The Redis SCAN command allows you to iterate over the key space. On a single Redis node you can SCAN all keys or just keys matching a pattern. It’s a slow operation: O(N) where N is the number of keys in the database. However, it can be useful when you want to view every item in the database or when there’s no way to find your values without traversing everything. Due to the way that Redis shards data though, it may be difficult to SCAN keys on a Redis Cluster. It is possible but it takes a little more work.
The Spring4Shell (CVE-2022-22965) critical severity vulnerability in Spring Framework allows remote code execution (RCE). At time of writing, it can be exploited only in very specific scenarios. However, Spring have made a patch available (Spring Framework version 5.3.18 and 5.2.20) and I strongly advise you to take them, even if you’re not running the exploitable setup.
The Spring Security PasswordEncoder interface exists to make it easy to safely encode passwords for storage in a database. Hashing the password using a secure algorithm with a heavy work factor will slow down an attacker even if they compromise the password database.
Since the interface was introduced, security recommendations have changed as CPUs / GPUs become more powerful and as vulnerabilities are discovered in legacy algorithms. The original StandardPasswordEncoder is now deprecated as the SHA-256 algorithm is considered insecure. Spring offers more secure implementations based on bcrypt, PBKDF2 and Argon2.
However, Spring no longer ties you to a single algorithm. The new DelegatingPasswordEncoder provides support for multiple PasswordEncoder implementations, many of which are available in Spring Boot applications with default configuration. This makes it possible to select an algorithm at run time and to have a database containing password hashes with different algorithms.
Spring WebClient is the reactive replacement for the legacy RestTemplate. It has a more modern fluent API and first class support for Reactive Streams. This means it supports non-blocking, asynchronous responses.
However, the reactive WebClient does not yet have the mature test support that RestTemplate now has. There is not yet a standard recipe to test Spring WebClient applications. No doubt support will be improved in future versions but for now, here’s what works for me.
In the previous post, we looked at how to build a three cluster Zookeeper ensemble. However, the ensemble was not secured in any way. This would allow unauthorised clients to query Zookeeper and to push data to znodes. It also allows unauthorised Zookeeper instances to join the ensemble and potentially even instruct the cluster to shut down.
Even in secured networks, it’s a good idea to use some of the security features available in Zookeeper. In this post we’ll look at two security mechanisms: mutual TLS (mTLS) and SASL authentication. We’ll set up these security features on the server-server communication (leader election protocols) and client-server communication (Kafta to Zookeeper).
Some notes on setting up and configuring a Zookeeper ensemble. Many guides use some shortcuts to setting up the ensemble such as running multiple Zookeeper instances on a single machine or running them in Docker. Both require some workarounds to make it work. As a better example, this guide runs three Zookeeper instances across three different VMs.
In the first two parts we built a bot using the Microsoft Bot Framework SDK and registered it in Azure. In this third and final part we’ll consume the bot using three of the available Bot Framework Channels: A simple chat component on a web page, SMS text and a fully custom Node.js application.
The Microsoft Bot Framework is a flexible framework for building conversational bots. A bot can be written once and deployed to multiple channels including webchat, Microsoft Teams, Alexa and SMS. It supports text, speech and rich GUIs with images and controls.
In this three part series, I’ll register a ‘hello world’ bot application as an Azure Bot Resource and then look at how to customise my bot behaviours. Finally I’ll make it available to a chat widget on a web page, SMS and consume it from a Node.js application.
In the first part, we created an Azure Bot registration and connected to a demo bot application. In this part we’ll swap out the demo bot for one we’ve built using the Microsoft Bot Framework SDK.
The Microsoft Bot Framework is a flexible framework for building conversational bots. A bot can be written once and deployed to multiple channels including webchat, Microsoft Teams, Alexa and SMS. It supports text, speech and rich GUIs with images and controls.
In this three part series, I’ll register a ‘hello world’ bot application as an Azure Bot Resource and then look at how to customise my bot behaviours. Finally I’ll make it available to a chat widget on a web page, SMS and consume it from a Node.js application.
In this part, I’ll register and configure a bot with Microsoft Azure Bot Service. It might seem odd to start here rather than going straight into the application code. However, getting this step out of the way gives us something simple to play with that works end to end.