We have expired or expiring SQL TDE certificates! What now?
Well, the first thing we do is not panic. Even if our TDE certificate expires it won’t cause any issues. The SQL Server will continue to work normally. Even if we restore the DB elsewhere using the expired certificate we will just get a warning that the certificate is expired.
A warning is nice, and the system still working let’s us breathe a little easier, but we know that an updated certificate is a much better thing to have. In fact, setting up a regular key rotation schedule is even better and a recommended practice.
Good information, and Chris shares scripts to make it easy.
With the addition of Databricks runtime 5.1 which was released December 2018, comes the ability to use Azure AD credential pass-through. This is a huge step forward since there is no longer a need to control user permissions through Databricks Groups / Bash and then assigning these groups access to secrets to access Data Lake at runtime. As mentioned previously – with the lack of support for AAD within Databricks currently, ACL activities were done on an individual basis which was not ideal. By using this feature, you can now pass the authentication onto Data Lake, and as we know one of the advantages of Data Lake is the tight integration into Active Directory so this simplifies things. Its worth noting that this feature is currently in public preview but having tested it thoroughly, am happy with the implementation/limitations. The feature also requires a premium workspace and only works with high concurrency clusters – both of which you’d expect to use in this scenario.
It looks like this is the way to go forward with securing Azure Databricks. Read the whole thing.
You’ll notice that as part of this I’m retrieving the secrets/GUIDS I need for the connection from somewhere else – namely the Databricks-backed secrets store. This avoids exposing those secrets in plain text in your notebook – again this would not be ideal. The secret access is then based on an ACL (access control list) so I can only connect to Data Lake if I’m granted access into the secrets. While it is also possible to connect Databricks up to the Azure Key Vault and use this for secrets store instead, when I tried to configure this I was denied based on permissions. After research I was unable to overcome the issue. This would be more ideal to use but unfortunately there is limited support currently and the fact the error message contained spelling mistakes suggests to me the functionality is not yet mature.
To be charitable, there appears to be room for implementation improvement.
While this file path serves as a useful location for us to load flat files, we should consider that the user account that is executing the underlying insert statement must be able to read (and possibly write to) that file location. The writing part of the equation comes in when it involves logging, even if the permissions of the written logging data are tied down strictly in the output, in that the user doesn’t control what gets written, but that errors are written. In the least, we want to ensure that a separate folder with strict permissions exists for any flat file import to restrict the account access – notice that we’re not reading off the root drive, as we’ve seen that we can insert an entire file of data – think about using SQL bulk insert to view files through SQL Server by inserting the file’s data and reviewing it.
It’s more than just “check the box for the server-level role.”
Once upon a time, I was in the position of trying to figure out why a job failed. After a bunch of digging and troubleshooting, it was discovered that the job had changed but nobody knew when or why. Because of that, I was asked to provide a low cost audit solution to try and at least provide answers to the when and who of the change.
Tracking who made a change to an agent job should be a task added to each database professionals checklist / toolbox. Being caught off guard from a change to a system under your purview isn’t necessarily a fun conversation – nor is it pleasant to be the one to find that somebody changed your jobs without notice – two weeks after the fact! Usually, that means that there is little to no information about the change and you find yourself getting frustrated.
Click through to see how Jason does it.
My second concern was twofold. Is the chapter about A Least Privilege Model Implementation Using Windows PowerShell published in the PowerShell Conference Book impacted by this change? Should I stop deploying Windows 10 at work because the LCU of January 2019 breaks my loopback scenario?
The answer is no and explained by the blog post Windows Security change affecting PowerShell
you would not be affected by this change, unless you explicitly set up loopback endpoints on your machine to allow non-Administrator account access
Read on for some testing and digging into what works when and why.
Once we run the above T-SQL query, any account that is part of the sysadmin role in the SQL Server instance has the ability to run the xp_cmdshell extended stored procedure. On the background, when the user with sysadmin privileges runs the xp_cmdshell, it will execute the Windows command shell using the SQL Server Service Account (So if you are executing xp_cmdshell to access certain resource on the network, for example, and you are having permission issue, you might want to make sure that the SQL Server Service Account has permission to that resource).
Now, what if you have a non-sysadmin account that needs to run xp_cmdshell? In order to do that, we would need to do some additional configuration.
Granting non-sysadmins rights to run xp_cmdshell definitely rates as well above-average in terms of risk. I don’t have any problem with xp_cmdshell being turned on—especially considering that by default, only sysadmin accounts get it and sysadmin accounts can turn it on if it’s disabled, meaning it’s effectively always on for sysadmin. But when you start granting non-sysadmin accounts the ability to shell out, you have to be even more careful of protecting that SQL Server instance.
This means that I could have multiple email accounts that I have to use in order to sign into the portal. Using a password manager such as 1Password, not usually a big deal and more of an annoyance rather than a headache.
Within the past month or so, Microsoft has updated the portal to allow me to easily switch accounts. Previously you had to log out of the portal and then log back in.
This is quite convenient. Prior to this change, switching to a different account could goof with other sites I had open (like if I was sending an Outlook e-mail through one account, switching the Azure Portal signed-in account would log me out from Outlook). It’s still not a perfect experience but it’s a lot better.
The only operation SQL Server 2016 and 2017 support on encrypted database columns is equality comparison, providing you use deterministic encryption. For anything else, your apps need to download the data to perform the computations outside of the database. Similarly, if you need to encrypt your data for the first time or re-encrypt it later (e.g. to rotate your keys), you need to use special tools that move the data and perform crypto operations on a different machine than your SQL Server computer. These restrictions are not an issue if equality comparison is all your applications need and if the tables containing your sensitive data are small. However, many types of sensitive information, e.g. a person’s name or phone number, often require richer operations, including pattern matching and sorting, and it’s not uncommon for sensitive data to be too large to move outside of the database for processing.
To address the above challenges, Always Encrypted in SQL Server 2019 is enhanced with secure enclaves. A secure enclave is a protected region of memory that appears as a black box to the containing process and to other processes running on the machine, including the operating system. There is no way to view the data or code inside the enclave from the outside, which makes enclaves ideal for processing sensitive data. There are several enclave technologies that differ in how enclave isolation is accomplished. SQL Server 2019 preview uses a Windows Server technology called Virtualization Based Security (VBS), which relies on Hypervisor to protect and isolate enclaves.
They’re going further with Always Encrypted than I thought would be possible. The first release of Always Encrypted had me asking “Why would I use this over running an encryption or decryption function in my app code?” I think secure enclaves starts to answer that question.
In this post, we’ll discuss how to prevent or mitigate compromise of credentials due to certain classes of vulnerabilities such as Server Side Request Forgery (SSRF) and XML External Entity (XXE) injection. If an attacker has remote code execution (RCE) or local presence on the AWS server, these methods discussed will not prevent compromise. For more information on how the AWS services mentioned work, see the Background section at the end of this post.
Protecting Your Credentials
There are many ways that you can protect your AWS temporary credentials. The two methods covered here are:
Enforcing where API calls are allowed to originate from.
Protecting the EC2 Metadata service so that credentials cannot be retrieved via a vulnerability in an application such as Server Side Request Forgery (SSRF).
Read the whole thing if you’re an AWS user.