In this article, we are going to learn about the db_datareader role. It is a fixed, database-level role. The database-level roles are a group of security principals that are used to manage the permissions within the databases more efficiently. There are two types of database-level roles. One is a predefined database-level role, and another is custom database-level roles. The custom database-level roles can be created by the database administrator or the member of the db_owner role.
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It is the 30th article in the SQL Server Always On Availability Groups series and explores column-level SQL Server encryption with AG groups.
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As tracking behavioral data becomes increasingly popular, firms may overlook areas where they can collect the same information while data masking details that can be used in a compromise. Behavioral data collection can be extremely dangerous as it allows attackers a wide range of attacks, from spoofing targets to automating custom attacks on targets. Since behavior can reveal key details about us, this information may be as costly as private identifiable information. When tracking behavioral data, we want to weigh risks, and, in some cases, we can accomplish the same result without specific details. In other cases, we may want to mask specific behavioral information on reports that are generated, even if we retain the specific time. We’ll look at a method where we can accomplish either – updating data to remove time or data masking specific time while returning the information we want.
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When we develop security testing within inconsistent data volume situations, we should consider our use of anti-malware applications that use behavioral analysis. Many of these applications are designed to catch and flag unusual behavior. This may help prevent attacks, but it may also cause ETL flows to be disrupted, potentially disrupting our customers or clients. While we may have a consistent flow of data throughout a time period – allowing for a normal window of behavior to occur – we may also have an inconsistent data schedule or inconsistent amount of data that cause these applications to flag files, directories, or the process itself.
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When we create an environment and consider our security testing from development to production and how changes are deployed throughout each environment, we want to consider what we’re protecting and how much resources we’ll devote to this protection. Every company has limited resources, so protecting against all possible threats will not be something we can achieve.
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In this article, we’ll look at using the built-in PWDCOMPARE function in SQL Server for security testing passwords. While this tool may seem like it exposes a weakness in Microsoft SQL Server because we can test for passwords, it should be of note that an attacker could do the same attack by attempting to login to our database server assuming the attacker was able to access a connection to it. Therefore, this function does not increase the risk of an attack on SQL Server but does help us identify possible weaknesses in our environment so that we can quickly mitigate these risks. In addition, we’ll also combine this with other related tools in SQL Server to help us with logins.
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Analyzing data with Power BI has always been fascinating to me. With ever-growing data comes more risk, and hence more security is needed. In this article, I am going to introduce what row-level security in Power BI is and how does it work. I’ll also demonstrate in detail how to implement the same in Power BI Desktop. Later, we will also discuss how to implement this row-level security in Power BI service as well. To learn about row-level security in SQL Server, please have a look at my previous article, where I have explained how to implement the same.
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In this article, I’m going to discuss Row-Level Security in SQL Server. RLS or Row-Level Security as the name suggests is a security mechanism that restricts the records from a SQL Server table based on the authorization context of the current user that is logged in. This means the records from the tables are displayed based on who the user is and to which records do the user has access to. This is usually done to allow specific users to have access to their data only without permission to view other users’ data.
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This article gives an overview of column level SQL Server encryption using examples.
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This article explores the Python scripts for encrypting and decrypting passwords in SQL Server using Azure Data Studio SQL Notebooks.
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A SQL injection attack is one of the most commonly used hacking techniques. It allows hacks to access information from a database that is otherwise not publically accessible.
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Security has been one of the prime concerns of database developers since the inception of database management systems. Various data protection schemes have been introduced to provide secure access to sensitive data.
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This article explores a method to enforce SSL for all connections in AWS RDS SQL Server.
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In this article, we will un-riddle the ways to make use of the data definition language trigger (DDL Trigger), in order to monitor the progressions made to the database programming objects, View, Procedure or Function with a few real-time examples.
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This article portrays the different utilization of database DDL Triggers for the Tables with a counting mail alert on schema composition using DDL (Data Definition Language) standard. Using that efficient method we can keep close eyes on monitoring schema changes in any database of SQL Server. We’ll also see how we could monitor these movements and send an alert email to persons responsible to inform about this change.
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In this article, we will review how to recover SA password by starting SQL Server in single user mode when you forget “sa” credentials or lose the access to the instances due to the following reasons:
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This article speaks to, how to copy SQL Logins on the new server with Server Level roles and database-level permissions as existing Source to Destination SQL Server instance using a script.
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This article contains the SQL Server login Authentication scope on the Security side. We will find the subtleties, how Login Authentication extension can be controlled SQL Server level Logon trigger.
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With an understanding of what SQL injection is and why it is important to an organization, we can shift into a discussion of how to prevent it. We ultimately want systems where SQL injection is impossible or very difficult to pull off. We then want systems where exploiting bugs is slow, laborious, and likely to raise monitoring alarms within an organization when attempted. The trio of layered security, prevention, and alerting can provide an immense advantage against not only SQL injection, but other data security threats.
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Many security vulnerabilities are discovered, patched, and go away forever. Some linger and continue to plague software development and will continue to do so for years to come. Setting aside social engineering and non-technical attacks, SQL injection remains one of the top security threats to our data, as well as one of the most misunderstood.
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In today’s time where data breaches are highly expected to happen, there is a high need to ensure sensitive data in the Azure SQL databases is secured and which is why data security implementation is gaining momentum across each community. We covered one of the features of Advanced Data Security here in Advanced Data Security in Azure SQL Database – Data Discovery & Classification. Let’s dive further into the other two features that Azure SQL offers with this capability in this article.
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Azure SQL supports in building and managing wide range of SQL databases, tools, frameworks etc. on the cloud. Organizations are drifting towards Azure SQL because of its obvious advantages over on-premises SQL Server and are generating, exchanging and storing data at an exponential rate on Azure. It becomes essential to safeguard, monitor our sensitive data and get alerts on anomalous activities else companies may come under fire for letting data leak and hacked.
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Certificate Management in SQL Server 2019 has been enhanced a lot when compared with previous versions of SQL Server, and it is part of a large set of new features and enhancements in SQL Server 2019. The most significant enhancement is that that it now allows you to directly import SSL/TLS certificates into SQL Server, thus simplifying the entire process a lot.
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We’ve looked at both the organization and development side of managing Azure costs. One risk we have is attackers who compromise an account and mis-scale resources (such as scaling up), driving up our costs. Another scenario is attackers scaling resources too low that affects client’s ability to do their work (performance problems) – a separate risk that may result in lower costs on the cloud side, but higher costs against our reputation. A third risk is reconnaissance of our Azure use: this allows the attackers to get information about our design and later make a wide range of attacks that will appear as normal to us – in this case, Azure costs may be only one of the impacts with other impacts being as severe.
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Azure costs can quickly mount, without careful supervision and management. This article will detail cost mitigation strategies using security and design
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