Hash deploy review

Since that time, this paper has taken on a life of its own In the earlys, when the commercial Internet was still young! Many thoiught that increased security provided comfort to paranoid people while most computer professionals realized that security provided some very basic protections that we all needed? Cryptography for the masses barely existed at that time and was certainly not a topic of common discourse. Security and privacy impacts many applications, ranging from secure commerce and payments to private communications and protecting health care information.



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WATCH RELATED VIDEO: Review of Blue Dream Bubble Hash by NuEra

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There are tons of options out there for deploying websites, but my default approach for years has been: dump it in an S3 bucket with CloudFront in front. There's a big assumption and scope narrowing here: that the website needs to be basically static, perhaps connecting to external APIs for dynamic behavior when needed.

For many low-write-volume websites, it doesn't take a ton of effort to make that assumption a good one. You might be saying "Hey! You're just describing Jamstack in a needlessly roundabout way! My experience with this kind of architecture has been that scalability concerns, along with many performance concerns, basically go away in this scenario. There can certainly be issues with site performance from the end user's perspective due to any number of JavaScript, image loading, or API connectivity issues—but in terms of backend server health, we just don't worry about it.

Of course there are lots of projects for which this sort of architecture is more trouble than it's worth, but that's why this is a "default" instead of a "thing I always do. I wanted to be able to try out those features straight from the Github PR review page: click a link, and right away I'm seeing a preview of the changes.

What would it take to wire up a feature like that ourselves? In this post, we'll take a look at the required bits and pieces that let us create static site deploy previews on AWS. I want to say up front that I don't think any of this approach is original: lots of other folks have blogged about similar approaches. It's also not even my recommendation that you choose this mechanism for your own static site deployments: for many use cases, dedicated services like the ones above and others!

So you don't actually have to do this yourself. That said, we learn a lot by digging into the details of useful features, so if nothing else this has been a great learning process for me. And depending on the tradeoffs and requirements in your unique situation, this might turn out to be a decent approach for you. The overall goal here is that when a PR is opened, we can see a preview site to evaluate before it goes live.

And then when we merge the PR to the main branch, the site gets deployed to production. We had an additional wrinkle in our setup, wiring up previews to be built when CMS changes were published. We'll save the story here for another time, but suffice to say that once the right build triggers were in place for PRs, we didn't need massive effort to wire in the CMS.

One natural approach might be to deploy each new site preview into a totally new and distinct S3 bucket, and point CloudFront at that new bucket. We did something like this for a previous version of the site, without a "preview site" feature: each new deployment would go in a new bucket. We had a couple of annoyances with this approach. First, there's an AWS limit on the number of S3 buckets per account.

The number of buckets grows over time as new deploys are made, so after enough deploys, we'd run out of available buckets on the AWS account. We could contact AWS support and get that limit raised, but it didn't seem worth it.

Regardless of the number, it's a limit we'd hit eventually and need to deal with. For that version of the site, our workaround was to manually delete old buckets once we hit the limit. This wasn't super-painful or super-frequent, but it was an annoyance we wanted to avoid.

Also, it took CloudFront like 20 minutes to update when we pointed it at the new S3 bucket. Since then, that wait time has gone way down , impressively so. Those two issues led us down a path of exploration: could we always deploy to the same S3 bucket for this use case? To do that, what would need to be in place?

An immediate idea here was to use "directory" prefixes, e. This was appealing because all preview sites go in the same bucket, but problematic because the way S3 static sites work means that our URLs when we visit the website would need that long, noisy path appended to them, and we don't want that noise in the URL. Because we're using CloudFront in front of the bucket, we had a nifty solution available to us. We could use custom subdomains to access the preview site e. Something like this:.

Our Terraform for this looks something like:. This means a request for Note that this is not a redirect, which would round-trip back to the client with a 3xx-level response. Instead, the request comes into this Lambda Edge function, and is passed along to the S3 bucket after that rewrite. Lambda Edge is kind of nifty—my mental model is effectively that it lets us run custom code on CloudFront. The pricing is higher than normal Lambda as you'd expect , and the language choices are more limited, but it's a pretty neat tool.

For this use case, we weren't too worried about this incrementally higher cost about 3x higher than regular Lambda, as of today , because these preview sites get visited so rarely. One gotcha with these Lambda Edge functions is making sure you know when this code ought to be running—should it process the request or the response?

Should it always execute, or only conditionally depending on whether or not the request is in CloudFront's cache? If you're going down this road, I definitely recommend reading up on the various CloudFront events that you'll need to pick for your function. The Lambda itself we also deployed with Terraform, which was straightforward after making sure that the runtime was allowed for Lambda Edge. The Terraform for these is noisier than I think would be helpful to show in code here, but hopefully that gives you enough flavor for what's involved.

There's one remaining problem with this URL-rewriting idea—have you spotted it already? What happens when the S3 website responds with a redirect? Well, because CloudFront has done that rewrite to use a path instead of a subdomain, as far as S3 knows, the requester knows about these paths, so its redirect looks just like the above. The user in their browser, on the other hand, gets redirected from their original request, Instead, we can use another one of the CloudFront events, "Origin Response", and write another Lambda Edge function to handle it:.

Because of this Lambda Edge machinery, we've got a situation where our preview environments do look different than the production environment. The production site doesn't have the Lambda Edge rewrites, and so perhaps we could have a bug that snuck in that only surfaces in the absence of such rewrites.

I can't think of a way this could happen, but also can't rule it out. This wouldn't have been too bad to implement—likely some build-time script that took the code SHA and injected it into the site's configuration file somehow. That would've presented the tradeoff that, as we previewed the site, we'd be looking at different paths than the production site. I'm not convinced either of these options is better than the other, but having this rewriting live purely in infrastructure made me think there might be less that could go wrong when it came time to go to production.

I'm satisfied that these tradeoffs are worth it, but I think it's important to be clear-eyed about the downsides you're accepting with big tech choices. There's not too much that's fancy about deploying to an S3 bucket. But there's a caveat worth noting. Gary Bernhardt gave a great summary of a race condition during deployment remember, web applications are distributed systems!

Web apps with hashes in asset filenames have this problem: 1. A deploy starts. A browser starts loading a page. The deploy finishes. The browser requests assets referenced by the page. Those assets no longer exist due to the deploy. The solution we went with is very similar to Gary's: use the CI provider's cache. Like Gary, I like the minimal infrastructure this adds basically none. But I should point out that there's an edge case where, if the CI provider's cache goes missing normally a totally fine thing to happen to a cache , some previously existing assets will go missing in the new deploy.

For our use case this is totally fine, but I can imagine scenarios where it would be more annoying. At any rate, after making sure to preserve pre-existing assets, we perform two AWS S3 sync operations for two different kinds of files.

Our static site generator appends SHA hashes to many of the files it builds e. CSS, JavaScript, and image assets so that, if any of the content of those files were to be updated, the newly generated files would include a different hash as part of the filename at build time.

And any files that reference the asset files most notably HTML, but often CSS as well are generated to include those hashes when referencing the assets. In this way, we can pretty easily identify which files in the build are immutable, because they have this pattern in the filename.

It's not foolproof, since someone could theoretically name a non-hashed file with this pattern, but it's correct by convention and works for our purposes. One gotcha here is that when deploying to the preview bucket, we need to deploy to a given prefix, the Git SHA of our codebase.

In order to automate any given feature, it's nice to be able to do the thing manually first. So once we have a script that can perform a deploy, then we can worry about triggering that thing. So CircleCI runs the deploys, using its aws-s3 orb , after running through most of our tests.

Some other tests need to wait until after the deployment, so we can run them against the deployed code. There's a bit of a gotcha here: we'd like to only deploy for pull requests, and we want preview deploys to go out when pull requests are opened. This way, any given build we run on CircleCI that isn't connected to a pull request will stop before trying to deploy.

The second part is a bit trickier, surprisingly-to-me. Our experience is that CircleCI would kick off a build from our Github repo on git push , but that a new build wouldn't be triggered when a PR was opened. This means that if we push a branch up, our previous circleci step halt would prevent a deploy preview from going out. And then when we open a PR for that same branch, there's no rebuild step as far as CircleCI is concerned, because the push event has already been processed.

It might look like a good solution here to just go ahead and do deploy previews for every git push , but a sticking point there is that we want the PR to have a link displayed. In order to solve all these issues, we've ended up with a bit of a roundabout solution that works reasonably well:. It'd be nice if this Lambda and API Gateway weren't required, because it feels like indirection that shouldn't be necessary.

I'm sure there are ways around this, using other CI providers or perhaps a Github app. But regardless of the ugliness, this seems to work reasonably well for us.

Besides, we ended up with another use case for which a webhook triggering a CircleCI build was useful: publishing deploys from our headless CMS. But that's a story for another day.



App security best practices

Try out PMC Labs and tell us what you think. Learn More. The sudden development of the COVID pandemic has exposed the limitations in modern healthcare systems to handle public health emergencies. It is evident that adopting innovative technologies such as blockchain can help in effective planning operations and resource deployments. Blockchain technology can play an important role in the healthcare sector, such as improved clinical trial data management by reducing delays in regulatory approvals, and streamline the communication between diverse stakeholders of the supply chain, etc. Moreover, the spread of misinformation has intensely increased during the outbreak, and existing platforms lack the ability to validate the authenticity of data, leading to public panic and irrational behavior. Thus, developing a blockchain-based tracking system is important to ensure that the information received by the public and government agencies is reliable and trustworthy.

The bitcoin blockchain is a public ledger that records bitcoin transactions. It is implemented as a chain of blocks, each block containing a hash of the.

Security code review

On an increasingly frequent basis during internal infrastructure penetration testing engagements, the Triskele Labs Ethical Hacking Team is finding that protections for traditional extraction of credentials from host memory are maturing. Gone are the days where a Mimikatz binary could be dropped to perform this task, and going are the days where these attacks can be executed remotely from memory, thanks to inbuilt Windows protections and security product protections. As such, new methods are required to achieve this goal while bypassing these protections. In this blog post, we discuss a relatively new technique discovered by Elad Shamir called the Internal Monologue attack. Elad has also published a tool written in C to provide a Proof of Concept for how this attack can be utilised. During an internal penetration test , after gaining privileged access to an internal system, a penetration tester will generally proceed to extract passwords from memory. T o overcome this , a tester who has gained privileged access on a victim host can simply dump the LSASS file from the system either directly from memory or by running a trusted Microsoft tool such as ProcDump. Nowadays many organisation s are deploy ing solution s to detect and restrict the dumping of LSASS process or execution of the ProcDump tool.


Introduction to Microsoft Defender for Storage

hash deploy review

There are tons of options out there for deploying websites, but my default approach for years has been: dump it in an S3 bucket with CloudFront in front. There's a big assumption and scope narrowing here: that the website needs to be basically static, perhaps connecting to external APIs for dynamic behavior when needed. For many low-write-volume websites, it doesn't take a ton of effort to make that assumption a good one. You might be saying "Hey!

Its blockchain, the history of all its transactions , was under attack.

It seems that your browser is not supported by our application.

The Deployment Rule Set feature is optional and shall only be used internally in an organization with a controlled environment. If a JAR file that contains a rule set is distributed or made available publicly, then the certificate used to sign the rule set will be blacklisted and blocked in Java. Overview of Deployment Rule Sets. Create the Rule Set. Packaging the Rule Set.


The Internal Monologue Attack – NTLM Hash Extraction

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Instead of adding code to the script tag, create a SHA hash of the script As a stepping stone to a complete deployment, you can ask the.

This topic includes a list of important product changes in Tableau Server, beginning with version The changes described in this topic may impact the upgrade process itself, or they may impact functionality after you have upgraded. Read these changes carefully and make note of the changes and remediation steps that you'll need to take. Include these remediation steps as part of your upgrade process or post-upgrade configuration plan.


These documentation pages are no longer current. They remain available for archival purposes. The Deployment Rule Set feature is for enterprises that manage their Java desktop environment directly, and provides a way for enterprises to continue using legacy business applications in an environment of ever-tightening Java applet and Java Web Start application security policies. To protect the user and minimize the possibility that a RIA was compromised, security checks are performed when a RIA is started, and the user is prompted for permission to run the RIA.

DestinationRule defines policies that apply to traffic intended for a service after routing has occurred.

To enable controllers to interoperate with third-party access points in the future. The following are some guidelines that you must follow for access point communication protocols:. If access control lists ACLs are in the control path between the controller and its access points, you need to open new protocol ports to prevent access points from being stranded. Rate-limiting is applicable to all traffic destined to the CPU from either direction wireless or wired. We recommend that you always run the controller with the default config advanced rate enable command in effect to rate limit traffic to the controller and protect against denial-of-service DoS attacks. You can use the config advanced rate disable command to stop rate-limiting of Internet Control Message Protocol ICMP echo responses for testing purposes. However, we recommend that you reapply the config advanced rate enable command after testing is complete.

Use deliver to submit your app for App Store review. The guide will create all the necessary files for you, using the existing app metadata from App Store Connect. From now on, you can run fastlane deliver to deploy a new update, or just upload new app metadata and screenshots. Check out your local.


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