Winner of the Best Book Bejtlich Read in 2009 award! "SQL injection is probably the number one problem for any server-side application, and this book is unequaled in its coverage." Richard Bejtlich, ...http://taosecurity.blogspot.com/ SQL injection represents one of the most dangerous and well-known, yet misunderstood, security vulnerabilities on the Internet, largely because there is no central repository of information to turn to for help. This is the only book devoted exclusively to this long-established but recently growing threat. It includes all the currently known information about these attacks and significant insight from its contributing team of SQL injection experts. * What is SQL injection?-Understand what it is and how it works * Find, confirm, and automate SQL injection discovery * Discover tips and tricks for finding SQL injection within the code * Create exploits using SQL injection * Design to avoid the dangers of these attacks
A key function of a software system is its ability to facilitate the manipulation of data, which is often implemented using a flavour of the Structured Query Language (SQL). To develop the data ...operations of software (i.e, creating, retrieving, updating, and deleting data), developers are required to excel in writing and combining both SQL and application code. The problem is that writing SQL code in itself is already challenging (e.g., SQL anti-patterns are commonplace) and combining SQL with application code (i.e., for SQL development tasks) is even more demanding. Meanwhile, we have little empirical understanding regarding the characteristics of SQL development tasks. Do SQL development tasks typically need more code changes? Do they typically have a longer time-to-completion? Answers to such questions would prepare the community for the potential challenges associated with such tasks. Our results obtained from 20 Apache projects reveal that SQL development tasks have a significantly longer time-to-completion than SQL-unrelated tasks and require significantly more code changes. Through our qualitative analyses, we observe that SQL development tasks require more spread out changes, effort in reviews and documentation. Our results also corroborate previous research highlighting the prevalence of SQL anti-patterns. The software engineering community should make provision for the peculiarities of SQL coding, in the delivery of safe and secure interactive software.
Computers are now involved in many economic transactions and can capture data associated with these transactions, which can then be manipulated and analyzed. Conventional statistical and econometric ...techniques such as regression often work well, but there are issues unique to big datasets that may require different tools. First, the sheer size of the data involved may require more powerful data manipulation tools. Second, we may have more potential predictors than appropriate for estimation, so we need to do some kind of variable selection. Third, large datasets may allow for more flexible relationships than simple linear models. Machine learning techniques such as decision trees, support vector machines, neural nets, deep learning, and so on may allow for more effective ways to model complex relationships. In this essay, I will describe a few of these tools for manipulating and analyzing big data. I believe that these methods have a lot to offer and should be more widely known and used by economists.
Cloud computing has revolutionized the way IT industries work. Most modern‐day companies rely on cloud services to accomplish their day‐to‐day tasks. From hosting websites to developing platforms and ...storing resources, cloud computing has tremendous use in the modern information technology industry. Although an emerging technique, it has many security challenges. In structured query language injection attacks, the attacker modifies some parts of the user query to still sensitive user information. This type of attack is challenging to detect and prevent. In this article, we have reviewed 65 research articles that address the issue of its prevention and detection in cloud and Traditional Networks, of which 11 research articles are related to general cloud attacks, and the rest of the 54 research articles are specifically on web security. Our result shows that Random Forest has an accuracy of 99.8% and a Precision rate of 99.9%, and the worst‐performing model is Multi‐Layer Perceptron (MLP) in the SQLIA Model. For recall value, Random Forest performs best while TensorFlow Linear Classifier performs worst. F1 score is best in Random Forest, while MLP is the most diminutive performer.
We present the ‘NoSQL Injection Dataset for MongoDB, a comprehensive collection of data obtained from diverse projects focusing on NoSQL attacks on MongoDB databases.
In the present era, we can ...classify databases into three main types: structured, semi-structured, and unstructured. While structured databases have played a prominent role in the past, unstructured databases like MongoDB are currently experiencing remarkable growth. Consequently, the vulnerabilities associated with these databases are also increasing. Hence, we have gathered a comprehensive dataset comprising 400 NoSQL injection commands. These commands are segregated into two categories: 221 malicious commands and 179 benign commands. The dataset was meticulously curated by combining both manually authored commands and those acquired through web scraping from reputable sources. The collected dataset serves as a valuable resource for studying and analysing NoSQL injection vulnerabilities, offering insights into potential security threats and aiding in the development of robust protection mechanisms against such attacks. The dataset includes a blend of complex and simple commands that have been enhanced. The dataset is well-suited for machine learning and data analysis, especially for security enthusiasts. The security professionals can use this dataset to train or fine tune the AI-models or LLMs in order to achieve higher attack detection accuracy. The security enthusiasts can also augment this dataset to generate more NoSQL commands and create robust security tools.
Resumen: Desde hace varios años y de acuerdo con el Open Web Application Security Project Foundation (OWASP), el riesgo de inyección SQL ha estado liderando el listado de los 10 principales riesgos ...en aplicaciones web, para lo cual se requiere llevar a cabo proyectos que permitan analizar sus algoritmos de ataque como mecanismo de protección. Abstract: For several years and according to the Open Web Application Security Foundation (OWASP), the risk of SQL injection has been leading the list of the top 10 risks in web applications, for which it is required to carry out projects that allow to analyze its attack algorithms as a protection mechanism. De acuerdo con la Open Web Application Security Project Foundation (OWASP, 2013, 2017, 2020), el principal riesgo de las aplicaciones web son las inyecciones, las cuales ocurren cuando datos no confiables son enviados a un intérprete como parte de un comando o una consulta. Id ="1 and (select 9223372036854775807+1 from employee where emp_id=i UNICODE(SUBSTRING(emp_description,i,i)) =65)" Con esta inyección SQL, en una base de datos MYSQL, se generará un error si el primer carácter del campo emp_description del emp_id elegido es igual al carácter 'A' (en UNICODE es el número 65).
•Describes an instructional approach and exercises to introduce a data analytics tool into a course covering relational databases and structured query language (SQL).•We position SQL as the mental ...model for learning the data preparation and data blending features of a popular analytics tool, Alteryx.•We split the traditional SQL content from our course into four increments that increase in complexity.•For each increment, we use a multi-step approach to first develop students’ mental model of the SQL query code and then apply the mental model to the new environment of Alteryx.
This paper describes an instructional approach and exercises to introduce a data analytics tool into an existing course that covers relational databases and structured query language (SQL). SQL and relational databases are traditional topics in many AIS classes and are frequently taught with established technologies such as Microsoft Access. With the onset of newer data analytics tools, educators are faced with the challenge of incorporating emerging technologies while still covering basic foundational concepts. In this paper, we position SQL as the mental model for learning the data preparation and data blending features of a popular analytics tool, Alteryx. We split the traditional SQL content from our course into four increments that increase in complexity. For each increment, we use a multi-step approach to first develop students’ mental model of the SQL query code and then apply the mental model to the new environment of Alteryx. For each increment, students solve the same set of problems in SQL and Alteryx, so that the understanding of SQL eases the transition to Alteryx, and the practice in Alteryx reinforces the understanding of SQL.
Speech-based inputs have been gaining significant momentum with the popularity of smartphones and tablets in our daily lives, since voice is the most popular and efficient way for human–computer ...interaction. This paper works toward designing more effective speech-based interfaces to query the structured data in relational databases. We first identify a new task named
Speech-to-SQL
, which aims to understand the information conveyed by human speech and directly translate it into structured query language (SQL) statements. A naive solution to this problem can work in a cascaded manner, that is, an automatic speech recognition component followed by a text-to-SQL component. However, it requires a high-quality ASR system and also suffers from the error compounding problem between the two components, resulting in limited performance. To handle these challenges, we propose a novel end-to-end neural architecture named
SpeechSQLNet
to directly translate human speech into SQL queries without an external ASR step. SpeechSQLNet has the advantage of making full use of the rich linguistic information presented in speech. To the best of our knowledge, this is the first attempt to directly synthesize SQL based on common natural language questions in spoken form, rather than a natural language-based version of SQL. To validate the effectiveness of the proposed problem and model, we further construct a dataset named
SpeechQL
, by piggybacking the widely used text-to-SQL datasets. Extensive experimental evaluations on this dataset show that SpeechSQLNet can directly synthesize high-quality SQL queries from human speech, outperforming various competitive counterparts as well as the cascaded methods in terms of exact match accuracies. We expect speech-to-SQL would inspire more research on more effective and efficient human–machine interfaces to lower the barrier of using relational databases.
Many intentionally vulnerable web applications are circulating on the Internet that serve as a legal test ground for practicing SQL injection attacks. For demonstration purposes the attacks will ...target an Acunetix test web application created using PHP programming language and MySQL relational database. In the practical part, the execution of the attack itself largely depends on the database management system, so the displayed syntax is intended only for the MySQL database management system. Example of an automated attack will be executed on SQLmap in a Linux Kali virtualized environment. Security guidelines with a purpose of protecting databases are also discussed.
Intelligent transportation is an emerging technology that integrates advanced sensors, network communication, data processing, and automatic control technologies to provide great convenience for our ...daily lives. With the increasing popularity of intelligent transportation, its security issues have also attracted much attention. SQL injection attack is one of the most common attacks in the intelligent transportation system. It has characteristics of various types, fast mutations, hidden attacks, etc., and leads to great harm. Most of the current SQL detection methods are based on manually defined features. The detection results are heavily dependent on the accuracy of feature extraction, so it cannot cope with the increasingly complex SQL injection attacks in the intelligent transportation system. In order to solve this problem, this paper proposes a long short-term memory based SQL injection attack detection method, which can automatically learn the effective representation of data, and has a strong advantage to confront with complex high-dimensional massive data. In addition, this paper proposes an injection sample generation method based on data transmission channel from the perspective of penetration. This method can formally model SQL injection attack and generate valid positive samples. It can effectively solve the over-fitting problem caused by insufficient positive samples. The experimental results show that the proposed method improves the accuracy of the SQL injection attack detection and reduces the false positive rate, which is better than several related classical machine learning algorithms and commonly used deep learning algorithms.