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codahale
sneaker
Go2015–2018
codahale / sneaker

sneaker

A tool for securely storing secrets on S3 using Amazon KMS.

8Distinct people
9Mentions
0Explicit recommenders
795GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A tool for securely storing secrets on S3 using Amazon KMS.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year9 dated mentions

Observed mentions: 2015-04-21 15:28:06 UTC to 2018-07-07 23:09:15 UTC.

012342015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC413
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC303
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101

What Hacker News says

9 sources
This write-up is solid - but man, this product looks questionable. 40 cents per secret per month? With Credstash[0] or a moral equivalent[1] you pay a buck for a KMS key and microcents for the data storage. RDS rotation is...fine, I guess, if you have an auditor who really wants that and can't write a scheduled job for the task (I've been using one with credstash so long it's just an automatic part of a new environment), but it's got me skeptical. Something AWS could do, and I'd be very interested in, is a hosted moral equivalent to Vault. Give me a daemon or something to run on an instance, allow me to IAM-gate temporary SSH credentials (and chuck it in CloudTrail) and temporary SQL databases, and that I'd pay for 'cause I really don't want to deal with Vault or HashiCorp. But AWS Secrets Manager, by itself, doesn't really present a good
Read the rest
In How to manage any kind of secret with AWS Secrets Manager
Not applicable for y'all, but for our AWS people, I'll cape up for Credstash[1] (or its moral equivalent, Sneaker[2], but I prefer the use of a Dynamo table to S3 for this). Uses IAM to ensure secret access and offers revisioning. Plus it's super easy to work with. My normal stack, using my own Auster[3] for orchestration, uses an offline, file-based secrets store (usually an encrypted USB key in production) for stuff like database root passwords that don't need to be online, then push database passwords into Credstash with encryption contexts (the KMS thing that makes IAM effective for this). My Chef cookbooks happily slurp in credstashed secrets via rcredstash, now that the PR to make it work with parameterized KMS keys has hit, and provisioning is very straightforward. (There are a lot of proper nouns in this paragraph, but the nice th
Read the rest
ing is that each component handles its own business and so there aren't many vertical concerns.) CI secret access isn't a thing in the systems I develop (unit tests don't need them, integration tests get a spun-up environment that provisions its own secrets), but you could provide access with a bog-standard token machine. [1] https://github.com/fugue/credstash [2] https://github.com/codahale/sneaker [3] https://github.com/eropple/auster
In Travis CI Security Advisory: Secured Environment Variables
We initially looked around, and here are a few alternatives: - Azure Key Vault: https://azure.microsoft.com/en-us/services/key-vault/ - Blackbox: https://github.com/StackExchange/blackbox - CredStash: https://github.com/fugue/credstash - Lyft Confydant: https://github.com/lyft/confidant - Trousseau: https://github.com/oleiade/trousseau - Sneaker: https://github.com/codahale/sneaker Some of these didn't exist when we were first investigating proper secret management, while others didn't fit as well with our deployment strategy. We're using what works when it makes sense - Blackbox is used in some repos, for instance - but I'll be sure the next time we have an internal doc like this that we cover why we didn't choose a different set of tools. One thing we liked about Vault is that it built upon our usage of Consul a
Read the rest
nd the http interface for Vault meant it was simple to plug into how we build and deploy services. While I'm sure some of these other tools would have had as good workflows, our experience in administrating Consul made it easier for us to have confidence in Vault.
In Secret Management with Vault
Encrypted S3 is definitely an option. The difficulty there is how to manage secrets that may be shared across services and how to ensure that there's no race conditions between updates of secrets. Confidant provides access to credentials by IAM role. The key here is that you can have credentials A, B, and C, and IAM roles example1-production, example2-production and example3-production, then map credentials A and B to example1-production, A and C to example2-production and A to example3-production. Confidant just stores mapping info for this. If you update A, you don't need to fan out an update to all three services. Race conditions can come in when A and B or C are updated at the same time. S3 is very eventually consistent and there's no locking. read-after-write consistency is only available in one region at this point. Of course, this
Read the rest
is all based on your assumptions and how you design your system. Based on our needs KMS + DynamoDB made more sense for us. Something like sneaker (https://github.com/codahale/sneaker) may fit your needs better. Another interesting bit about Confidant is that it manages the KMS grants on the auth KMS key, which lets you use the key from any service to any service to pass secrets, or to do general service to service auth. Also, there's a bit more coming down the road for automatic management of other common secrets that are annoying to manage in AWS, like SSH host keys for autoscale groups: https://github.com/lyft/confidant/issues/1
In Confidant: an open-source secret management service

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