The first game I ever wrote was named Pooh. It had nothing to do with the bear. In September 1982, I was four years old, and the ZX Spectrum home computer had just been released. It was incredible enough that the Spectrum let you play games on the TV, but like most home computers of the time, it also came with a built-in language called BASIC, and a manual which explained how to program it. In my first game, Pooh (the title was a misspelling), the player controlled a baby, represented by a pound sign, and had to guide it to a potty, represented by the letter O. There were no obstacles, no enemies, and if you tried to walk off the screen, the program would stop with an error message. I didn’t have any idea how to create a graphical game more complex than Pooh. I didn’t even know how to display a sprite on the screen.
The Hobbit, released in 1982, was widely praised for its intuitive parser.
Text adventures
Instead, I focused on writing text adventures, where the game describes scenes to the player (“You are in a comfortable, tunnel-like hall. You can see a door,” from 1982’s The Hobbit) and the player enters commands such as “Go through door” or “Kill goblin with sword.” Although this type of game is comparatively easy to write, I implemented it in the worst way possible. The code was essentially a huge list of IF statements. Each room had its own set of code, which would print out a description of the room and then check to see what the player typed. This ‘hard-coding’ led to the code being much longer than necessary, and more difficult to maintain.
The correct way would have been to separate my code and data. Each room would have had several pieces of data associated with it, such as an ID number, the description of the room (“You are in a small cave”), an array of objects which can be found in the room, and an array of room numbers indicating where the player should end up if they try to move in a particular direction – for example, the first number could indicate which room to go to if the player enters ‘NORTH’. You’d then have the main game code which keeps track of the room the player is currently in, and looks up the data for that room. With that data, it can then take the appropriate action based on the command the player typed.
Getting it right
The code below shows how to implement the beginnings of a text adventure game in Python. Instead of numeric IDs and arrays, the code uses string IDs and dictionary data structures, where each piece of data is associated with an ID or ‘key’. This is a more convenient option which wasn’t available in Spectrum BASIC. We first create a list of directions in which the player can potentially move. We then create the class Location which specifies each location’s properties. We store a name, a description, and a dictionary data structure which stores the other locations that the current location is linked to. For example, if you go north from the woods, you’ll reach the lake. The class includes a method named addLink, which adds entries to the linked locations dictionary after checking that the specified direction and destination exist.
Following the class definition, we then create a dictionary named locations. This has two entries, with the keys being woods and lake, and the values being instances of the Location class. Next, we call the addLink method on each of the locations we’ve just created, so that the player will be able to walk between them. The final step of the setup phase is to create the variable currentLocation, specifying where the player will start the game.
We then reach the main game loop, which will repeat indefinitely. We first display the description of the current location, along with the available directions in which the player can move. Then we wait for the player to input a command. In this version of the code, the only valid commands are directions: for example, type ‘north’ at the starting location to go to the lake. When a direction is entered, we check to make sure it’s a valid direction from the current location, then update currentLocation to the new location. When the main loop restarts, the description of the new location is displayed.
I moved on from the ZX Spectrum eight years after my dad first unpacked it. Despite the poor design of my code, I’d learned the essentials of programming. Ten years later, I was a game developer.
Further reading
If you’re keen to learn more about making a text adventure in Python, you could check out Phillip Johnson’s guide to the subject, Make Your Own Python Text Adventure. The author has also written a condensed version of the same guide.
You can discover more tutorials, alongside great reviews, articles and advice, in Wireframe issue 6, out now and available in Tesco, WHSmith, and all good independent UK newsagents.
Join us this month to learn about AWS services and solutions. New this month, we have a fireside chat with the GM of Amazon WorkSpaces and our 2nd episode of the “How to re:Invent” series. We’ll also cover best practices, deep dives, use cases and more! Join us and register today!
AWS re:Invent June 13, 2018 | 05:00 PM – 05:30 PM PT – Episode 2: AWS re:Invent Breakout Content Secret Sauce – Hear from one of our own AWS content experts as we dive deep into the re:Invent content strategy and how we maintain a high bar. Compute
Containers June 25, 2018 | 09:00 AM – 09:45 AM PT – Running Kubernetes on AWS – Learn about the basics of running Kubernetes on AWS including how setup masters, networking, security, and add auto-scaling to your cluster.
June 19, 2018 | 11:00 AM – 11:45 AM PT – Launch AWS Faster using Automated Landing Zones – Learn how the AWS Landing Zone can automate the set up of best practice baselines when setting up new
June 21, 2018 | 01:00 PM – 01:45 PM PT – Enabling New Retail Customer Experiences with Big Data – Learn how AWS can help retailers realize actual value from their big data and deliver on differentiated retail customer experiences.
June 28, 2018 | 01:00 PM – 01:45 PM PT – Fireside Chat: End User Collaboration on AWS – Learn how End User Compute services can help you deliver access to desktops and applications anywhere, anytime, using any device. IoT
June 27, 2018 | 11:00 AM – 11:45 AM PT – AWS IoT in the Connected Home – Learn how to use AWS IoT to build innovative Connected Home products.
Mobile June 25, 2018 | 11:00 AM – 11:45 AM PT – Drive User Engagement with Amazon Pinpoint – Learn how Amazon Pinpoint simplifies and streamlines effective user engagement.
June 26, 2018 | 11:00 AM – 11:45 AM PT – Deep Dive: Hybrid Cloud Storage with AWS Storage Gateway – Learn how you can reduce your on-premises infrastructure by using the AWS Storage Gateway to connecting your applications to the scalable and reliable AWS storage services. June 27, 2018 | 01:00 PM – 01:45 PM PT – Changing the Game: Extending Compute Capabilities to the Edge – Discover how to change the game for IIoT and edge analytics applications with AWS Snowball Edge plus enhanced Compute instances. June 28, 2018 | 11:00 AM – 11:45 AM PT – Big Data and Analytics Workloads on Amazon EFS – Get best practices and deployment advice for running big data and analytics workloads on Amazon EFS.
One of the most common enquiries I receive at Pi Towers is “How can I get my hands on a Raspberry Pi Oracle Weather Station?” Now the answer is: “Why not build your own version using our guide?”
Tadaaaa! The BYO weather station fully assembled.
Our Oracle Weather Station
In 2016 we sent out nearly 1000 Raspberry Pi Oracle Weather Station kits to schools from around the world who had applied to be part of our weather station programme. In the original kit was a special HAT that allows the Pi to collect weather data with a set of sensors.
The original Raspberry Pi Oracle Weather Station HAT
We designed the HAT to enable students to create their own weather stations and mount them at their schools. As part of the programme, we also provide an ever-growing range of supporting resources. We’ve seen Oracle Weather Stations in great locations with a huge differences in climate, and they’ve even recorded the effects of a solar eclipse.
Our new BYO weather station guide
We only had a single batch of HATs made, and unfortunately we’ve given nearly* all the Weather Station kits away. Not only are the kits really popular, we also receive lots of questions about how to add extra sensors or how to take more precise measurements of a particular weather phenomenon. So today, to satisfy your demand for a hackable weather station, we’re launching our Build your own weather station guide!
Fun with meteorological experiments!
Our guide suggests the use of many of the sensors from the Oracle Weather Station kit, so can build a station that’s as close as possible to the original. As you know, the Raspberry Pi is incredibly versatile, and we’ve made it easy to hack the design in case you want to use different sensors.
Many other tutorials for Pi-powered weather stations don’t explain how the various sensors work or how to store your data. Ours goes into more detail. It shows you how to put together a breadboard prototype, it describes how to write Python code to take readings in different ways, and it guides you through recording these readings in a database.
There’s also a section on how to make your station weatherproof. And in case you want to move past the breadboard stage, we also help you with that. The guide shows you how to solder together all the components, similar to the original Oracle Weather Station HAT.
Who should try this build
We think this is a great project to tackle at home, at a STEM club, Scout group, or CoderDojo, and we’re sure that many of you will be chomping at the bit to get started. Before you do, please note that we’ve designed the build to be as straight-forward as possible, but it’s still fairly advanced both in terms of electronics and programming. You should read through the whole guide before purchasing any components.
The sensors and components we’re suggesting balance cost, accuracy, and easy of use. Depending on what you want to use your station for, you may wish to use different components. Similarly, the final soldered design in the guide may not be the most elegant, but we think it is achievable for someone with modest soldering experience and basic equipment.
You can build a functioning weather station without soldering with our guide, but the build will be more durable if you do solder it. If you’ve never tried soldering before, that’s OK: we have a Getting started with soldering resource plus video tutorial that will walk you through how it works step by step.
For those of you who are more experienced makers, there are plenty of different ways to put the final build together. We always like to hear about alternative builds, so please post your designs in the Weather Station forum.
Our plans for the guide
Our next step is publishing supplementary guides for adding extra functionality to your weather station. We’d love to hear which enhancements you would most like to see! Our current ideas under development include adding a webcam, making a tweeting weather station, adding a light/UV meter, and incorporating a lightning sensor. Let us know which of these is your favourite, or suggest your own amazing ideas in the comments!
*We do have a very small number of kits reserved for interesting projects or locations: a particularly cool experiment, a novel idea for how the Oracle Weather Station could be used, or places with specific weather phenomena. If have such a project in mind, please send a brief outline to [email protected], and we’ll consider how we might be able to help you.
Previously, I showed you how to rotate Amazon RDS database credentials automatically with AWS Secrets Manager. In addition to database credentials, AWS Secrets Manager makes it easier to rotate, manage, and retrieve API keys, OAuth tokens, and other secrets throughout their lifecycle. You can configure Secrets Manager to rotate these secrets automatically, which can help you meet your compliance needs. You can also use Secrets Manager to rotate secrets on demand, which can help you respond quickly to security events. In this post, I show you how to store an API key in Secrets Manager and use a custom Lambda function to rotate the key automatically. I’ll use a Twitter API key and bearer token as an example; you can reference this example to rotate other types of API keys.
The instructions are divided into four main phases:
Store a Twitter API key and bearer token in Secrets Manager.
Create a custom Lambda function to rotate the bearer token.
Configure your application to retrieve the bearer token from Secrets Manager.
Configure Secrets Manager to use the custom Lambda function to rotate the bearer token automatically.
For the purpose of this post, I use the placeholder Demo/Twitter_Api_Key to denote the API key, the placeholder Demo/Twitter_bearer_token to denote the bearer token, and placeholder Lambda_Rotate_Bearer_Token to denote the custom Lambda function. Be sure to replace these placeholders with the resource names from your account.
Phase 1: Store a Twitter API key and bearer token in Secrets Manager
Twitter enables developers to register their applications and retrieve an API key, which includes a consumer_key and consumer_secret. Developers use these to generate a bearer token that applications can then use to authenticate and retrieve information from Twitter. At any given point of time, you can use an API key to create only one valid bearer token.
Start by storing the API key in Secrets Manager. Here’s how:
Figure 1: The “Store a new secret” button in the AWS Secrets Manager console
Select Other type of secrets (because you’re storing an API key).
Input the consumer_key and consumer_secret, and then select Next.
Figure 2: Select the consumer_key and the consumer_secret
Specify values for Secret Name and Description, then select Next. For this example, I use Demo/Twitter_API_Key.
Figure 3: Set values for “Secret Name” and “Description”
On the next screen, keep the default setting, Disable automatic rotation, because you’ll use the same API key to rotate bearer tokens programmatically and automatically. Applications and employees will not retrieve this API key. Select Next.
Figure 4: Keep the default “Disable automatic rotation” setting
Review the information on the next screen and, if everything looks correct, select Store. You’ve now successfully stored a Twitter API key in Secrets Manager.
Next, store the bearer token in Secrets Manager. Here’s how:
From the Secrets Manager console, select Store a new secret, select Other type of secrets, input details (access_token, token_type, and ARN of the API key) about the bearer token, and then select Next.
Figure 5: Add details about the bearer token
Specify values for Secret Name and Description, and then select Next. For this example, I use Demo/Twitter_bearer_token.
Figure 6: Again set values for “Secret Name” and “Description”
Keep the default rotation setting, Disable automatic rotation, and then select Next. You’ll enable rotation after you’ve updated the application to use Secrets Manager APIs to retrieve secrets.
Review the information and select Store. You’ve now completed storing the bearer token in Secrets Manager. I take note of the sample code provided on the review page. I’ll use this code to update my application to retrieve the bearer token using Secrets Manager APIs.
Figure 7: The sample code you can use in your app
Phase 2: Create a custom Lambda function to rotate the bearer token
While Secrets Manager supports rotating credentials for databases hosted on Amazon RDS natively, it also enables you to meet your unique rotation-related use cases by authoring custom Lambda functions. Now that you’ve stored the API key and bearer token, you’ll create a Lambda function to rotate the bearer token. For this example, I’ll create my Lambda function using Python 3.6.
Figure 8: In the Lambda console, select “Create function”
Select Author from scratch. For this example, I use the name Lambda_Rotate_Bearer_Token for my Lambda function. I also set the Runtime environment as Python 3.6.
Figure 9: Create a new function from scratch
This Lambda function requires permissions to call AWS resources on your behalf. To grant these permissions, select Create a custom role. This opens a console tab.
Select Create a new IAM Role and specify the value for Role Name. For this example, I use Role_Lambda_Rotate_Twitter_Bearer_Token.
Figure 10: For “IAM Role,” select “Create a new IAM role”
Next, to define the IAM permissions, copy and paste the following IAM policy in the View Policy Document text-entry field. Be sure to replace the placeholder ARN-OF-Demo/Twitter_API_Key with the ARN of your secret.
Figure 11: The IAM policy pasted in the “View Policy Document” text-entry field
Now, select Allow. This brings me back to the Lambda console with the appropriate Role selected.
Select Create function.
Figure 12: Select the “Create function” button in the lower-right corner
Copy the following Python code and paste it in the Function code section.
import base64
import json
import logging
import os
import boto3
from botocore.vendored import requests
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def lambda_handler(event, context):
"""Secrets Manager Twitter Bearer Token Handler
This handler uses the master-user rotation scheme to rotate a bearer token of a Twitter app.
The Secret PlaintextString is expected to be a JSON string with the following format:
{
'access_token': ,
'token_type': ,
'masterarn':
}
Args:
event (dict): Lambda dictionary of event parameters. These keys must include the following:
- SecretId: The secret ARN or identifier
- ClientRequestToken: The ClientRequestToken of the secret version
- Step: The rotation step (one of createSecret, setSecret, testSecret, or finishSecret)
context (LambdaContext): The Lambda runtime information
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
ValueError: If the secret is not properly configured for rotation
KeyError: If the secret json does not contain the expected keys
"""
arn = event['SecretId']
token = event['ClientRequestToken']
step = event['Step']
# Setup the client and environment variables
service_client = boto3.client('secretsmanager', endpoint_url=os.environ['SECRETS_MANAGER_ENDPOINT'])
oauth2_token_url = os.environ['TWITTER_OAUTH2_TOKEN_URL']
oauth2_invalid_token_url = os.environ['TWITTER_OAUTH2_INVALID_TOKEN_URL']
tweet_search_url = os.environ['TWITTER_SEARCH_URL']
# Make sure the version is staged correctly
metadata = service_client.describe_secret(SecretId=arn)
if not metadata['RotationEnabled']:
logger.error("Secret %s is not enabled for rotation" % arn)
raise ValueError("Secret %s is not enabled for rotation" % arn)
versions = metadata['VersionIdsToStages']
if token not in versions:
logger.error("Secret version %s has no stage for rotation of secret %s." % (token, arn))
raise ValueError("Secret version %s has no stage for rotation of secret %s." % (token, arn))
if "AWSCURRENT" in versions[token]:
logger.info("Secret version %s already set as AWSCURRENT for secret %s." % (token, arn))
return
elif "AWSPENDING" not in versions[token]:
logger.error("Secret version %s not set as AWSPENDING for rotation of secret %s." % (token, arn))
raise ValueError("Secret version %s not set as AWSPENDING for rotation of secret %s." % (token, arn))
# Call the appropriate step
if step == "createSecret":
create_secret(service_client, arn, token, oauth2_token_url, oauth2_invalid_token_url)
elif step == "setSecret":
set_secret(service_client, arn, token, oauth2_token_url)
elif step == "testSecret":
test_secret(service_client, arn, token, tweet_search_url)
elif step == "finishSecret":
finish_secret(service_client, arn, token)
else:
logger.error("lambda_handler: Invalid step parameter %s for secret %s" % (step, arn))
raise ValueError("Invalid step parameter %s for secret %s" % (step, arn))
def create_secret(service_client, arn, token, oauth2_token_url, oauth2_invalid_token_url):
"""Get a new bearer token from Twitter
This method invalidates existing bearer token for the Twitter app and retrieves a new one from Twitter.
If a secret version with AWSPENDING stage exists, updates it with the newly retrieved bearer token and if
the AWSPENDING stage does not exist, creates a new version of the secret with that stage label.
Args:
service_client (client): The secrets manager service client
arn (string): The secret ARN or other identifier
token (string): The ClientRequestToken associated with the secret version
oauth2_token_url (string): The Twitter API endpoint to request a bearer token
oauth2_invalid_token_url (string): The Twitter API endpoint to invalidate a bearer token
Raises:
ValueError: If the current secret is not valid JSON
KeyError: If the secret json does not contain the expected keys
ResourceNotFoundException: If the current secret is not found
"""
# Make sure the current secret exists and try to get the master arn from the secret
try:
current_secret_dict = get_secret_dict(service_client, arn, "AWSCURRENT")
master_arn = current_secret_dict['masterarn']
logger.info("createSecret: Successfully retrieved secret for %s." % arn)
except service_client.exceptions.ResourceNotFoundException:
return
# create bearer token credentials to be passed as authorization string to Twitter
bearer_token_credentials = encode_credentials(service_client, master_arn, "AWSCURRENT")
# get the bearer token from Twitter
bearer_token_from_twitter = get_bearer_token(bearer_token_credentials,oauth2_token_url)
# invalidate the current bearer token
invalidate_bearer_token(oauth2_invalid_token_url,bearer_token_credentials,bearer_token_from_twitter)
# get a new bearer token from Twitter
new_bearer_token = get_bearer_token(bearer_token_credentials, oauth2_token_url)
# if a secret version with AWSPENDING stage exists, update it with the lastest bearer token
# if the AWSPENDING stage does not exist, then create the version with AWSPENDING stage
try:
pending_secret_dict = get_secret_dict(service_client, arn, "AWSPENDING", token)
pending_secret_dict['access_token'] = new_bearer_token
service_client.put_secret_value(SecretId=arn, ClientRequestToken=token, SecretString=json.dumps(pending_secret_dict), VersionStages=['AWSPENDING'])
logger.info("createSecret: Successfully invalidated the bearer token of the secret %s and updated the pending version" % arn)
except service_client.exceptions.ResourceNotFoundException:
current_secret_dict['access_token'] = new_bearer_token
service_client.put_secret_value(SecretId=arn, ClientRequestToken=token, SecretString=json.dumps(current_secret_dict), VersionStages=['AWSPENDING'])
logger.info("createSecret: Successfully invalidated the bearer token of the secret %s and and created the pending version." % arn)
def set_secret(service_client, arn, token, oauth2_token_url):
"""Validate the pending secret with that in Twitter
This method checks wether the bearer token in Twitter is the same as the one in the version with AWSPENDING stage.
Args:
service_client (client): The secrets manager service client
arn (string): The secret ARN or other identifier
token (string): The ClientRequestToken associated with the secret version
oauth2_token_url (string): The Twitter API endopoint to get a bearer token
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
ValueError: If the secret is not valid JSON or master credentials could not be used to login to DB
KeyError: If the secret json does not contain the expected keys
"""
# First get the pending version of the bearer token and compare it with that in Twitter
pending_secret_dict = get_secret_dict(service_client, arn, "AWSPENDING")
master_arn = pending_secret_dict['masterarn']
# create bearer token credentials to be passed as authorization string to Twitter
bearer_token_credentials = encode_credentials(service_client, master_arn, "AWSCURRENT")
# get the bearer token from Twitter
bearer_token_from_twitter = get_bearer_token(bearer_token_credentials, oauth2_token_url)
# if the bearer tokens are same, invalidate the bearer token in Twitter
# if not, raise an exception that bearer token in Twitter was changed outside Secrets Manager
if pending_secret_dict['access_token'] == bearer_token_from_twitter:
logger.info("createSecret: Successfully verified the bearer token of arn %s" % arn)
else:
raise ValueError("The bearer token of the Twitter app was changed outside Secrets Manager. Please check.")
def test_secret(service_client, arn, token, tweet_search_url):
"""Test the pending secret by calling a Twitter API
This method tries to use the bearer token in the secret version with AWSPENDING stage and search for tweets
with 'aws secrets manager' string.
Args:
service_client (client): The secrets manager service client
arn (string): The secret ARN or other identifier
token (string): The ClientRequestToken associated with the secret version
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
ValueError: If the secret is not valid JSON or pending credentials could not be used to login to the database
KeyError: If the secret json does not contain the expected keys
"""
# First get the pending version of the bearer token and compare it with that in Twitter
pending_secret_dict = get_secret_dict(service_client, arn, "AWSPENDING", token)
# Now verify you can search for tweets using the bearer token
if verify_bearer_token(pending_secret_dict['access_token'], tweet_search_url):
logger.info("testSecret: Successfully authorized with the pending secret in %s." % arn)
return
else:
logger.error("testSecret: Unable to authorize with the pending secret of secret ARN %s" % arn)
raise ValueError("Unable to connect to Twitter with pending secret of secret ARN %s" % arn)
def finish_secret(service_client, arn, token):
"""Finish the rotation by marking the pending secret as current
This method moves the secret from the AWSPENDING stage to the AWSCURRENT stage.
Args:
service_client (client): The secrets manager service client
arn (string): The secret ARN or other identifier
token (string): The ClientRequestToken associated with the secret version
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
"""
# First describe the secret to get the current version
metadata = service_client.describe_secret(SecretId=arn)
current_version = None
for version in metadata["VersionIdsToStages"]:
if "AWSCURRENT" in metadata["VersionIdsToStages"][version]:
if version == token:
# The correct version is already marked as current, return
logger.info("finishSecret: Version %s already marked as AWSCURRENT for %s" % (version, arn))
return
current_version = version
break
# Finalize by staging the secret version current
service_client.update_secret_version_stage(SecretId=arn, VersionStage="AWSCURRENT", MoveToVersionId=token, RemoveFromVersionId=current_version)
logger.info("finishSecret: Successfully set AWSCURRENT stage to version %s for secret %s." % (version, arn))
def encode_credentials(service_client, arn, stage):
"""Encodes the Twitter credentials
This helper function encodes the Twitter credentials (consumer_key and consumer_secret)
Args:
service_client (client):The secrets manager service client
arn (string): The secret ARN or other identifier
stage (stage): The stage identifying the secret version
Returns:
encoded_credentials (string): base64 encoded authorization string for Twitter
Raises:
KeyError: If the secret json does not contain the expected keys
"""
required_fields = ['consumer_key','consumer_secret']
master_secret_dict = get_secret_dict(service_client, arn, stage)
for field in required_fields:
if field not in master_secret_dict:
raise KeyError("%s key is missing from the secret JSON" % field)
encoded_credentials = base64.urlsafe_b64encode(
'{}:{}'.format(master_secret_dict['consumer_key'], master_secret_dict['consumer_secret']).encode('ascii')).decode('ascii')
return encoded_credentials
def get_bearer_token(encoded_credentials, oauth2_token_url):
"""Gets a bearer token from Twitter
This helper function retrieves the current bearer token from Twitter, given a set of credentials.
Args:
encoded_credentials (string): Twitter credentials for authentication
oauth2_token_url (string): REST API endpoint to request a bearer token from Twitter
Raises:
KeyError: If the secret json does not contain the expected keys
"""
headers = {
'Authorization': 'Basic {}'.format(encoded_credentials),
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
}
data = 'grant_type=client_credentials'
response = requests.post(oauth2_token_url, headers=headers, data=data)
response_data = response.json()
if response_data['token_type'] == 'bearer':
bearer_token = response_data['access_token']
return bearer_token
else:
raise RuntimeError('unexpected token type: {}'.format(response_data['token_type']))
def invalidate_bearer_token(oauth2_invalid_token_url, bearer_token_credentials, bearer_token):
"""Invalidates a Bearer Token of a Twitter App
This helper function invalidates a bearer token of a Twitter app.
If successful, it returns the invalidated bearer token, else None
Args:
oauth2_invalid_token_url (string): The Twitter API endpoint to invalidate a bearer token
bearer_token_credentials (string): encoded consumer key and consumer secret to authenticate with Twitter
bearer_token (string): The bearer token to be invalidated
Returns:
invalidated_bearer_token: The invalidated bearer token
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
ValueError: If the secret is not valid JSON
KeyError: If the secret json does not contain the expected keys
"""
headers = {
'Authorization': 'Basic {}'.format(bearer_token_credentials),
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
}
data = 'access_token=' + bearer_token
invalidate_response = requests.post(oauth2_invalid_token_url, headers=headers, data=data)
invalidate_response_data = invalidate_response.json()
if invalidate_response_data:
return
else:
raise RuntimeError('Invalidate bearer token request failed')
def verify_bearer_token(bearer_token, tweet_search_url):
"""Verifies access to Twitter APIs using a bearer token
This helper function verifies that the bearer token is valid by calling Twitter's search/tweets API endpoint
Args:
bearer_token (string): The current bearer token for the application
Returns:
True or False
Raises:
KeyError: If the response of search tweets API call fails
"""
headers = {
'Authorization' : 'Bearer {}'.format(bearer_token),
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
}
search_results = requests.get(tweet_search_url, headers=headers)
try:
search_results.json()['statuses']
return True
except:
return False
def get_secret_dict(service_client, arn, stage, token=None):
"""Gets the secret dictionary corresponding for the secret arn, stage, and token
This helper function gets credentials for the arn and stage passed in and returns the dictionary by parsing the JSON string
Args:
service_client (client): The secrets manager service client
arn (string): The secret ARN or other identifier
token (string): The ClientRequestToken associated with the secret version, or None if no validation is desired
stage (string): The stage identifying the secret version
Returns:
SecretDictionary: Secret dictionary
Raises:
ResourceNotFoundException: If the secret with the specified arn and stage does not exist
ValueError: If the secret is not valid JSON
"""
# Only do VersionId validation against the stage if a token is passed in
if token:
secret = service_client.get_secret_value(SecretId=arn, VersionId=token, VersionStage=stage)
else:
secret = service_client.get_secret_value(SecretId=arn, VersionStage=stage)
plaintext = secret['SecretString']
# Parse and return the secret JSON string
return json.loads(plaintext)
Here’s what it will look like:
Figure 13: The Python code pasted in the “Function code” section
On the same page, provide the following environment variables:
Note: Resources used in this example are in US East (Ohio) region. If you intend to use another AWS Region, change the SECRETS_MANAGER_ENDPOINT set in the Environment variables to the appropriate region.
You’ve now created a Lambda function that can rotate the bearer token:
Figure 15: The new Lambda function
Before you can configure Secrets Manager to use this Lambda function, you need to update the function policy of the Lambda function. A function policy permits AWS services, such as Secrets Manager, to invoke a Lambda function on behalf of your application. You can attach a Lambda function policy from the AWS Command Line Interface (AWS CLI) or SDK. To attach a function policy, call the add-permission Lambda API from the AWS CLI.
Phase 3: Configure your application to retrieve the bearer token from Secrets Manager
Now that you’ve stored the bearer token in Secrets Manager, update the application to retrieve the bearer token from Secrets Manager instead of hard-coding this information in a configuration file or source code. For this example, I show you how to configure a Python application to retrieve this secret from Secrets Manager.
import config
def no_secrets_manager_sample()
# Get the bearer token from a config file.
Bearer_token = config.bearer_token
# Use the bearer token to authenticate requests to Twitter
Use the sample code from section titled Phase 1 and update the application to retrieve the bearer token from Secrets Manager. The following code sets up the client and retrieves and decrypts the secret Demo/Twitter_bearer_token.
# Use this code snippet in your app.
import boto3
from botocore.exceptions import ClientError
def get_secret():
secret_name = "Demo/Twitter_bearer_token"
endpoint_url = "https://secretsmanager.us-east-2.amazonaws.com"
region_name = "us-east-2"
session = boto3.session.Session()
client = session.client(
service_name='secretsmanager',
region_name=region_name,
endpoint_url=endpoint_url
)
try:
get_secret_value_response = client.get_secret_value(
SecretId=secret_name
)
except ClientError as e:
if e.response['Error']['Code'] == 'ResourceNotFoundException':
print("The requested secret " + secret_name + " was not found")
elif e.response['Error']['Code'] == 'InvalidRequestException':
print("The request was invalid due to:", e)
elif e.response['Error']['Code'] == 'InvalidParameterException':
print("The request had invalid params:", e)
else:
# Decrypted secret using the associated KMS CMK
# Depending on whether the secret was a string or binary, one of these fields will be populated
if 'SecretString' in get_secret_value_response:
secret = get_secret_value_response['SecretString']
else:
binary_secret_data = get_secret_value_response['SecretBinary']
# Your code goes here.
Applications require permissions to access Secrets Manager. My application runs on Amazon EC2 and uses an IAM role to get access to AWS services. I’ll attach the following policy to my IAM role, and you should take a similar action with your IAM role. This policy uses the GetSecretValue action to grant my application permissions to read secrets from Secrets Manager. This policy also uses the resource element to limit my application to read only the Demo/Twitter_bearer_token secret from Secrets Manager. Read the AWS Secrets Manager documentation to understand the minimum IAM permissions required to retrieve a secret.
{
"Version": "2012-10-17",
"Statement": {
"Sid": "RetrieveBearerToken",
"Effect": "Allow",
"Action": "secretsmanager:GetSecretValue",
"Resource": Input ARN of the secret Demo/Twitter_bearer_token here
}
}
Note: To improve the resiliency of your applications, associate your application with two API keys/bearer tokens. This is a higher availability option because you can continue to use one bearer token while Secrets Manager rotates the other token. Read the AWS documentation to learn how AWS Secrets Manager rotates your secrets.
Phase 4: Enable and verify rotation
Now that you’ve stored the secret in Secrets Manager and created a Lambda function to rotate this secret, configure Secrets Manager to rotate the secret Demo/Twitter_bearer_token.
From the Secrets Manager console, go to the list of secrets and choose the secret you created in the first step (in my example, this is named Demo/Twitter_bearer_token).
Scroll to Rotation configuration, and then select Edit rotation.
Figure 16: Select the “Edit rotation” button
To enable rotation, select Enable automatic rotation, and then choose how frequently you want Secrets Manager to rotate this secret. For this example, I set the rotation interval to 30 days. I also choose the rotation Lambda function, Lambda_Rotate_Bearer_Token, from the drop-down list.
Figure 17: “Edit rotation configuration” options
The banner on the next screen confirms that I have successfully configured rotation and the first rotation is in progress, which enables you to verify that rotation is functioning as expected. Secrets Manager will rotate this credential automatically every 30 days.
Figure 18: Confirmation notice
Summary
In this post, I showed you how to configure Secrets Manager to manage and rotate an API key and bearer token used by applications to authenticate and retrieve information from Twitter. You can use the steps described in this blog to manage and rotate other API keys, as well.
Secrets Manager helps you protect access to your applications, services, and IT resources without the upfront investment and on-going maintenance costs of operating your own secrets management infrastructure. To get started, open the Secrets Manager console. To learn more, read the Secrets Manager documentation.
If you have comments about this post, submit them in the Comments section below. If you have questions about anything in this post, start a new thread on the Secrets Manager forum or contact AWS Support.
Want more AWS Security news? Follow us on Twitter.
Thanks to Greg Eppel, Sr. Solutions Architect, Microsoft Platform for this great blog that describes how to create a custom CodeBuild build environment for the .NET Framework. — AWS CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy. CodeBuild provides curated build environments for programming languages and runtimes such as Android, Go, Java, Node.js, PHP, Python, Ruby, and Docker. CodeBuild now supports builds for the Microsoft Windows Server platform, including a prepackaged build environment for .NET Core on Windows. If your application uses the .NET Framework, you will need to use a custom Docker image to create a custom build environment that includes the Microsoft proprietary Framework Class Libraries. For information about why this step is required, see our FAQs. In this post, I’ll show you how to create a custom build environment for .NET Framework applications and walk you through the steps to configure CodeBuild to use this environment.
Build environments are Docker images that include a complete file system with everything required to build and test your project. To use a custom build environment in a CodeBuild project, you build a container image for your platform that contains your build tools, push it to a Docker container registry such as Amazon Elastic Container Registry (Amazon ECR), and reference it in the project configuration. When it builds your application, CodeBuild retrieves the Docker image from the container registry specified in the project configuration and uses the environment to compile your source code, run your tests, and package your application.
Step 1: Launch EC2 Windows Server 2016 with Containers
In the Amazon EC2 console, in your region, launch an Amazon EC2 instance from a Microsoft Windows Server 2016 Base with Containers AMI.
Increase disk space on the boot volume to at least 50 GB to account for the larger size of containers required to install and run Visual Studio Build Tools.
Run the following command in that directory. This process can take a while. It depends on the size of EC2 instance you launched. In my tests, a t2.2xlarge takes less than 30 minutes to build the image and produces an approximately 15 GB image.
docker build -t buildtools2017:latest -m 2GB .
Run the following command to test the container and start a command shell with all the developer environment variables:
docker run -it buildtools2017
Create a repository in the Amazon ECS console. For the repository name, type buildtools2017. Choose Next step and then complete the remaining steps.
Execute the following command to generate authentication details for our registry to the local Docker engine. Make sure you have permissions to the Amazon ECR registry before you execute the command.
aws ecr get-login
In the same command prompt window, copy and paste the following commands:
In the CodeCommit console, create a repository named DotNetFrameworkSampleApp. On the Configure email notifications page, choose Skip.
Clone a .NET Framework Docker sample application from GitHub. The repository includes a sample ASP.NET Framework that we’ll use to demonstrate our custom build environment.On the EC2 instance, open a command prompt and execute the following commands:
Navigate to the CodeCommit repository and confirm that the files you just pushed are there.
Step 4: Configure build spec
To build your .NET Framework application with CodeBuild you use a build spec, which is a collection of build commands and related settings, in YAML format, that AWS CodeBuild can use to run a build. You can include a build spec as part of the source code or you can define a build spec when you create a build project. In this example, I include a build spec as part of the source code.
In the root directory of your source directory, create a YAML file named buildspec.yml.
At this point, we have a Docker image with Visual Studio Build Tools installed and stored in the Amazon ECR registry. We also have a sample ASP.NET Framework application in a CodeCommit repository. Now we are going to set up CodeBuild to build the ASP.NET Framework application.
In the Amazon ECR console, choose the repository that was pushed earlier with the docker push command. On the Permissions tab, choose Add.
For Source Provider, choose AWS CodeCommit and then choose the called DotNetFrameworkSampleApp repository.
For Environment Image, choose Specify a Docker image.
For Environment type, choose Windows.
For Custom image type, choose Amazon ECR.
For Amazon ECR repository, choose the Docker image with the Visual Studio Build Tools installed, buildtools2017. Your configuration should look like the image below:
Choose Continue and then Save and Build to create your CodeBuild project and start your first build. You can monitor the status of the build in the console. You can also configure notifications that will notify subscribers whenever builds succeed, fail, go from one phase to another, or any combination of these events.
Summary
CodeBuild supports a number of platforms and languages out of the box. By using custom build environments, it can be extended to other runtimes. In this post, I showed you how to build a .NET Framework environment on a Windows container and demonstrated how to use it to build .NET Framework applications in CodeBuild.
We’re excited to see how customers extend and use CodeBuild to enable continuous integration and continuous delivery for their Windows applications. Feel free to share what you’ve learned extending CodeBuild for your own projects. Just leave questions or suggestions in the comments.
Slack is widely used by DevOps and development teams to communicate status. Typically, when a build has been tested and is ready to be promoted to a staging environment, a QA engineer or DevOps engineer kicks off the deployment. Using Slack in a ChatOps collaboration model, the promotion can be done in a single click from a Slack channel. And because the promotion happens through a Slack channel, the whole development team knows what’s happening without checking email.
In this blog post, I will show you how to integrate AWS services with a Slack application. I use an interactive message button and incoming webhook to promote a stage with a single click.
To follow along with the steps in this post, you’ll need a pipeline in AWS CodePipeline. If you don’t have a pipeline, the fastest way to create one for this use case is to use AWS CodeStar. Go to the AWS CodeStar console and select the Static Website template (shown in the screenshot). AWS CodeStar will create a pipeline with an AWS CodeCommit repository and an AWS CodeDeploy deployment for you. After the pipeline is created, you will need to add a manual approval stage.
You’ll also need to build a Slack app with webhooks and interactive components, write two Lambda functions, and create an API Gateway API and a SNS topic.
As you’ll see in the following diagram, when I make a change and merge a new feature into the master branch in AWS CodeCommit, the check-in kicks off my CI/CD pipeline in AWS CodePipeline. When CodePipeline reaches the approval stage, it sends a notification to Amazon SNS, which triggers an AWS Lambda function (ApprovalRequester).
The Slack channel receives a prompt that looks like the following screenshot. When I click Yes to approve the build promotion, the approval result is sent to CodePipeline through API Gateway and Lambda (ApprovalHandler). The pipeline continues on to deploy the build to the next environment.
Create a Slack app
For App Name, type a name for your app. For Development Slack Workspace, choose the name of your workspace. You’ll see in the following screenshot that my workspace is AWS ChatOps.
After the Slack application has been created, you will see the Basic Information page, where you can create incoming webhooks and enable interactive components.
To add incoming webhooks:
Under Add features and functionality, choose Incoming Webhooks. Turn the feature on by selecting Off, as shown in the following screenshot.
Now that the feature is turned on, choose Add New Webhook to Workspace. In the process of creating the webhook, Slack lets you choose the channel where messages will be posted.
After the webhook has been created, you’ll see its URL. You will use this URL when you create the Lambda function.
If you followed the steps in the post, the pipeline should look like the following.
Write the Lambda function for approval requests
This Lambda function is invoked by the SNS notification. It sends a request that consists of an interactive message button to the incoming webhook you created earlier. The following sample code sends the request to the incoming webhook. WEBHOOK_URL and SLACK_CHANNEL are the environment variables that hold values of the webhook URL that you created and the Slack channel where you want the interactive message button to appear.
# This function is invoked via SNS when the CodePipeline manual approval action starts.
# It will take the details from this approval notification and sent an interactive message to Slack that allows users to approve or cancel the deployment.
import os
import json
import logging
import urllib.parse
from base64 import b64decode
from urllib.request import Request, urlopen
from urllib.error import URLError, HTTPError
# This is passed as a plain-text environment variable for ease of demonstration.
# Consider encrypting the value with KMS or use an encrypted parameter in Parameter Store for production deployments.
SLACK_WEBHOOK_URL = os.environ['SLACK_WEBHOOK_URL']
SLACK_CHANNEL = os.environ['SLACK_CHANNEL']
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def lambda_handler(event, context):
print("Received event: " + json.dumps(event, indent=2))
message = event["Records"][0]["Sns"]["Message"]
data = json.loads(message)
token = data["approval"]["token"]
codepipeline_name = data["approval"]["pipelineName"]
slack_message = {
"channel": SLACK_CHANNEL,
"text": "Would you like to promote the build to production?",
"attachments": [
{
"text": "Yes to deploy your build to production",
"fallback": "You are unable to promote a build",
"callback_id": "wopr_game",
"color": "#3AA3E3",
"attachment_type": "default",
"actions": [
{
"name": "deployment",
"text": "Yes",
"style": "danger",
"type": "button",
"value": json.dumps({"approve": True, "codePipelineToken": token, "codePipelineName": codepipeline_name}),
"confirm": {
"title": "Are you sure?",
"text": "This will deploy the build to production",
"ok_text": "Yes",
"dismiss_text": "No"
}
},
{
"name": "deployment",
"text": "No",
"type": "button",
"value": json.dumps({"approve": False, "codePipelineToken": token, "codePipelineName": codepipeline_name})
}
]
}
]
}
req = Request(SLACK_WEBHOOK_URL, json.dumps(slack_message).encode('utf-8'))
response = urlopen(req)
response.read()
return None
Create a SNS topic
Create a topic and then create a subscription that invokes the ApprovalRequester Lambda function. You can configure the manual approval action in the pipeline to send a message to this SNS topic when an approval action is required. When the pipeline reaches the approval stage, it sends a notification to this SNS topic. SNS publishes a notification to all of the subscribed endpoints. In this case, the Lambda function is the endpoint. Therefore, it invokes and executes the Lambda function. For information about how to create a SNS topic, see Create a Topic in the Amazon SNS Developer Guide.
Write the Lambda function for handling the interactive message button
This Lambda function is invoked by API Gateway. It receives the result of the interactive message button whether or not the build promotion was approved. If approved, an API call is made to CodePipeline to promote the build to the next environment. If not approved, the pipeline stops and does not move to the next stage.
The Lambda function code might look like the following. SLACK_VERIFICATION_TOKEN is the environment variable that contains your Slack verification token. You can find your verification token under Basic Information on Slack manage app page. When you scroll down, you will see App Credential. Verification token is found under the section.
# This function is triggered via API Gateway when a user acts on the Slack interactive message sent by approval_requester.py.
from urllib.parse import parse_qs
import json
import os
import boto3
SLACK_VERIFICATION_TOKEN = os.environ['SLACK_VERIFICATION_TOKEN']
#Triggered by API Gateway
#It kicks off a particular CodePipeline project
def lambda_handler(event, context):
#print("Received event: " + json.dumps(event, indent=2))
body = parse_qs(event['body'])
payload = json.loads(body['payload'][0])
# Validate Slack token
if SLACK_VERIFICATION_TOKEN == payload['token']:
send_slack_message(json.loads(payload['actions'][0]['value']))
# This will replace the interactive message with a simple text response.
# You can implement a more complex message update if you would like.
return {
"isBase64Encoded": "false",
"statusCode": 200,
"body": "{\"text\": \"The approval has been processed\"}"
}
else:
return {
"isBase64Encoded": "false",
"statusCode": 403,
"body": "{\"error\": \"This request does not include a vailid verification token.\"}"
}
def send_slack_message(action_details):
codepipeline_status = "Approved" if action_details["approve"] else "Rejected"
codepipeline_name = action_details["codePipelineName"]
token = action_details["codePipelineToken"]
client = boto3.client('codepipeline')
response_approval = client.put_approval_result(
pipelineName=codepipeline_name,
stageName='Approval',
actionName='ApprovalOrDeny',
result={'summary':'','status':codepipeline_status},
token=token)
print(response_approval)
Create the API Gateway API
In the Amazon API Gateway console, create a resource called InteractiveMessageHandler.
Create a POST method.
For Integration type, choose Lambda Function.
Select Use Lambda Proxy integration.
From Lambda Region, choose a region.
In Lambda Function, type a name for your function.
Now go back to your Slack application and enable interactive components.
To enable interactive components for the interactive message (Yes) button:
Under Features, choose Interactive Components.
Choose Enable Interactive Components.
Type a request URL in the text box. Use the invoke URL in Amazon API Gateway that will be called when the approval button is clicked.
Now that all the pieces have been created, run the solution by checking in a code change to your CodeCommit repo. That will release the change through CodePipeline. When the CodePipeline comes to the approval stage, it will prompt to your Slack channel to see if you want to promote the build to your staging or production environment. Choose Yes and then see if your change was deployed to the environment.
Conclusion
That is it! You have now created a Slack ChatOps solution using AWS CodeCommit, AWS CodePipeline, AWS Lambda, Amazon API Gateway, and Amazon Simple Notification Service.
Now that you know how to do this Slack and CodePipeline integration, you can use the same method to interact with other AWS services using API Gateway and Lambda. You can also use Slack’s slash command to initiate an action from a Slack channel, rather than responding in the way demonstrated in this post.
Businesses and organizations that rely on macOS server for essential office and data services are facing some decisions about the future of their IT services.
Apple recently announced that it is deprecating a significant portion of essential network services in macOS Server, as they described in a support statement posted on April 24, 2018, “Prepare for changes to macOS Server.” Apple’s note includes:
macOS Server is changing to focus more on management of computers, devices, and storage on your network. As a result, some changes are coming in how Server works. A number of services will be deprecated, and will be hidden on new installations of an update to macOS Server coming in spring 2018.
The note lists the services that will be removed in a future release of macOS Server, including calendar and contact support, Dynamic Host Configuration Protocol (DHCP), Domain Name Services (DNS), mail, instant messages, virtual private networking (VPN), NetInstall, Web server, and the Wiki.
Apple assures users who have already configured any of the listed services that they will be able to use them in the spring 2018 macOS Server update, but the statement ends with links to a number of alternative services, including hosted services, that macOS Server users should consider as viable replacements to the features it is removing. These alternative services are all FOSS (Free and Open-Source Software).
As difficult as this could be for organizations that use macOS server, this is not unexpected. Apple left the server hardware space back in 2010, when Steve Jobs announced the company was ending its line of Xserve rackmount servers, which were introduced in May, 2002. Since then, macOS Server has hardly been a prominent part of Apple’s product lineup. It’s not just the product itself that has lost some luster, but the entire category of SMB office and business servers, which has been undergoing a gradual change in recent years.
Some might wonder how important the news about macOS Server is, given that macOS Server represents a pretty small share of the server market. macOS Server has been important to design shops, agencies, education users, and small businesses that likely have been on Macs for ages, but it’s not a significant part of the IT infrastructure of larger organizations and businesses.
What Comes After macOS Server?
Lovers of macOS Server don’t have to fear having their Mac minis pried from their cold, dead hands quite yet. Installed services will continue to be available. In the fall of 2018, new installations and upgrades of macOS Server will require users to migrate most services to other software. Since many of the services of macOS Server were already open-source, this means that a change in software might not be required. It does mean more configuration and management required from those who continue with macOS Server, however.
Users can continue with macOS Server if they wish, but many will see the writing on the wall and look for a suitable substitute.
The Times They Are A-Changin’
For many people working in organizations, what is significant about this announcement is how it reflects the move away from the once ubiquitous server-based IT infrastructure. Services that used to be centrally managed and office-based, such as storage, file sharing, communications, and computing, have moved to the cloud.
In selecting the next office IT platforms, there’s an opportunity to move to solutions that reflect and support how people are working and the applications they are using both in the office and remotely. For many, this means including cloud-based services in office automation, backup, and business continuity/disaster recovery planning. This includes Software as a Service, Platform as a Service, and Infrastructure as a Service (Saas, PaaS, IaaS) options.
IT solutions that integrate well with the cloud are worth strong consideration for what comes after a macOS Server-based environment.
Synology NAS as a macOS Server Alternative
One solution that is becoming popular is to replace macOS Server with a device that has the ability to provide important office services, but also bridges the office and cloud environments. Using Network-Attached Storage (NAS) to take up the server slack makes a lot of sense. Many customers are already using NAS for file sharing, local data backup, automatic cloud backup, and other uses. In the case of Synology, their operating system, Synology DiskStation Manager (DSM), is Linux based, and integrates the basic functions of file sharing, centralized backup, RAID storage, multimedia streaming, virtual storage, and other common functions.
Synology NAS
Since DSM is based on Linux, there are numerous server applications available, including many of the same ones that are available for macOS Server, which shares conceptual roots with Linux as it comes from BSD Unix.
Synology DiskStation Manager Package Center
According to Ed Lukacs, COO at 2FIFTEEN Systems Management in Salt Lake City, their customers have found the move from macOS Server to Synology NAS not only painless, but positive. DSM works seamlessly with macOS and has been faster for their customers, as well. Many of their customers are running Adobe Creative Suite and Google G Suite applications, so a workflow that combines local storage, remote access, and the cloud, is already well known to them. Remote users are supported by Synology’s QuickConnect or VPN.
Business continuity and backup are simplified by the flexible storage capacity of the NAS. Synology has built-in backup to Backblaze B2 Cloud Storage with Synology’s Cloud Sync, as well as a choice of a number of other B2-compatible applications, such as Cloudberry, Comet, and Arq.
Customers have been able to get up and running quickly, with only initial data transfers requiring some time to complete. After that, management of the NAS can be handled in-house or with the support of a Managed Service Provider (MSP).
Are You Sticking with macOS Server or Moving to Another Platform?
If you’re affected by this change in macOS Server, please let us know in the comments how you’re planning to cope. Are you using Synology NAS for server services? Please tell us how that’s working for you.
I’m in danger of contradicting myself, after previously pointing out that x86 machine code is a high-level language, but this article claiming C is a not a low level language is bunk. C certainly has some problems, but it’s still the closest language to assembly. This is obvious by the fact it’s still the fastest compiled language. What we see is a typical academic out of touch with the real world.
The author makes the (wrong) observation that we’ve been stuck emulating the PDP-11 for the past 40 years. C was written for the PDP-11, and since then CPUs have been designed to make C run faster. The author imagines a different world, such as where CPU designers instead target something like LISP as their preferred language, or Erlang. This misunderstands the state of the market. CPUs do indeed supports lots of different abstractions, and C has evolved to accommodate this.
The author criticizes things like “out-of-order” execution which has lead to the Spectre sidechannel vulnerabilities. Out-of-order execution is necessary to make C run faster. The author claims instead that those resources should be spent on having more slower CPUs, with more threads. This sacrifices single-threaded performance in exchange for a lot more threads executing in parallel. The author cites Sparc Tx CPUs as his ideal processor.
But here’s the thing, the Sparc Tx was a failure. To be fair, it’s mostly a failure because most of the time, people wanted to run old C code instead of new Erlang code. But it was still a failure at running Erlang.
Time after time, engineers keep finding that “out-of-order”, single-threaded performance is still the winner. A good example is ARM processors for both mobile phones and servers. All the theory points to in-order CPUs as being better, but all the products are out-of-order, because this theory is wrong. The custom ARM cores from Apple and Qualcomm used in most high-end phones are so deeply out-of-order they give Intel CPUs competition. The same is true on the server front with the latest Qualcomm Centriq and Cavium ThunderX2 processors, deeply out of order supporting more than 100 instructions in flight.
The Cavium is especially telling. Its ThunderX CPU had 48 simple cores which was replaced with the ThunderX2 having 32 complex, deeply out-of-order cores. The performance increase was massive, even on multithread-friendly workloads. Every competitor to Intel’s dominance in the server space has learned the lesson from Sparc Tx: many wimpy cores is a failure, you need fewer beefy cores. Yes, they don’t need to be as beefy as Intel’s processors, but they need to be close.
Even Intel’s “Xeon Phi” custom chip learned this lesson. This is their GPU-like chip, running 60 cores with 512-bit wide “vector” (sic) instructions, designed for supercomputer applications. Its first version was purely in-order. Its current version is slightly out-of-order. It supports four threads and focuses on basic number crunching, so in-order cores seems to be the right approach, but Intel found in this case that out-of-order processing still provided a benefit. Practice is different than theory.
As an academic, the author of the above article focuses on abstractions. The criticism of C is that it has the wrong abstractions which are hard to optimize, and that if we instead expressed things in the right abstractions, it would be easier to optimize.
This is an intellectually compelling argument, but so far bunk.
The reason is that while the theoretical base language has issues, everyone programs using extensions to the language, like “intrinsics” (C ‘functions’ that map to assembly instructions). Programmers write libraries using these intrinsics, which then the rest of the normal programmers use. In other words, if your criticism is that C is not itself low level enough, it still provides the best access to low level capabilities.
Given that C can access new functionality in CPUs, CPU designers add new paradigms, from SIMD to transaction processing. In other words, while in the 1980s CPUs were designed to optimize C (stacks, scaled pointers), these days CPUs are designed to optimize tasks regardless of language.
The author of that article criticizes the memory/cache hierarchy, claiming it has problems. Yes, it has problems, but only compared to how well it normally works. The author praises the many simple cores/threads idea as hiding memory latency with little caching, but misses the point that caches also dramatically increase memory bandwidth. Intel processors are optimized to read a whopping 256 bits every clock cycle from L1 cache. Main memory bandwidth is orders of magnitude slower.
The author goes onto criticize cache coherency as a problem. C uses it, but other languages like Erlang don’t need it. But that’s largely due to the problems each languages solves. Erlang solves the problem where a large number of threads work on largely independent tasks, needing to send only small messages to each other across threads. The problems C solves is when you need many threads working on a huge, common set of data.
For example, consider the “intrusion prevention system”. Any thread can process any incoming packet that corresponds to any region of memory. There’s no practical way of solving this problem without a huge coherent cache. It doesn’t matter which language or abstractions you use, it’s the fundamental constraint of the problem being solved. RDMA is an important concept that’s moved from supercomputer applications to the data center, such as with memcached. Again, we have the problem of huge quantities (terabytes worth) shared among threads rather than small quantities (kilobytes).
The fundamental issue the author of the the paper is ignoring is decreasing marginal returns. Moore’s Law has gifted us more transistors than we can usefully use. We can’t apply those additional registers to just one thing, because the useful returns we get diminish.
For example, Intel CPUs have two hardware threads per core. That’s because there are good returns by adding a single additional thread. However, the usefulness of adding a third or fourth thread decreases. That’s why many CPUs have only two threads, or sometimes four threads, but no CPU has 16 threads per core.
You can apply the same discussion to any aspect of the CPU, from register count, to SIMD width, to cache size, to out-of-order depth, and so on. Rather than focusing on one of these things and increasing it to the extreme, CPU designers make each a bit larger every process tick that adds more transistors to the chip.
The same applies to cores. It’s why the “more simpler cores” strategy fails, because more cores have their own decreasing marginal returns. Instead of adding cores tied to limited memory bandwidth, it’s better to add more cache. Such cache already increases the size of the cores, so at some point it’s more effective to add a few out-of-order features to each core rather than more cores. And so on.
The question isn’t whether we can change this paradigm and radically redesign CPUs to match some academic’s view of the perfect abstraction. Instead, the goal is to find new uses for those additional transistors. For example, “message passing” is a useful abstraction in languages like Go and Erlang that’s often more useful than sharing memory. It’s implemented with shared memory and atomic instructions, but I can’t help but think it couldn’t better be done with direct hardware support.
Of course, as soon as they do that, it’ll become an intrinsic in C, then added to languages like Go and Erlang.
Summary Academics live in an ideal world of abstractions, the rest of us live in practical reality. The reality is that vast majority of programmers work with the C family of languages (JavaScript, Go, etc.), whereas academics love the epiphanies they learned using other languages, especially function languages. CPUs are only superficially designed to run C and “PDP-11 compatibility”. Instead, they keep adding features to support other abstractions, abstractions available to C. They are driven by decreasing marginal returns — they would love to add new abstractions to the hardware because it’s a cheap way to make use of additional transitions. Academics are wrong believing that the entire system needs to be redesigned from scratch. Instead, they just need to come up with new abstractions CPU designers can add.
GDPR day, May 25, 2018, is nearly here. On that day, will your inbox explode with update notices, opt-in agreements, and offers from lawyers searching for GDPR violators? Perhaps all the companies on earth that are not GDPR ready will just dissolve into dust. More likely, there will be some changes, but business as usual will continue and we’ll all be more aware of data privacy. Let’s go with the last one.
What’s Different With GDPR at Backblaze
The biggest difference you’ll notice is a completely updated Privacy Policy. Last week we sent out a service email announcing the new Privacy Policy. Some people asked what was different. Basically everything. About 95% of the agreement was rewritten. In the agreement, we added in the appropriate provisions required by GDPR, and hopefully did a better job specifying the data we collect from you, why we collect it, and what we are going to do with it.
As a reminder, at Backblaze your data falls into two catagories. The first type of data is the data you store with us — stored data. These are the files and objects you upload and store, and as needed, restore. We do not share this data. We do not process this data, except as requested by you to store and restore the data. We do not analyze this data looking for keywords, tags, images, etc. No one outside of Backblaze has access to this data unless you explicitly shared the data by providing that person access to one or more files.
The second type of data is your account data. Some of your account data is considered personal data. This is the information we collect from you to provide our Personal Backup, Business Backup and B2 Cloud Storage services. Examples include your email address to provide access to your account, or the name of your computer so we can organize your files like they are arranged on your computer to make restoration easier. We have written a number of Help Articles covering the different ways this information is collected and processed. In addition, these help articles outline the various “rights” granted via GDPR. We will continue to add help articles over the coming weeks to assist in making it easy to work with us to understand and exercise your rights.
What’s New With GDPR at Backblaze
The most obvious addition is the Data Processing Addendum (DPA). This covers how we protect the data you store with us, i.e. stored data. As noted above, we don’t do anything with your data, except store it and keep it safe until you need it. Now we have a separate document saying that.
It is important to note the new Data Processing Addendum is now incorporated by reference into our Terms of Service, which everyone agrees to when they sign up for any of our services. Now all of our customers have a shiny new Data Processing Agreement to go along with the updated Privacy Policy. We promise they are not long or complicated, and we encourage you to read them. If you have any questions, stop by our GDPR help section on our website.
Patience, Please
Every company we have dealt with over the last few months is working hard to comply with GDPR. It has been a tough road whether you tried to do it yourself or like Backblaze, hired an EU-based law firm for advice. Over the coming weeks and months as you reach out to discover and assert your rights, please have a little patience. We are all going through a steep learning curve as GDPR gets put into practice. Along the way there are certain to be some growing pains — give us a chance, we all want to get it right.
Regardless, at Backblaze we’ve been diligently protecting our customers’ data for over 11 years and nothing that will happen on May 25th will change that.
One of the more useful features of masscan is the “–banners” check, which connects to the TCP port, sends some request, and gets a basic response back. However, since masscan has it’s own TCP stack, it’ll interfere with the operating system’s TCP stack if they are sharing the same IPv4 address. The operating system will reply with a RST packet before the TCP connection can be established.
The way to fix this is to use the built-in packet-filtering firewall to block those packets in the operating-system TCP/IP stack. The masscan program still sees everything before the packet-filter, but the operating system can’t see anything after the packet-filter.
Note that we are talking about the “packet-filter” firewall feature here. Remember that macOS, like most operating systems these days, has two separate firewalls: an application firewall and a packet-filter firewall. The application firewall is the one you see in System Settings labeled “Firewall”, and it controls things based upon the application’s identity rather than by which ports it uses. This is normally “on” by default. The packet-filter is normally “off” by default and is of little use to normal users.
Also note that macOS changed packet-filters around version 10.10.5 (“Yosemite”, October 2014). The older one is known as “ipfw“, which was the default firewall for FreeBSD (much of macOS is based on FreeBSD). The replacement is known as PF, which comes from OpenBSD. Whereas you used to use the old “ipfw” command on the command line, you now use the “pfctl” command, as well as the “/etc/pf.conf” configuration file.
What we need to filter is the source port of the packets that masscan will send, so that when replies are received, they won’t reach the operating-system stack, and just go to masscan instead. To do this, we need find a range of ports that won’t conflict with the operating system. Namely, when the operating system creates outgoing connections, it randomly chooses a source port within a certain range. We want to use masscan to use source ports in a different range.
To figure out the range macOS uses, we run the following command:
On my laptop, which is probably the default for macOS, I get the following range. Sniffing with Wireshark confirms this is the range used for source ports for outgoing connections.
So this means I shouldn’t use source ports anywhere in the range 49152 to 65535. On my laptop, I’ve decided to use for masscan the ports 40000 to 41023. The range masscan uses must be a power of 2, so here I’m using 1024 (two to the tenth power).
To configure masscan, I can either type the parameter “–source-port 40000-41023” every time I run the program, or I can add the following line to /etc/masscan/masscan.conf. Remember that by default, masscan will look in that configuration file for any configuration parameters, so you don’t have to keep retyping them on the command line.
source-port = 40000-41023
Next, I need to add the following firewall rule to the bottom of /etc/pf.conf:
block in proto tcp from any to any port 40000 >< 41024
However, we aren’t done yet. By default, the packet-filter firewall is off on some versions of macOS. Therefore, every time you reboot your computer, you need to enable it. The simple way to do this is on the command line run:
pfctl -e
Or, if that doesn’t work, try:
pfctl -E
If the firewall is already running, then you’ll need to load the file explicitly (or reboot):
This post courtesy of Jeff Levine Solutions Architect for Amazon Web Services
Amazon Linux 2 is the next generation of Amazon Linux, a Linux server operating system from Amazon Web Services (AWS). Amazon Linux 2 offers a high-performance Linux environment suitable for organizations of all sizes. It supports applications ranging from small websites to enterprise-class, mission-critical platforms.
Amazon Linux 2 includes support for the LAMP (Linux/Apache/MariaDB/PHP) stack, one of the most popular platforms for deploying websites. To secure the transmission of data-in-transit to such websites and prevent eavesdropping, organizations commonly leverage Secure Sockets Layer/Transport Layer Security (SSL/TLS) services which leverage certificates to provide encryption. The LAMP stack provided by Amazon Linux 2 includes a self-signed SSL/TLS certificate. Such certificates may be fine for internal usage but are not acceptable when attestation by a certificate authority is required.
In this post, I discuss how to extend the capabilities of Amazon Linux 2 by installing Let’s Encrypt, a certificate authority provided by the Internet Security Research Group. Let’s Encrypt offers basic SSL/TLS certificates for DNS hosts at no charge that you can use to add encryption-in-transit to a single web server. For commercial or multi-server configurations, you should consider AWS Certificate Manager and Elastic Load Balancing.
Let’s Encrypt also requires the certbot package, which you install from EPEL, the Extra Packaged for Enterprise Linux collection. Although EPEL is not included with Amazon Linux 2, I show how you can install it from the Fedora Project.
Walkthrough
At a high level, you perform the following tasks for this walkthrough:
Provision a VPC, Amazon Linux 2 instance, and LAMP stack.
Install and enable the EPEL repository.
Install and configure Let’s Encrypt.
Validate the installation.
Clean up.
Prerequisites and costs
To follow along with this walkthrough, you need the following:
Accept all other default values including with regard to storage.
Create a new security group and accept the default rule that allows TCP port 22 (SSH) from everywhere (0.0.0.0/0 in IPv4). For the purposes of this walkthrough, permitting access from all IP addresses is reasonable. In a production environment, you may restrict access to different addresses.
Allocate and associate an Elastic IP address to the server when it enters the running state.
Respond “Y” to all requests for approval to install the software.
Step 3: Install and configure Let’s Encrypt
If you are no longer connected to the Amazon Linux 2 instance, connect to it at the Elastic IP address that you just created.
Install certbot, the Let’s Encrypt client to be used to obtain an SSL/TLS certificate and install it into Apache.
sudo yum install python2-certbot-apache.noarch
Respond “Y” to all requests for approval to install the software. If you see a message appear about SELinux, you can safely ignore it. This is a known issue with the latest version of certbot.
Create a DNS “A record” that maps a host name to the Elastic IP address. For this post, assume that the name of the host is lamp.example.com. If you are hosting your DNS in Amazon Route 53, do this by creating the appropriate record set.
After the “A record” has propagated, browse to lamp.example.com. The Apache test page should appear. If the page does not appear, use a tool such as nslookup on your workstation to confirm that the DNS record has been properly configured.
You are now ready to install Let’s Encrypt. Let’s Encrypt does the following:
Confirms that you have control over the DNS domain being used, by having you create a DNS TXT record using the value that it provides.
Obtains an SSL/TLS certificate.
Modifies the Apache-related scripts to use the SSL/TLS certificate and redirects users browsing the site in HTTP mode to HTTPS mode.
Use the following command to install certbot:
sudo certbot -i apache -a manual \
--preferred-challenges dns -d lamp.example.com
The options have the following meanings:
-i apache Use the Apache installer.
-a manual Authenticate domain ownership manually.
--preferred-challenges dns Use DNS TXT records for authentication challenge.
-d lamp.example.com Specify the domain for the SSL/TLS certificate.
You are prompted for the following information: E-mail address for renewals? Enter an email address for certificate renewals. Accept the terms of services? Respond as appropriate. Send your e-mail address to the EFF? Respond as appropriate. Log your current IP address? Respond as appropriate.
You are prompted to deploy a DNS TXT record with the name “_acme-challenge.lamp.example.com” with the supplied value, as shown below.
After you enter the record, wait until the TXT record propagates. To look up the TXT record to confirm the deployment, use the nslookup command in a separate command window, as shown below. Remember to use the set ty=txt command before entering the TXT record. You are prompted to select a virtual host. There is only one, so choose 1. The final prompt asks whether to redirect HTTP traffic to HTTPS. To perform the redirection, choose 2. That completes the configuration of Let’s Encrypt.
Browse to the http:// lamp.example.com site. You are redirected to the SSL/TLS page https://lamp.example.com.
To look at the encryption information, use the appropriate actions within your browser. For example, in Firefox, you can open the padlock and traverse the menus. In the encryption technical details, you can see from the “Connection Encrypted” line that traffic to the website is now encrypted using TLS 1.2.
Security note: As of the time of publication, this website also supports TLS 1.0. I recommend that you disable this protocol because of some known vulnerabilities associated with it. To do this:
Edit the file /etc/letsencrypt/options-ssl-apache.conf.
Look for the line beginning with SSLProtocol and change it to the following:
SSLProtocol all -SSLv2 -SSLv3 -TLSv1
Save the file. After you make changes to this file, Let’s Encrypt no longer automatically updates it. Periodically check your log files for recommended updates to this file.
Restart the httpd server with the following command:
sudo service httpd restart
Step 5: Cleanup
Use the following steps to avoid incurring any further costs.
Terminate the Amazon Linux 2 instance that you created.
Release the Elastic IP address that you allocated.
Revert any DNS changes that you made, including the A and TXT records.
Conclusion
Amazon Linux 2 is an excellent option for hosting websites through the LAMP stack provided by the Amazon-Linux-Extras feature. You can then enhance the security of the Apache web server by installing EPEL and Let’s Encrypt. Let’s Encrypt provisions an SSL/TLS certificate, optionally installs it for you on the Apache server, and enables data-in-transit encryption. You can get started with Amazon Linux 2 in just a few clicks.
The EU’s General Data Protection Regulation (GDPR) describes data processor and data controller roles, and some customers and AWS Partner Network (APN) partners are asking how this affects the long-established AWS Shared Responsibility Model. I wanted to take some time to help folks understand shared responsibilities for us and for our customers in context of the GDPR.
How does the AWS Shared Responsibility Model change under GDPR? The short answer – it doesn’t. AWS is responsible for securing the underlying infrastructure that supports the cloud and the services provided; while customers and APN partners, acting either as data controllers or data processors, are responsible for any personal data they put in the cloud. The shared responsibility model illustrates the various responsibilities of AWS and our customers and APN partners, and the same separation of responsibility applies under the GDPR.
AWS responsibilities as a data processor
The GDPR does introduce specific regulation and responsibilities regarding data controllers and processors. When any AWS customer uses our services to process personal data, the controller is usually the AWS customer (and sometimes it is the AWS customer’s customer). However, in all of these cases, AWS is always the data processor in relation to this activity. This is because the customer is directing the processing of data through its interaction with the AWS service controls, and AWS is only executing customer directions. As a data processor, AWS is responsible for protecting the global infrastructure that runs all of our services. Controllers using AWS maintain control over data hosted on this infrastructure, including the security configuration controls for handling end-user content and personal data. Protecting this infrastructure, is our number one priority, and we invest heavily in third-party auditors to test our security controls and make any issues they find available to our customer base through AWS Artifact. Our ISO 27018 report is a good example, as it tests security controls that focus on protection of personal data in particular.
AWS has an increased responsibility for our managed services. Examples of managed services include Amazon DynamoDB, Amazon RDS, Amazon Redshift, Amazon Elastic MapReduce, and Amazon WorkSpaces. These services provide the scalability and flexibility of cloud-based resources with less operational overhead because we handle basic security tasks like guest operating system (OS) and database patching, firewall configuration, and disaster recovery. For most managed services, you only configure logical access controls and protect account credentials, while maintaining control and responsibility of any personal data.
Customer and APN partner responsibilities as data controllers — and how AWS Services can help
Our customers can act as data controllers or data processors within their AWS environment. As a data controller, the services you use may determine how you configure those services to help meet your GDPR compliance needs. For example, AWS Services that are classified as Infrastructure as a Service (IaaS), such as Amazon EC2, Amazon VPC, and Amazon S3, are under your control and require you to perform all routine security configuration and management that would be necessary no matter where the servers were located. With Amazon EC2 instances, you are responsible for managing: guest OS (including updates and security patches), application software or utilities installed on the instances, and the configuration of the AWS-provided firewall (called a security group).
To help you realize data protection by design principles under the GDPR when using our infrastructure, we recommend you protect AWS account credentials and set up individual user accounts with Amazon Identity and Access Management (IAM) so that each user is only given the permissions necessary to fulfill their job duties. We also recommend using multi-factor authentication (MFA) with each account, requiring the use of SSL/TLS to communicate with AWS resources, setting up API/user activity logging with AWS CloudTrail, and using AWS encryption solutions, along with all default security controls within AWS Services. You can also use advanced managed security services, such as Amazon Macie, which assists in discovering and securing personal data stored in Amazon S3.
For more information, you can download the AWS Security Best Practices whitepaper or visit the AWS Security Resources or GDPR Center webpages. In addition to our solutions and services, AWS APN partners can provide hundreds of tools and features to help you meet your security objectives, ranging from network security and configuration management to access control and data encryption.
A new PGP vulnerability was announced today. Basically, the vulnerability makes use of the fact that modern e-mail programs allow for embedded HTML objects. Essentially, if an attacker can intercept and modify a message in transit, he can insert code that sends the plaintext in a URL to a remote website. Very clever.
The EFAIL attacks exploit vulnerabilities in the OpenPGP and S/MIME standards to reveal the plaintext of encrypted emails. In a nutshell, EFAIL abuses active content of HTML emails, for example externally loaded images or styles, to exfiltrate plaintext through requested URLs. To create these exfiltration channels, the attacker first needs access to the encrypted emails, for example, by eavesdropping on network traffic, compromising email accounts, email servers, backup systems or client computers. The emails could even have been collected years ago.
The attacker changes an encrypted email in a particular way and sends this changed encrypted email to the victim. The victim’s email client decrypts the email and loads any external content, thus exfiltrating the plaintext to the attacker.
A few initial comments:
1. Being able to intercept and modify e-mails in transit is the sort of thing the NSA can do, but is hard for the average hacker. That being said, there are circumstances where someone can modify e-mails. I don’t mean to minimize the seriousness of this attack, but that is a consideration.
2. The vulnerability isn’t with PGP or S/MIME itself, but in the way they interact with modern e-mail programs. You can see this in the two suggested short-term mitigations: “No decryption in the e-mail client,” and “disable HTML rendering.”
3. I’ve been getting some weird press calls from reporters wanting to know if this demonstrates that e-mail encryption is impossible. No, this just demonstrates that programmers are human and vulnerabilities are inevitable. PGP almost certainly has fewer bugs than your average piece of software, but it’s not bug free.
3. Why is anyone using encrypted e-mail anymore, anyway? Reliably and easily encrypting e-mail is an insurmountably hard problem for reasons having nothing to do with today’s announcement. If you need to communicate securely, use Signal. If having Signal on your phone will arouse suspicion, use WhatsApp.
I’ll post other commentaries and analyses as I find them.
In our blog post on Tuesday, Cryptocurrency Security Challenges, we wrote about the two primary challenges faced by anyone interested in safely and profitably participating in the cryptocurrency economy: 1) make sure you’re dealing with reputable and ethical companies and services, and, 2) keep your cryptocurrency holdings safe and secure.
In this post, we’re going to focus on how to make sure you don’t lose any of your cryptocurrency holdings through accident, theft, or carelessness. You do that by backing up the keys needed to sell or trade your currencies.
$34 Billion in Lost Value
Of the 16.4 million bitcoins said to be in circulation in the middle of 2017, close to 3.8 million may have been lost because their owners no longer are able to claim their holdings. Based on today’s valuation, that could total as much as $34 billion dollars in lost value. And that’s just bitcoins. There are now over 1,500 different cryptocurrencies, and we don’t know how many of those have been misplaced or lost.
Now that some cryptocurrencies have reached (at least for now) staggering heights in value, it’s likely that owners will be more careful in keeping track of the keys needed to use their cryptocurrencies. For the ones already lost, however, the owners have been separated from their currencies just as surely as if they had thrown Benjamin Franklins and Grover Clevelands over the railing of a ship.
The Basics of Securing Your Cryptocurrencies
In our previous post, we reviewed how cryptocurrency keys work, and the common ways owners can keep track of them. A cryptocurrency owner needs two keys to use their currencies: a public key that can be shared with others is used to receive currency, and a private key that must be kept secure is used to spend or trade currency.
Many wallets and applications allow the user to require extra security to access them, such as a password, or iris, face, or thumb print scan. If one of these options is available in your wallets, take advantage of it. Beyond that, it’s essential to back up your wallet, either using the backup feature built into some applications and wallets, or manually backing up the data used by the wallet. When backing up, it’s a good idea to back up the entire wallet, as some wallets require additional private data to operate that might not be apparent.
No matter which backup method you use, it is important to back up often and have multiple backups, preferable in different locations. As with any valuable data, a 3-2-1 backup strategy is good to follow, which ensures that you’ll have a good backup copy if anything goes wrong with one or more copies of your data.
One more caveat, don’t reuse passwords. This applies to all of your accounts, but is especially important for something as critical as your finances. Don’t ever use the same password for more than one account. If security is breached on one of your accounts, someone could connect your name or ID with other accounts, and will attempt to use the password there, as well. Consider using a password manager such as LastPass or 1Password, which make creating and using complex and unique passwords easy no matter where you’re trying to sign in.
Approaches to Backing Up Your Cryptocurrency Keys
There are numerous ways to be sure your keys are backed up. Let’s take them one by one.
1. Automatic backups using a backup program
If you’re using a wallet program on your computer, for example, Bitcoin Core, it will store your keys, along with other information, in a file. For Bitcoin Core, that file is wallet.dat. Other currencies will use the same or a different file name and some give you the option to select a name for the wallet file.
To back up the wallet.dat or other wallet file, you might need to tell your backup program to explicitly back up that file. Users of Backblaze Backup don’t have to worry about configuring this, since by default, Backblaze Backup will back up all data files. You should determine where your particular cryptocurrency, wallet, or application stores your keys, and make sure the necessary file(s) are backed up if your backup program requires you to select which files are included in the backup.
Backblaze B2 is an option for those interested in low-cost and high security cloud storage of their cryptocurrency keys. Backblaze B2 supports 2-factor verification for account access, works with a number of apps that support automatic backups with encryption, error-recovery, and versioning, and offers an API and command-line interface (CLI), as well. The first 10GB of storage is free, which could be all one needs to store encrypted cryptocurrency keys.
2. Backing up by exporting keys to a file
Apps and wallets will let you export your keys from your app or wallet to a file. Once exported, your keys can be stored on a local drive, USB thumb drive, DAS, NAS, or in the cloud with any cloud storage or sync service you wish. Encrypting the file is strongly encouraged — more on that later. If you use 1Password or LastPass, or other secure notes program, you also could store your keys there.
3. Backing up by saving a mnemonic recovery seed
A mnemonic phrase, mnemonic recovery phrase, or mnemonic seed is a list of words that stores all the information needed to recover a cryptocurrency wallet. Many wallets will have the option to generate a mnemonic backup phrase, which can be written down on paper. If the user’s computer no longer works or their hard drive becomes corrupted, they can download the same wallet software again and use the mnemonic recovery phrase to restore their keys.
The phrase can be used by anyone to recover the keys, so it must be kept safe. Mnemonic phrases are an excellent way of backing up and storing cryptocurrency and so they are used by almost all wallets.
A mnemonic recovery seed is represented by a group of easy to remember words. For example:
The first four letters are enough to unambiguously identify the word.
Similar words are avoided (such as: build and built).
Bitcoin and most other cryptocurrencies such as Litecoin, Ethereum, and others use mnemonic seeds that are 12 to 24 words long. Other currencies might use different length seeds.
4. Physical backups — Paper, Metal
Some cryptocurrency holders believe that their backup, or even all their cryptocurrency account information, should be stored entirely separately from the internet to avoid any risk of their information being compromised through hacks, exploits, or leaks. This type of storage is called “cold storage.” One method of cold storage involves printing out the keys to a piece of paper and then erasing any record of the keys from all computer systems. The keys can be entered into a program from the paper when needed, or scanned from a QR code printed on the paper.
Printed public and private keys
Some who go to extremes suggest separating the mnemonic needed to access an account into individual pieces of paper and storing those pieces in different locations in the home or office, or even different geographical locations. Some say this is a bad idea since it could be possible to reconstruct the mnemonic from one or more pieces. How diligent you wish to be in protecting these codes is up to you.
Mnemonic recovery phrase booklet
There’s another option that could make you the envy of your friends. That’s the CryptoSteel wallet, which is a stainless steel metal case that comes with more than 250 stainless steel letter tiles engraved on each side. Codes and passwords are assembled manually from the supplied part-randomized set of tiles. Users are able to store up to 96 characters worth of confidential information. Cryptosteel claims to be fireproof, waterproof, and shock-proof.
Cryptosteel cold wallet
Of course, if you leave your Cryptosteel wallet in the pocket of a pair of ripped jeans that gets thrown out by the housekeeper, as happened to the character Russ Hanneman on the TV show Silicon Valley in last Sunday’s episode, then you’re out of luck. That fictional billionaire investor lost a USB drive with $300 million in cryptocoins. Let’s hope that doesn’t happen to you.
Encryption & Security
Whether you store your keys on your computer, an external disk, a USB drive, DAS, NAS, or in the cloud, you want to make sure that no one else can use those keys. The best way to handle that is to encrypt the backup.
With Backblaze Backup for Windows and Macintosh, your backups are encrypted in transmission to the cloud and on the backup server. Users have the option to add an additional level of security by adding a Personal Encryption Key (PEK), which secures their private key. Your cryptocurrency backup files are secure in the cloud. Using our web or mobile interface, previous versions of files can be accessed, as well.
Our object storage cloud offering, Backblaze B2, can be used with a variety of applications for Windows, Macintosh, and Linux. With B2, cryptocurrency users can choose whichever method of encryption they wish to use on their local computers and then upload their encrypted currency keys to the cloud. Depending on the client used, versioning and life-cycle rules can be applied to the stored files.
Other backup programs and systems provide some or all of these capabilities, as well. If you are backing up to a local drive, it is a good idea to encrypt the local backup, which is an option in some backup programs.
Address Security
Some experts recommend using a different address for each cryptocurrency transaction. Since the address is not the same as your wallet, this means that you are not creating a new wallet, but simply using a new identifier for people sending you cryptocurrency. Creating a new address is usually as easy as clicking a button in the wallet.
One of the chief advantages of using a different address for each transaction is anonymity. Each time you use an address, you put more information into the public ledger (blockchain) about where the currency came from or where it went. That means that over time, using the same address repeatedly could mean that someone could map your relationships, transactions, and incoming funds. The more you use that address, the more information someone can learn about you. For more on this topic, refer to Address reuse.
Note that a downside of using a paper wallet with a single key pair (type-0 non-deterministic wallet) is that it has the vulnerabilities listed above. Each transaction using that paper wallet will add to the public record of transactions associated with that address. Newer wallets, i.e. “deterministic” or those using mnemonic code words support multiple addresses and are now recommended.
There are other approaches to keeping your cryptocurrency transaction secure. Here are a couple of them.
Multi-signature
Multi-signature refers to requiring more than one key to authorize a transaction, much like requiring more than one key to open a safe. It is generally used to divide up responsibility for possession of cryptocurrency. Standard transactions could be called “single-signature transactions” because transfers require only one signature — from the owner of the private key associated with the currency address (public key). Some wallets and apps can be configured to require more than one signature, which means that a group of people, businesses, or other entities all must agree to trade in the cryptocurrencies.
Deep Cold Storage
Deep cold storage ensures the entire transaction process happens in an offline environment. There are typically three elements to deep cold storage.
First, the wallet and private key are generated offline, and the signing of transactions happens on a system not connected to the internet in any manner. This ensures it’s never exposed to a potentially compromised system or connection.
Second, details are secured with encryption to ensure that even if the wallet file ends up in the wrong hands, the information is protected.
Third, storage of the encrypted wallet file or paper wallet is generally at a location or facility that has restricted access, such as a safety deposit box at a bank.
Deep cold storage is used to safeguard a large individual cryptocurrency portfolio held for the long term, or for trustees holding cryptocurrency on behalf of others, and is possibly the safest method to ensure a crypto investment remains secure.
Keep Your Software Up to Date
You should always make sure that you are using the latest version of your app or wallet software, which includes important stability and security fixes. Installing updates for all other software on your computer or mobile device is also important to keep your wallet environment safer.
One Last Thing: Think About Your Testament
Your cryptocurrency funds can be lost forever if you don’t have a backup plan for your peers and family. If the location of your wallets or your passwords is not known by anyone when you are gone, there is no hope that your funds will ever be recovered. Taking a bit of time on these matters can make a huge difference.
To the Moon*
Are you comfortable with how you’re managing and backing up your cryptocurrency wallets and keys? Do you have a suggestion for keeping your cryptocurrencies safe that we missed above? Please let us know in the comments.
*To the Moon — Crypto slang for a currency that reaches an optimistic price projection.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easier to prepare and load your data for analytics. You can create and run an ETL job with a few clicks on the AWS Management Console. Just point AWS Glue to your data store. AWS Glue discovers your data and stores the associated metadata (for example, a table definition and schema) in the AWS Glue Data Catalog.
AWS Glue has native connectors to data sources using JDBC drivers, either on AWS or elsewhere, as long as there is IP connectivity. In this post, we demonstrate how to connect to data sources that are not natively supported in AWS Glue today. We walk through connecting to and running ETL jobs against two such data sources, IBM DB2 and SAP Sybase. However, you can use the same process with any other JDBC-accessible database.
AWS Glue data sources
AWS Glue natively supports the following data stores by using the JDBC protocol:
One of the fastest growing architectures deployed on AWS is the data lake. The ETL processes that are used to ingest, clean, transform, and structure data are critically important for this architecture. Having the flexibility to interoperate with a broader range of database engines allows for a quicker adoption of the data lake architecture.
For data sources that AWS Glue doesn’t natively support, such as IBM DB2, Pivotal Greenplum, SAP Sybase, or any other relational database management system (RDBMS), you can import custom database connectors from Amazon S3 into AWS Glue jobs. In this case, the connection to the data source must be made from the AWS Glue script to extract the data, rather than using AWS Glue connections. To learn more, see Providing Your Own Custom Scripts in the AWS Glue Developer Guide.
Setting up an ETL job for an IBM DB2 data source
The first example demonstrates how to connect the AWS Glue ETL job to an IBM DB2 instance, transform the data from the source, and store it in Apache Parquet format in Amazon S3. To successfully create the ETL job using an external JDBC driver, you must define the following:
The S3 location of the job script
The S3 location of the temporary directory
The S3 location of the JDBC driver
The S3 location of the Parquet data (output)
The IAM role for the job
By default, AWS Glue suggests bucket names for the scripts and the temporary directory using the following format:
Keep in mind that having the AWS Glue job and S3 buckets in the same AWS Region helps save on cross-Region data transfer fees. For this post, we will work in the US East (Ohio) Region (us-east-2).
Creating the IAM role
The next step is to set up the IAM role that the ETL job will use:
Sign in to the AWS Management Console, and search for IAM:
On the IAM console, choose Roles in the left navigation pane.
Choose Create role. The role type of trusted entity must be an AWS service, specifically AWS Glue.
Choose Next: Permissions.
Search for the AWSGlueServiceRole policy, and select it.
Search again, now for the SecretsManagerReadWrite This policy allows the AWS Glue job to access database credentials that are stored in AWS Secrets Manager.
CAUTION: This policy is open and is being used for testing purposes only. You should create a custom policy to narrow the access just to the secrets that you want to use in the ETL job.
Select this policy, and choose Next: Review.
Give your role a name, for example, GluePermissions, and confirm that both policies were selected.
Choose Create role.
Now that you have created the IAM role, it’s time to upload the JDBC driver to the defined location in Amazon S3. For this example, we will use the DB2 driver, which is available on the IBM Support site.
Storing database credentials
It is a best practice to store database credentials in a safe store. In this case, we use AWS Secrets Manager to securely store credentials. Follow these steps to create those credentials:
Open the console, and search for Secrets Manager.
In the AWS Secrets Manager console, choose Store a new secret.
Under Select a secret type, choose Other type of secrets.
In the Secret key/value, set one row for each of the following parameters:
db_username
db_password
db_url (for example, jdbc:db2://10.10.12.12:50000/SAMPLE)
db_table
driver_name (ibm.db2.jcc.DB2Driver)
output_bucket: (for example, aws-glue-data-output-1234567890-us-east-2/User)
Choose Next.
For Secret name, use DB2_Database_Connection_Info.
Choose Next.
Keep the Disable automatic rotation check box selected.
Choose Next.
Choose Store.
Adding a job in AWS Glue
The next step is to author the AWS Glue job, following these steps:
In the AWS Management Console, search for AWS Glue.
In the navigation pane on the left, choose Jobs under the ETL
Choose Add job.
Fill in the basic Job properties:
Give the job a name (for example, db2-job).
Choose the IAM role that you created previously (GluePermissions).
For This job runs, choose A new script to be authored by you.
For ETL language, choose Python.
In the Script libraries and job parameters section, choose the location of your JDBC driver for Dependent jars path.
Choose Next.
On the Connections page, choose Next
On the summary page, choose Save job and edit script. This creates the job and opens the script editor.
In the editor, replace the existing code with the following script. Important: Line 47 of the script corresponds to the mapping of the fields in the source table to the destination, dropping of the null fields to save space in the Parquet destination, and finally writing to Amazon S3 in Parquet format.
Choose the black X on the right side of the screen to close the editor.
Running the ETL job
Now that you have created the job, the next step is to execute it as follows:
On the Jobs page, select your new job. On the Action menu, choose Run job, and confirm that you want to run the job. Wait a few moments as it finishes the execution.
After the job shows as Succeeded, choose Logs to read the output of the job.
In the output of the job, you will find the result of executing the df.printSchema() and the message with the df.count().
Also, if you go to your output bucket in S3, you will find the Parquet result of the ETL job.
Using AWS Glue, you have created an ETL job that connects to an existing database using an external JDBC driver. It enables you to execute any transformation that you need.
Setting up an ETL job for an SAP Sybase data source
In this section, we describe how to create an AWS Glue ETL job against an SAP Sybase data source. The process mentioned in the previous section works for a Sybase data source with a few changes required in the job:
While creating the job, choose the correct jar for the JDBC dependency.
In the script, change the reference to the secret to be used from AWS Secrets Manager:
After you successfully execute the new ETL job, the output contains the same type of information that was generated with the DB2 data source.
Note that each of these JDBC drivers has its own nuances and different licensing terms that you should be aware of before using them.
Maximizing JDBC read parallelism
Something to keep in mind while working with big data sources is the memory consumption. In some cases, “Out of Memory” errors are generated when all the data is read into a single executor. One approach to optimize this is to rely on the parallelism on read that you can implement with Apache Spark and AWS Glue. To learn more, see the Apache Spark SQL module.
You can use the following options:
partitionColumn: The name of an integer column that is used for partitioning.
lowerBound: The minimum value of partitionColumn that is used to decide partition stride.
upperBound: The maximum value of partitionColumn that is used to decide partition stride.
numPartitions: The number of partitions. This, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions used to split the partitionColumn When unset, this defaults to SparkContext.defaultParallelism.
Those options specify the parallelism of the table read. lowerBound and upperBound decide the partition stride, but they don’t filter the rows in the table. Therefore, Spark partitions and returns all rows in the table. For example:
It’s important to be careful with the number of partitions because too many partitions could also result in Spark crashing your external database systems.
Conclusion
Using the process described in this post, you can connect to and run AWS Glue ETL jobs against any data source that can be reached using a JDBC driver. This includes new generations of common analytical databases like Greenplum and others.
You can improve the query efficiency of these datasets by using partitioning and pushdown predicates. For more information, see Managing Partitions for ETL Output in AWS Glue. This technique opens the door to moving data and feeding data lakes in hybrid environments.
Kapil Shardha is a Technical Account Manager and supports enterprise customers with their AWS adoption. He has background in infrastructure automation and DevOps.
William Torrealba is an AWS Solutions Architect supporting customers with their AWS adoption. He has background in Application Development, High Available Distributed Systems, Automation, and DevOps.
Most likely you’ve read the tantalizing stories of big gains from investing in cryptocurrencies. Someone who invested $1,000 into bitcoins five years ago would have over $85,000 in value now. Alternatively, someone who invested in bitcoins three months ago would have seen their investment lose 20% in value. Beyond the big price fluctuations, currency holders are possibly exposed to fraud, bad business practices, and even risk losing their holdings altogether if they are careless in keeping track of the all-important currency keys.
It’s certain that beyond the rewards and risks, cryptocurrencies are here to stay. We can’t ignore how they are changing the game for how money is handled between people and businesses.
Some Advantages of Cryptocurrency
Cryptocurrency is accessible to anyone.
Decentralization means the network operates on a user-to-user (or peer-to-peer) basis.
Transactions can completed for a fraction of the expense and time required to complete traditional asset transfers.
Transactions are digital and cannot be counterfeited or reversed arbitrarily by the sender, as with credit card charge-backs.
There aren’t usually transaction fees for cryptocurrency exchanges.
Cryptocurrency allows the cryptocurrency holder to send exactly what information is needed and no more to the merchant or recipient, even permitting anonymous transactions (for good or bad).
Cryptocurrency operates at the universal level and hence makes transactions easier internationally.
There is no other electronic cash system in which your account isn’t owned by someone else.
On top of all that, blockchain, the underlying technology behind cryptocurrencies, is already being applied to a variety of business needs and itself becoming a hot sector of the tech economy. Blockchain is bringing traceability and cost-effectiveness to supply-chain management — which also improves quality assurance in areas such as food, reducing errors and improving accounting accuracy, smart contracts that can be automatically validated, signed and enforced through a blockchain construct, the possibility of secure, online voting, and many others.
Like any new, booming marketing there are risks involved in these new currencies. Anyone venturing into this domain needs to have their eyes wide open. While the opportunities for making money are real, there are even more ways to lose money.
We’re going to cover two primary approaches to staying safe and avoiding fraud and loss when dealing with cryptocurrencies. The first is to thoroughly vet any person or company you’re dealing with to judge whether they are ethical and likely to succeed in their business segment. The second is keeping your critical cryptocurrency keys safe, which we’ll deal with in this and a subsequent post.
Caveat Emptor — Buyer Beware
The short history of cryptocurrency has already seen the demise of a number of companies that claimed to manage, mine, trade, or otherwise help their customers profit from cryptocurrency. Mt. Gox, GAW Miners, and OneCoin are just three of the many companies that disappeared with their users’ money. This is the traditional equivalent of your bank going out of business and zeroing out your checking account in the process.
That doesn’t happen with banks because of regulatory oversight. But with cryptocurrency, you need to take the time to investigate any company you use to manage or trade your currencies. How long have they been around? Who are their investors? Are they affiliated with any reputable financial institutions? What is the record of their founders and executive management? These are all important questions to consider when evaluating a company in this new space.
Would you give the keys to your house to a service or person you didn’t thoroughly know and trust? Some companies that enable you to buy and sell currencies online will routinely hold your currency keys, which gives them the ability to do anything they want with your holdings, including selling them and pocketing the proceeds if they wish.
That doesn’t mean you shouldn’t ever allow a company to keep your currency keys in escrow. It simply means that you better know with whom you’re doing business and if they’re trustworthy enough to be given that responsibility.
Keys To the Cryptocurrency Kingdom — Public and Private
If you’re an owner of cryptocurrency, you know how this all works. If you’re not, bear with me for a minute while I bring everyone up to speed.
Cryptocurrency has no physical manifestation, such as bills or coins. It exists purely as a computer record. And unlike currencies maintained by governments, such as the U.S. dollar, there is no central authority regulating its distribution and value. Cryptocurrencies use a technology called blockchain, which is a decentralized way of keeping track of transactions. There are many copies of a given blockchain, so no single central authority is needed to validate its authenticity or accuracy.
The validity of each cryptocurrency is determined by a blockchain. A blockchain is a continuously growing list of records, called “blocks”, which are linked and secured using cryptography. Blockchains by design are inherently resistant to modification of the data. They perform as an open, distributed ledger that can record transactions between two parties efficiently and in a verifiable, permanent way. A blockchain is typically managed by a peer-to-peer network collectively adhering to a protocol for validating new blocks. Once recorded, the data in any given block cannot be altered retroactively without the alteration of all subsequent blocks, which requires collusion of the network majority. On a scaled network, this level of collusion is impossible — making blockchain networks effectively immutable and trustworthy.
The other element common to all cryptocurrencies is their use of public and private keys, which are stored in the currency’s wallet. A cryptocurrency wallet stores the public and private “keys” or “addresses” that can be used to receive or spend the cryptocurrency. With the private key, it is possible to write in the public ledger (blockchain), effectively spending the associated cryptocurrency. With the public key, it is possible for others to send currency to the wallet.
Cryptocurrency “coins” can be lost if the owner loses the private keys needed to spend the currency they own. It’s as if the owner had lost a bank account number and had no way to verify their identity to the bank, or if they lost the U.S. dollars they had in their wallet. The assets are gone and unusable.
The Cryptocurrency Wallet
Given the importance of these keys, and lack of recourse if they are lost, it’s obviously very important to keep track of your keys.
If you’re being careful in choosing reputable exchanges, app developers, and other services with whom to trust your cryptocurrency, you’ve made a good start in keeping your investment secure. But if you’re careless in managing the keys to your bitcoins, ether, Litecoin, or other cryptocurrency, you might as well leave your money on a cafe tabletop and walk away.
What Are the Differences Between Hot and Cold Wallets?
Just like other numbers you might wish to keep track of — credit cards, account numbers, phone numbers, passphrases — cryptocurrency keys can be stored in a variety of ways. Those who use their currencies for day-to-day purchases most likely will want them handy in a smartphone app, hardware key, or debit card that can be used for purchases. These are called “hot” wallets. Some experts advise keeping the balances in these devices and apps to a minimal amount to avoid hacking or data loss. We typically don’t walk around with thousands of dollars in U.S. currency in our old-style wallets, so this is really a continuation of the same approach to managing spending money.
A “hot” wallet, the Bread mobile app
Some investors with large balances keep their keys in “cold” wallets, or “cold storage,” i.e. a device or location that is not connected online. If funds are needed for purchases, they can be transferred to a more easily used payment medium. Cold wallets can be hardware devices, USB drives, or even paper copies of your keys.
A “cold” wallet, the Trezor hardware wallet
A “cold” wallet, the Ledger Nano S
A “cold” Bitcoin paper wallet
Wallets are suited to holding one or more specific cryptocurrencies, and some people have multiple wallets for different currencies and different purposes.
A paper wallet is nothing other than a printed record of your public and private keys. Some prefer their records to be completely disconnected from the internet, and a piece of paper serves that need. Just like writing down an account password on paper, however, it’s essential to keep the paper secure to avoid giving someone the ability to freely access your funds.
How to Keep your Keys, and Cryptocurrency Secure
In a post this coming Thursday, Securing Your Cryptocurrency, we’ll discuss the best strategies for backing up your cryptocurrency so that your currencies don’t become part of the millions that have been lost. We’ll cover the common (and uncommon) approaches to backing up hot wallets, cold wallets, and using paper and metal solutions to keeping your keys safe.
In the meantime, please tell us of your experiences with cryptocurrencies — good and bad — and how you’ve dealt with the issue of cryptocurrency security.
Last month, Wired published a long article about Ray Ozzie and his supposed new scheme for adding a backdoor in encrypted devices. It’s a weird article. It paints Ozzie’s proposal as something that “attains the impossible” and “satisfies both law enforcement and privacy purists,” when (1) it’s barely a proposal, and (2) it’s essentially the same key escrow scheme we’ve been hearing about for decades.
Basically, each device has a unique public/private key pair and a secure processor. The public key goes into the processor and the device, and is used to encrypt whatever user key encrypts the data. The private key is stored in a secure database, available to law enforcement on demand. The only other trick is that for law enforcement to use that key, they have to put the device in some sort of irreversible recovery mode, which means it can never be used again. That’s basically it.
I have no idea why anyone is talking as if this were anything new. Severalcryptographershavealreadyexplained why this key escrow scheme is no better than any other key escrow scheme. The short answer is (1) we won’t be able to secure that database of backdoor keys, (2) we don’t know how to build the secure coprocessor the scheme requires, and (3) it solves none of the policy problems around the whole system. This is the typical mistake non-cryptographers make when they approach this problem: they think that the hard part is the cryptography to create the backdoor. That’s actually the easy part. The hard part is ensuring that it’s only used by the good guys, and there’s nothing in Ozzie’s proposal that addresses any of that.
I worry that this kind of thing is damaging in the long run. There should be some rule that any backdoor or key escrow proposal be a fully specified proposal, not just some cryptography and hand-waving notions about how it will be used in practice. And before it is analyzed and debated, it should have to satisfy some sort of basic security analysis. Otherwise, we’ll be swatting pseudo-proposals like this one, while those on the other side of this debate become increasingly convinced that it’s possible to design one of these things securely.
Already people are using the National Academies report on backdoors for law enforcement as evidence that engineers are developing workable and secure backdoors. Writing in Lawfare, Alan Z. Rozenshtein claims that the report — and a related New York Timesstory — “undermine the argument that secure third-party access systems are so implausible that it’s not even worth trying to develop them.” Susan Landau effectively corrects this misconception, but the damage is done.
Here’s the thing: it’s not hard to design and build a backdoor. What’s hard is building the systems — both technical and procedural — around them. Here’s Rob Graham:
He’s only solving the part we already know how to solve. He’s deliberately ignoring the stuff we don’t know how to solve. We know how to make backdoors, we just don’t know how to secure them.
A bunch of us cryptographers have already explained why we don’t think this sort of thing will work in the foreseeable future. We write:
Exceptional access would force Internet system developers to reverse “forward secrecy” design practices that seek to minimize the impact on user privacy when systems are breached. The complexity of today’s Internet environment, with millions of apps and globally connected services, means that new law enforcement requirements are likely to introduce unanticipated, hard to detect security flaws. Beyond these and other technical vulnerabilities, the prospect of globally deployed exceptional access systems raises difficult problems about how such an environment would be governed and how to ensure that such systems would respect human rights and the rule of law.
The reason so few of us are willing to bet on massive-scale key escrow systems is that we’ve thought about it and we don’t think it will work. We’ve looked at the threat model, the usage model, and the quality of hardware and software that exists today. Our informed opinion is that there’s no detection system for key theft, there’s no renewability system, HSMs are terrifically vulnerable (and the companies largely staffed with ex-intelligence employees), and insiders can be suborned. We’re not going to put the data of a few billion people on the line an environment where we believe with high probability that the system will fail.
Students taking Design of Mechatronics at the Technical University of Denmark have created some seriously elegant and striking Raspberry Pi speakers. Their builds are part of a project asking them to “explore, design and build a 3D printed speaker, around readily available electronics and components”.
The students have been uploading their designs, incorporating Raspberry Pis and HiFiBerry HATs, to Thingiverse throughout April. The task is a collaboration with luxury brand Bang & Olufsen’s Create initiative, and the results wouldn’t look out of place in a high-end showroom; I’d happily take any of these home.
Søren Qvist’s wall-mounted kitchen sphere uses 3D-printed and laser-cut parts, along with the HiFiBerry HAT and B&O speakers to create a sleek-looking design.
Otto Ømann’s group have designed the Hex One – a work-in-progress wireless 360° speaker. A particular objective for their project is to create a speaker using as many 3D-printed parts as possible.
“The design is supposed to resemble that of a B&O speaker, and from a handful of categories we chose to create a portable and wearable speaker,” explain Gustav Larsen and his team.
Oliver Repholtz Behrens and team have housed a Raspberry Pi and HiFiBerry HAT inside this this stylish airplay speaker. You can follow their design progress on their team blog.
Tue Thomsen’s six-person team Mechatastic have produced the B&O TILE. “The speaker consists of four 3D-printed cabinet and top parts, where the top should be covered by fabric,” they explain. “The speaker insides consists of laser-cut wood to hold the tweeter and driver and encase the Raspberry Pi.”
The team aimed to design a speaker that would be at home in a kitchen. With a removable upper casing allowing for a choice of colour, the TILE can be customised to fit particular tastes and colour schemes.
Build your own speakers with Raspberry Pis
Raspberry Pi’s onboard audio jack, along with third-party HATs such as the HiFiBerry and Pimoroni Speaker pHAT, make speaker design and fabrication with the Pi an interesting alternative to pre-made tech. These builds don’t tend to be technically complex, and they provide some lovely examples of tech-based projects that reflect makers’ own particular aesthetic style.
If you have access to a 3D printer or a laser cutter, perhaps at a nearby maker space, then those can be excellent resources, but fancy kit isn’t a requirement. Basic joinery and crafting with card or paper are just a couple of ways you can build things that are all your own, using familiar tools and materials. We think more people would enjoy getting hands-on with this sort of thing if they gave it a whirl, and we publish a free magazine to help.
Looking for a new project to build around the Raspberry Pi Zero, I came across the pHAT DAC from Pimoroni. This little add-on board adds audio playback capabilities to the Pi Zero. Because the pHAT uses the GPIO pins, the USB OTG port remains available for a wifi dongle.
This video by Frederick Vandenbosch is a great example of building AirPlay speakers using a Pi and HAT, and a quick search will find you lots more relevant tutorials and ideas.
Have you built your own? Share your speaker-based Pi builds with us in the comments.
If you store sensitive or confidential data in Amazon DynamoDB, you might want to encrypt that data as close as possible to its origin so your data is protected throughout its lifecycle.
You can use the DynamoDB Encryption Client to protect your table data before you send it to DynamoDB. Encrypting your sensitive data in transit and at rest helps assure that your plaintext data isn’t available to any third party, including AWS.
You don’t need to be a cryptography expert to use the DynamoDB Encryption Client. The encryption and signing elements are designed to work with your existing DynamoDB applications. After you create and configure the required components, the DynamoDB Encryption Client transparently encrypts and signs your table items when you call PutItem and verifies and decrypts them when you call GetItem.
You can create your own custom components, or use the basic implementations that are included in the library. We’ve made sure that the classes that we provide implement strong and secure cryptography.
You can use the DynamoDB Encryption Client with AWS Key Management Service (AWS KMS) or AWS CloudHSM, but the library doesn’t require AWS or any AWS service.
The DynamoDB Encryption Client is now available in Python, as well as Java. All supported language implementations are interoperable. For example, you can encrypt table data with the Python library and decrypt it with the Java library.
The DynamoDB Encryption Client is an open-source project. We hope that you will join us in developing the libraries and writing great documentation.
How it works
The DynamoDB Encryption Client processes one table item at a time. First, it encrypts the values (but not the names) of attributes that you specify. Then, it calculates a signature over the attributes that you specify, so you can detect unauthorized changes to the item as a whole, including adding or deleting attributes, or substituting one encrypted value for another.
However, attribute names, and the names and values in the primary key (the partition key and sort key, if one is provided) must remain in plaintext to make the item discoverable. They’re included in the signature by default.
Important: Do not put any sensitive data in the table name, attribute names, the names and values of the primary key attributes, or any attribute values that you tell the client not to encrypt.
How to use it
I’ll demonstrate how to use the DynamoDB Encryption Client in Python with a simple example. I’ll encrypt and sign one table item, and then add it to an existing table. This example uses a test item with arbitrary data, but you can use a similar procedure to protect a table item that contains highly sensitive data, such as a customer’s personal information.
I’ll start by creating a DynamoDB table resource that represents an existing table. If you use the code, be sure to supply a valid table name.
# Create a DynamoDB table
table = boto3.resource('dynamodb').Table(table_name)
Step 2: Create a cryptographic materials provider
Next, create an instance of a cryptographic materials provider (CMP). The CMP is the component that gathers the encryption and signing keys that are used to encrypt and sign your table items. The CMP also determines the encryption algorithms that are used and whether you create unique keys for every item or reuse them.
The DynamoDB Encryption Client includes several CMPs and you can create your own. And, if you’re in doubt, we help you to choose a CMP that fits your application and its security requirements.
In this example, I’ll use the Direct KMS Provider, which gets its cryptographic material from the AWS Key Management Service (AWS KMS). The encryption and signing keys that you use are protected by a customer master key in your AWS account that never leaves AWS KMS unencrypted.
To create a Direct KMS Provider, you specify an AWS KMS customer master key. Be sure to replace the fictitious customer master key ID (the value of aws-cmk-id) in this example with a valid one.
# Create a Direct KMS provider. Pass in a valid KMS customer master key.
aws_cmk_id = '1234abcd-12ab-34cd-56ef-1234567890ab'
aws_kms_cmp = AwsKmsCryptographicMaterialsProvider(key_id=aws_cmk_id)
Step 3: Create an attribute actions object
An attribute actions object tells the DynamoDB Encryption Client which item attribute values to encrypt and which attributes to include in the signature. The options are: ENCRYPT_AND_SIGN, SIGN_ONLY, and DO_NOTHING.
This sample attribute action encrypts and signs all attributes values except for the value of the test attribute; that attribute is neither encrypted nor included in the signature.
# Tell the encrypted table to encrypt and sign all attributes except one.
actions = AttributeActions(
default_action=CryptoAction.ENCRYPT_AND_SIGN,
attribute_actions={
'test': CryptoAction.DO_NOTHING
}
)
If you’re using a helper class, such as the EncryptedTable class that I use in the next step, you can’t specify an attribute action for the primary key. The helper classes make sure that the primary key is signed, but never encrypted (SIGN_ONLY).
Step 4: Create an encrypted table
Now I can use the original table object, along with the materials provider and attribute actions, to create an encrypted table.
# Use these objects to create an encrypted table resource.
encrypted_table = EncryptedTable(
table=table,
materials_provider=aws_kms_cmp,
attribute_actions=actions
)
In this example, I’m using the EncryptedTable helper class, which adds encryption features to the DynamoDB Table class in the AWS SDK for Python (Boto 3). The DynamoDB Encryption Client in Python also includes EncryptedClient and EncryptedResource helper classes.
The DynamoDB Encryption Client helper classes call the DescribeTable operation to find the primary key. The application that runs the code must have permission to call the operation.
We’re done configuring the client. Now, we can encrypt, sign, verify, and decrypt table items.
When we call the PutItem operation, the item is transparently encrypted and signed, except for the primary key, which is signed, but not encrypted, and the test attribute, which is ignored.
encrypted_table.put_item(Item=plaintext_item)
And, when we call the GetItem operation, the item is transparently verified and decrypted.
To view the encrypted item, call the GetItem operation on the original table object, instead of the encrypted_table object. It gets the item from the DynamoDB table without verifying and decrypting it.
Here’s an excerpt of the output that displays the encrypted item:
Figure 1: Output that displays the encrypted item
Client-side or server-side encryption?
The DynamoDB Encryption Client is designed for client-side encryption, where you encrypt your data before you send it to DynamoDB.
But, you have other options. DynamoDB supports encryption at rest, a server-side encryption option that transparently encrypts the data in your table whenever DynamoDB saves the table to disk. You can even use both the DynamoDB Encryption Client and encryption at rest together. The encrypted and signed items that the client generates are standard table items that have binary data in their attribute values. Your choice depends on the sensitivity of your data and the security requirements of your application.
Although the Java and Python versions of the DynamoDB Encryption Client are fully compatible, the DynamoDB Encryption Client isn’t compatible with other client-side encryption libraries, such as the AWS Encryption SDK or the S3 Encryption Client. You can’t encrypt data with one library and decrypt it with another. For data that you store in DynamoDB, we recommend the DynamoDB Encryption Client.
Encryption is crucial
Using tools like the DynamoDB Encryption Client helps you to protect your table data and comply with the security requirements for your application. We hope that you use the client and join us in developing it on GitHub.
If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on the AWS Key Management Service forum or contact AWS Support.
Want more AWS Security news? Follow us on Twitter.
SMS messaging is becoming an increasingly vital tool for companies in a variety of industries and across a diverse range of use cases. For example, many app developers use SMS messaging as part of their process for onboarding new customers. When new customers sign up for a service, they’re asked to provide their mobile phone numbers. The developer sends the customer a one-time password in an SMS message, which the customer then enters into a form on the web or in an app to complete the registration process. This capability is an important tool for ensuring the security of customers’ accounts. However, if the customer doesn’t receive the SMS message that contains the one-time password, he or she may become frustrated, and might abandon the registration process completely.
There are many things that could prevent an SMS message from arriving, but the most common causes are data entry errors. Apps and web forms typically only perform basic verification of phone numbers that end users provide. For example, they might check to make sure customers only entered numeric characters, or that the number contains the right number of digits. When customers enter their mobile numbers into an app or on a web form, they might accidentally enter their country code twice, or not enter a country code at all, or enter a leading zero in front of their phone number, or any of a variety of other common errors. In some cases, customers might even enter numbers that aren’t capable of receiving SMS messages, such as landline or Voice over IP (VoIP) numbers. Basic number validation techniques won’t stop any of these common errors from occurring. To help our customers find and correct these common issues, we’re launching a new feature in Amazon Pinpoint called Phone Number Verify.
With Phone Number Verify, Amazon Pinpoint checks to see whether the phone number provided is in a valid format based on its country code prefix. If the number is formatted correctly, Amazon Pinpoint leaves the number as the customer entered it. If the number isn’t formatted correctly, Amazon Pinpoint compares the phone number to various rules to make it valid. For example, if a customer enters a leading zero after the country code, Phone Number Verify removes the extra character to make the number valid. In this case, if the customer entered +1 0 206 555 0199 (a United States phone number in the 206 area code), Phone Number Verify changes the number to a correctly formatted number without the extra zero (+1 206 555 0199).
In addition to formatting numbers properly, Phone Number Verify can also detect and fix country-specific nuances. For example, in Brazil, older mobile phone numbers had eight digits. To create a larger pool of possible mobile phone numbers, Brazilian mobile companies added a ninth digit, and added a 9 to the beginning of the older eight digit numbers. If a customer provides a Brazilian mobile number that contains eight digits, Phone Number Verify will detect the issue and automatically insert the 9 in the appropriate place, between the area code and the phone number. In this example, Phone Number Verify would change +55 11 9123 4567 (a number in country code 55 and area code 11) to +55 11 99123 4567. By capturing and addressing these issues at the time of entry, Phone Number Verify can potentially increase the number of customers you’re able to contact. Our internal testing shows that up to 10% of mobile phone numbers contain these kinds of errors—that’s 10% of your potential customers that you might not be able to contact otherwise!
Phone Number Verify also returns metadata about phone numbers, such as the name of the telephone carrier, the type of phone number (landline, VoIP, mobile), and the geographic location (city, country, state and time zone) where the number is registered. Amazon Pinpoint users can use this metadata to perform additional validation. For example, if a user provides a landline number, you can immediately prompt the customer to enter a phone number that is capable of receiving text messages. Alternatively, when a customer provides a landline or VoIP number, you can call the user by using text-to-speech technology, rather than by sending a text message.
Phone Number Verify is now available in Amazon Pinpoint in a limited release. If you’re interested in testing this feature, complete our application form.
The collective thoughts of the interwebz
By continuing to use the site, you agree to the use of cookies. more information
The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.
