SQL Server Vulnerability Assessment Powershell Cmdlets

Ronit Reger announces a new set of SQL Server vulnerability assessment Powershell cmdlets:

SQL Vulnerability Assessment (VA) is a service that provides visibility into your security state, and includes actionable steps to resolve security issues, and enhance your database security. It can help you:

  • Meet compliance requirements that require database scan reports.
  • Meet data privacy standards.
  • Monitor a dynamic database environment where changes are difficult to track.

VA runs vulnerability scans on your database, flagging security vulnerabilities and highlight deviations from best practices, such as misconfigurations, excessive permissions, and unprotected sensitive data. The rules are based on Microsoft’s best practices and focus on the security issues that present the biggest risks to your database and its valuable data. These rules also represent many of the requirements from various regulatory bodies to meet their compliance standards.

Results of the scan include actionable steps to resolve each issue and provide customized remediation scripts where applicable. An assessment report can be customized for your environment by setting an acceptable baseline for permission configurations, feature configurations, and database settings. This baseline is then used as a basis for comparison in subsequent scans, to detect deviations or drifts from your secure database state.

Read on for more, and if you’re interested, the cmdlets are available in the SqlServer Powershell module.

Enabling LDAP Authentication On Cassandra

Kurt Greaves shows off a new LDAP authenticator for Apache Cassandra:

The LDAPAuthenticator is implemented using JNDI, and authentication requests will be made by Cassandra to the LDAP server using the username and password provided by the client. At this time only plain text authentication is supported.

If you configure a service LDAP user in the ldap.properties file, on startup Cassandra will authenticate the service user and create a corresponding role in the system_auth.roles table. This service user will then be used for future authentication requests received from clients. Alternatively (not recommended), if you have anonymous access enabled for your LDAP server, the authenticator allows authentication without a service user configured. The service user will be configured as a superuser role in Cassandra, and you will need to log in as the service user to define permissions for other users once they have authenticated.

The authenticator itself is hosted on GitHub, so you can check out its repo too.

Running SSMS As A Different Windows Account

Jason Brimhall shows a couple ways of running SQL Server Management Studio with different Active Directory credentials:

One of the tasks I find myself doing on a fairly regular basis is running SSMS as a different Windows User. The two biggest use cases for this are: a) to test an account to prove that it is working (or not) and has the appropriate level of access, and b) to use SSMS to connect to a Domain SQL Server from a computer in a different domain (or not on the domain).

In addition to needing to do these tasks for myself, I find that I need to show somebody else how to do the same thing on a fairly consistent basis. Considering the finite keystrokes we all have (which I referenced here), it is time for me to “document” how to do this task.

The “/netonly” command line parameter is one I’ve occasionally forgotten to my inevitable chagrin.

Alerting On Azure Data Lake Store Data Usage

Jose Lara shows off an interesting feature in Azure Data Lake Store:

The massive scale and capabilities of Azure Data Lake Store are regularly used by companies for big data storage. As the number of files, file types, and folders grow, things get harder to manage and staying compliant becomes a greater challenge for companies. Regulations such as GDPR (General Data Protection Regulation) have heightened requirements for control and supervision of files that contain sensitive data.

In this blog post, I’ll show you how to set up alerts in your Azure Data Lake Store to make managing your data easier. We will create a log analytics query and an alert that monitors a specific path and file type and sends a notification whenever the path or file is created, accessed, modified, or deleted.

Auditing access has historically been tricky, so it’s nice that they were able to get that in.

Data Protection Principles

K. Brian Kelley gives us an overview of what database security entails:

We have to be sure we know what accesses our data. There isn’t a technical solution that can automatically give us the answer. We can’t run a PowerShell script and know immediately everything that hits our key financial database. Over time we can collect that information, but the key word is “time.” If I look today, and today is not quarter end, then I don’t see the quarter end processes. If we’re looking at our HR related databases, then we really don’t know everything unless we also take into account the annual enrollment period.

The only way to be able to follow the principle of least privilege correctly is to know who and what access our data. This also includes ad hoc access, like folks running reports through SQL Server Reporting Services (SSRS) or doing analysis through Microsoft Excel. Therefore, in order to improve our data protection, we have to understand what accesses that data.

Obviously, documentation is required. When we have documentation there’s always the problem with keeping that documentation updated. While there are tools available, this task ultimately falls to people. Realistically, this is a battle we will always have to fight. Taking time to update documentation means we take time from other efforts. However, if we want to be serious about data protection, we have to know what accesses that data in order to be able to protect it.

It’s interesting to contrast this with Alex Yates’s essay on the topic.

Traditional Database Security Doesn’t Protect Data

Alex Yates has a controversial topic and some interesting thoughts:

Unfortunately, traditional database security has failed us.

Developers need access to the dev database to do their work. They need to be able to use appropriate test data to test their code. Traditional security features (logins, roles and users – even encryption technologies, dynamic data masking and row level security, etc) can be used to manage who has access to the data in production systems, but if a dev or test database already has the sensitive data these fundamental security features are worthless with regard to data protection. Even encrypted data only remains secure if the keys remain safe.

Sure, traditional security features protect the data in the production system – but not if it has already been copied to a less secure environment. And most people don’t track that with anywhere near as much rigor as they should.

To protect data effectively, we need to think much more consciously, not just about the production database, but also about all the other databases and backups that make up our database lifecycles, including dev and test systems and dev workstations. We need to know exactly where our security perimeter lies. Any copy of sensitive production data needs to live within the security perimeter and not outside it.

Read the whole article.

Granting Non-Admin Users Access To Run ML Services

Niels Berglund walks through the rights needed for a non-administrative user to execute an external script using SQL Server Machine Learning Services:

Oops, something did go wrong, as it turns out that if you try to grant permissions on extended stored procedures, which SPEES is, you need to do it from the master database. Cool, let us switch to master and do it there. Well, if you try to do that – then you get another error: the user does not exist in master, sigh!

At this stage you have a couple of options:

  • Add the login for the user to the sysadmin role, or the user to the db_owner role in the actual database. No do not do that, I am only kidding! Do.Not.Do.That!

  • Create the user in master and grant the permission. That would work.

  • Grant the permission to public.

Check it out, as there are two parts to the process.

Column-Level Security In Azure SQL Data Warehouse

Kavitha Jonnakuti announces a new feature for Azure SQL Data Warehouse:

Access to the table columns can be controlled based on the user’s execution context or their group membership with the standard GRANT T-SQL statement. To secure your data, you simply define a security policy via the GRANT statement to your table columns. For example, if you would like to limit access to PII data in your customers table, you can simply GRANT SELECT permissions on specific columns to the ContractEmp role:

GRANT SELECT ON dbo.Customers (CustomerId, FirstName, LastName) TO ContractEmp;

This capability is available now in all Azure regions with no additional charge.

This has been in regular SQL Server for a long time, so it’s good to see it make its way into Azure SQL Data Warehouse, and in a manner which doesn’t involve creating user-defined functions for predicates like Row-Level Security.

“Server Is Configured For Windows Authentication Only” Error

Kenneth Fisher diagnoses a misleading error:

In general, the errors SQL gives are highly useful. Of course every now and again you get one that’s just confounding. The other day I saw the following error in the log:

Login failed for user ”. Reason: An attempt to login using SQL authentication failed. Server is configured for Windows authentication only. [CLIENT: ]

This one confused me for a couple of reasons. First, the user ”. Why an empty user? That’s not really helpful. And second Server is configured for Windows authentication only.

But Kenneth shows that the server is configured for SQL authentication as well as Windows authentication.  Click through to see what gives.

Auditing Options With Azure SQL Data Warehouse

Janusz Rokicki explores what is available in Azure SQL Data Warehouse when it comes to auditing:

Auditing is disabled by default and the UI experience depends on the region to which the logical server is deployed. For instance, in UK South, the portal offers no options to manage auditing:

In North Europe, the portal allows Table Auditing (table-storage based) to be enabled on the SQL Data Warehouse scope, but it isn’t possible to enable Blob Auditing:

On top of that, Blob Auditing behaves differently when enabled on a logical server level in different regions. In locations that support Table Auditing, turning on Blob Auditing automatically enables it in all databases, including SQL Data Warehouses—and that’s expected. In other regions, Blob Auditing is not automatically enabled and has to be turned on programmatically by calling ARM REST API.

I imagine the plan is to support this across the board but it’s rolling out region by region.

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