having to pull the entire
secret which could lead to high costs for retrieving the data if many and/or
large secrets are stored, S3 tags are used to tag each object stored with the
creation (tag: create_date
) and expiration dates (tag: expire_date
). This allows
the storage cleaner to pull only the tags for each object making it a simple,
small request. If the object is determined to be expired based on the values of
these tags, then the object is deleted.
Similar to S3 storage, GCS can be used to make the application more scalable by detaching the need for local storage but providing persistence and the ability for multiple instances of the application to access the stored secrets.
GCS allows metadata stored with each object (similar to S3 tags), so metadata
keys for expire_date
and create_date
are added so that the entire object
does not need to be pulled in order to expire secrets by the store cleaner.
With any of the following three methods to provide credentials to the application, a minimum set of IAM permissions will need to be granted to that user/role.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:ListBucket",
"s3:GetBucketLocation",
"s3:GetObject",
"s3:PutObject",
"s3:DeleteObject",
"s3:GetObjectTagging",
"s3:PutObjectTagging",
"s3:DeleteObjectTagging",
],
"Resource": [
"arn:aws:s3:::my-whisper-bucket",
"arn:aws:s3:::my-whisper-bucket/*"
]
}
]
}
The simplest way is to use the built-in IAM roles to provide access. The code will automatically use the IAM role to access the backend, so no additional configuration is needed with this method.
A second method is to mount a ".aws/" directory containing the config and/or credentials file into the container. If using a specific profile, the env var AWS_PROFILE can be set to specify which profile should be used.
These can be specified in the Docker run command, such as:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
-v ~/.aws:/.aws:ro \
-e AWS_PROFILE=default \
viyh/whisper:0.1.0
More info can be found here.
The final method that can be used is setting the environment variables for the AWS access key ID and secret access key. The env vars are:
AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
AWS_DEFAULT_REGION
These can be specified in the Docker run command, such as:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
-e AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE \
-e AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY \
-e AWS_DEFAULT_REGION=us-east-1 \
viyh/whisper:0.1.0
See also the AWS documentation for environment variables.
When using Google Cloud Storage as the backend, the following permissions are required:
storage.objects.get
storage.objects.update
storage.objects.list
storage.objects.create
storage.objects.delete
storage.multipartUploads.create
storage.multipartUploads.abort
storage.multipartUploads.listParts
storage.multipartUploads.list
storage.buckets.get
Unfortunately, there is no built-in IAM role that provides the necessary access without providing additional unnecessary permissions to the user such as the ability to edit the IAM policy for an object or bucket. The above permissions can be used to create a custom role and apply it to the user/service account that Whisper is using. If you want a simpler configuration that also provides a few of those unnecessary permissions but allows you to use built-in roles, the following two roles will be sufficient:
roles/storage.legacyObjectOwner
roles/storage.legacyBucketWriter
This is the best method for authenticating against Google. If the application default credentials are set up for the environment that Whisper is running in, these will be automatically used and no additional configuration is required.
A second method is to mount a ".config/gcloud" directory containing the credentials directory into the container. This assumes you already installed the Google Cloud SDK and configured the application default credentials for your local user outside of the container.
These can be specified in the Docker run command, such as:
docker run -it --rm --name whisper -p 8000:8000 \
-v /home/whisper/config.yaml:/usr/src/app/config.yaml \
-v ~/.config/gcloud:/.config/gcloud:ro \
viyh/whisper:0.1.0
Any of these defaults can be overridden when running the Docker container.
WEB_PORT
- Default: 8000 - The port for Whisper to listen on.LOG_LEVEL
- Default: INFO - Debugging can be turned on by setting this to "DEBUG".CONFIG_FILE
- Default: config.yaml - This can override the configuration file path within the container.
Secrets are at the heart of whisper. These are the pieces of information that the user is storing, along with some additional metadata about that data.
The structure of a secret in storage depends on the implementation of the specific backend that is being used, but here is what an example secret looks like represented as a JSON object:
{
"id": "8d692508856cabba82d73e15ef6f0364de70546c",
"create_date": 1657421435,
"expire_date": -1,
"data": "U2FsdGVkX1/qMytBOYisCGZ3KjpkowinHQhu12lGY8E=",
"hash": "$2b$12$ku/b46sSaK45f9jV.t8/2OfZoiCtjk8kzC5QBjQsieFai/HLCaYMy"
}
The attributes are as follows:
id
: a unique secret identifier. This ID is used in the URL to retrieve the secret.create_date
: UNIX epoch timestamp of when the secret was created.expire_date
: UNIX epoch timestamp of when the secret expires. If this is -1, then the secret is for one-time retrieval then will be deleted immediately.data
: The AES encrypted text or file.hash
: The password hash that is used to retrieve the secret.
Secrets are saved and retrieved from the secret Store. The store deals with getting and setting secrets in the storage backend and running the storage cleaner loop to delete expired secrets. When Whisper starts, the class set in the configuration file for the storage backend is loaded and initialized.
The storage backend is the specific store configured by the user. Each storage backend has code that deals with implementation specifics around retrieving, saving, and deleting secrets. Additional custom storage backends can be written and added as needed.
Storage backends must at a minimum implement the following design features:
- Subclass of the
store
class - Define an init function with a
name
andparent
keyword argument. Thename
keyword argument should be a descriptive name for the backend, and theparent
keyword should default toNone
since it will be set by the main app that instantiates the storage backend and set to itself at that time. - Define an attribute named
default_configuration
which is a dict containing key/value pairs of the defaultstorage_config
values for that particular backend. A default value ofNone
for a given config key means that the configuration parameter must be set by the user in order for the backend to be used. - Define a
start
function that initializes the backend for use. - Define a
get_secret
function that takes a secret ID argument and returns the secret object from the backend if it exists orFalse
. - Define a
set_secret
function that takes a secret object argument and saves the object in the backend in whatever way that is necessary for the backend implementation. - Define a
delete_secret
function that takes a secret ID arguemnt and deletes the secret from the backend if it exists. - Define a
delete_expired
function that iterates through all stored secrets and checks each secret to see if it is expired and deletes any that are expired.
Example skeleton class:
import logging
from whisper.storage import store
logger = logging.getLogger(__name__)
class dummy(store):
def __init__(self, name="dummy", parent=None):
self.default_config = {}
super().__init__(name, parent)
def start(self):
pass
def get_secret(self, secret_id):
# get and return secret here
pass
def set_secret(self, s):
# save the secret here
pass
def delete_secret(self, secret_id):
# delete the secret here
pass
def delete_expired(self):
# loop through secrets and check secret.is_expired(), then delete any
# that have expired.
pass
Whisper has a storage cleaner which will delete secrets which have expired. The storage cleaner runs at intervals of your choosing for the granularity of secrecy you require.
For instance, if a secret is created with an expiration period of "1 day", the expiratiion date is timestamped down to the second. If the storage cleaner period is set to "900" seconds (the default) in the configuration file, then that secret may exist for up to 14 minutes and 59 seconds after it truly expired, and then the storage cleaner will actually remove it from the storage backend. This can be tuned to a lower setting if needed, but keep in mind that the more frequently that the cleaner runs, the more resources such as disk IO, network bandwidth, etc. it will use depending upon the specifics of the storage backend. For these reasons, it's usually sufficient to keep the cleaner run interval set to the default of 900 seconds (15 minutes) since this consumes minimal resources and is typically an acceptible additional potential wait period before deletion.
The secret text/file is encrypted using AES on the client-side and a user-supplied password. The data is only transmitted after encryption to the server for storage. The secret password is also hashed (salted SHA512 with 10000 rounds) before being sent, in order to protect against eavesdropping, server compromise, or malicious server administrators. The data is stored in the server storage backend and the password is re-hashed along with a server-specific key using bcrypt before also being stored in the backend. This protects the key further from being cracked or stolen and resent to retrieve the encrypted secret.
To retrieve a secret, the client-hashed password is sent to the server where it is hashed using the server-key and compared against the stored hash. If they match, the server sends the encrypted secret data back to the client. The client then decrypts the data using the password.
Nginx is used as the front end webserver. The configuration is stored within the container at /tmp/nginx.template.conf and envsubst is used at runtime to replace the WEB_PORT environment variable.
The Flask app is contained withint the app.py file. This deals with firing up the Flask application, parsing the config file, the endpoint code, and initializing the storage backend.
See src/whisper/storage/init.py for code and class implementation. The memory.py storage backend can be used as a simple backend implementation example.
If implementing a custom storage backend, the cleaner thread calls a store class's "delete_expired()" method. A store class should override this method and provide any functionality necessary to delete any secrets that return True with the "secret.check_id()" and return True from the "secret.is_expired()" secret class methods. All other objects should remain untouched. "Is it really a secret and is it expired?"
See the Storage Backend section in the Architecture Details for more info.
When writing code, it's helpful to run a container that can be used to start/stop the application manually instead of having to rebuild the container with each change.
The following command will run a development container with the live code repo mounted in place so that you can live edit.
docker run -it --rm --name whisper -p 8000:8000 \
-e LOG_LEVEL=DEBUG \
-v whisper-storage:/tmp/whisper \
-v /full/path/to/your/whisper/src:/usr/src/app:ro \
viyh/whisper:0.1.0
The /src
dir in the repo should be mounted to /usr/src/app within the
container. Simply ^C to end the process and rerun the command to start again
when changes are made.
The repo contains a Dockerfile that can be built using the same process as as any standard Docker image.
For cross-platform builds, that can be performed with something such as the following:
docker buildx build --platform=linux/amd64,linux/arm64 \
-t whisper:0.1.0-alpha.$(date +%s) \
-t whisper:0.1.0-alpha .
Please submit pull requests on Github, contributions are encouraged and welcome!
Joe Richards (GitHub: @viyh)