1,773 research outputs found
DeepSQLi: Deep Semantic Learning for Testing SQL Injection
Security is unarguably the most serious concern for Web applications, to
which SQL injection (SQLi) attack is one of the most devastating attacks.
Automatically testing SQLi vulnerabilities is of ultimate importance, yet is
unfortunately far from trivial to implement. This is because the existence of a
huge, or potentially infinite, number of variants and semantic possibilities of
SQL leading to SQLi attacks on various Web applications. In this paper, we
propose a deep natural language processing based tool, dubbed DeepSQLi, to
generate test cases for detecting SQLi vulnerabilities. Through adopting deep
learning based neural language model and sequence of words prediction, DeepSQLi
is equipped with the ability to learn the semantic knowledge embedded in SQLi
attacks, allowing it to translate user inputs (or a test case) into a new test
case, which is semantically related and potentially more sophisticated.
Experiments are conducted to compare DeepSQLi with SQLmap, a state-of-the-art
SQLi testing automation tool, on six real-world Web applications that are of
different scales, characteristics and domains. Empirical results demonstrate
the effectiveness and the remarkable superiority of DeepSQLi over SQLmap, such
that more SQLi vulnerabilities can be identified by using a less number of test
cases, whilst running much faster
Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces
Embedded devices are becoming more widespread, interconnected, and
web-enabled than ever. However, recent studies showed that these devices are
far from being secure. Moreover, many embedded systems rely on web interfaces
for user interaction or administration. Unfortunately, web security is known to
be difficult, and therefore the web interfaces of embedded systems represent a
considerable attack surface.
In this paper, we present the first fully automated framework that applies
dynamic firmware analysis techniques to achieve, in a scalable manner,
automated vulnerability discovery within embedded firmware images. We apply our
framework to study the security of embedded web interfaces running in
Commercial Off-The-Shelf (COTS) embedded devices, such as routers, DSL/cable
modems, VoIP phones, IP/CCTV cameras. We introduce a methodology and implement
a scalable framework for discovery of vulnerabilities in embedded web
interfaces regardless of the vendor, device, or architecture. To achieve this
goal, our framework performs full system emulation to achieve the execution of
firmware images in a software-only environment, i.e., without involving any
physical embedded devices. Then, we analyze the web interfaces within the
firmware using both static and dynamic tools. We also present some interesting
case-studies, and discuss the main challenges associated with the dynamic
analysis of firmware images and their web interfaces and network services. The
observations we make in this paper shed light on an important aspect of
embedded devices which was not previously studied at a large scale.
We validate our framework by testing it on 1925 firmware images from 54
different vendors. We discover important vulnerabilities in 185 firmware
images, affecting nearly a quarter of vendors in our dataset. These
experimental results demonstrate the effectiveness of our approach
The approaches to quantify web application security scanners quality: A review
The web application security scanner is a computer program that assessed web application security with penetration testing technique. The benefit of automated web application penetration testing is huge, which web application security scanner not only reduced the time, cost, and resource required for web application penetration testing but also eliminate test engineer reliance on human knowledge. Nevertheless, web application security scanners are possessing weaknesses of low test coverage, and the scanners are generating inaccurate test results. Consequently, experimentations are frequently held to quantitatively quantify web application security scanner's quality to investigate the web application security scanner's strengths and limitations. However, there is a discovery that neither a standard methodology nor criterion is available for quantifying the web application security scanner's quality. Hence, in this paper systematic review is conducted and analysed the methodology and criterion used for quantifying web application security scanners' quality. In this survey, the experiment methodologies and criterions that had been used to quantify web application security scanner's quality is classified and review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. The objectives are to provide practitioners with the understanding of methodologies and criterions that available for measuring web application security scanners' test coverage, attack coverage, and vulnerability detection rate, while provides the critical hint for development of the next testing framework, model, methodology, or criterions, to measure web application security scanner quality
Web Security Detection Tool
According to Government Computer News (GCN) web attacks have been marked as all- time high this year. GCN says that some of the leading security software like SOPHOS detected about 15,000 newly infected web pages daily in initial three months of 2008 [13]. This has lead to the need of efficient software to make web applications robust and sustainable to these attacks. While finding information on different types of attacks, I found that SQL injection and cross site scripting are the most famous among attackers. These attacks are used extensively since, they can be performed using different techniques and it is difficult to make a web application completely immune to these attacks. There are myriad detection tools available which help to detect vulnerabilities in web applications. These tools are mainly categorized as white-box and black-box testing tools. In this writing project, we aim to develop a detection tool which would be efficient and helpful for the users to pinpoint possible vulnerabilities in his/her PHP scripts. We propose a technique to integrate the aforementioned categories of tools under one framework to achieve better detection against possible vulnerabilities. Our system focuses on giving the developer a simple and concise tool which would help him/her to correct possible loopholes in the PHP code snippets
SQL Injection Detection Using Machine Learning Techniques and Multiple Data Sources
SQL Injection continues to be one of the most damaging security exploits in terms of personal information exposure as well as monetary loss. Injection attacks are the number one vulnerability in the most recent OWASP Top 10 report, and the number of these attacks continues to increase. Traditional defense strategies often involve static, signature-based IDS (Intrusion Detection System) rules which are mostly effective only against previously observed attacks but not unknown, or zero-day, attacks. Much current research involves the use of machine learning techniques, which are able to detect unknown attacks, but depending on the algorithm can be costly in terms of performance. In addition, most current intrusion detection strategies involve collection of traffic coming into the web application either from a network device or from the web application host, while other strategies collect data from the database server logs. In this project, we are collecting traffic from two points: the web application host, and a Datiphy appliance node located between the webapp host and the associated MySQL database server. In our analysis of these two datasets, and another dataset that is correlated between the two, we have been able to demonstrate that accuracy obtained with the correlated dataset using algorithms such as rule-based and decision tree are nearly the same as those with a neural network algorithm, but with greatly improved performance
A detailed survey on various aspects of SQL injection in web applications: vulnerabilities, innovative attacks and remedies
In today’s world, Web applications play a very important role in individual life as well as in any country’s development. Web applications have gone through a very rapid growth in the recent years and their adoption is moving faster than that was expected few years ago. Now-a-days, billions of transactions are done online with the aid of different Web applications. Though these applications are used by hundreds of people, in many cases the security level is weak, which makes them vulnerable to get compromised. In most of the scenarios, a user has to be identified before any communication is established with the backend database. An arbitrary user should not be allowed access to the system without proof of valid credentials. However, a crafted injection gives access to unauthorized users. This is mostly accomplished via SQL Injection input. In spite of the development of different approaches to prevent SQL injection, it still remains an alarming threat to Web applications. In this paper, we present a detailed survey on various types of SQL Injection vulnerabilities, attacks, and their prevention techniques. Alongside presenting our findings from the study, we also note down future expectations and possible development of countermeasures against SQL Injection attacks
A Detailed Survey on Various Aspects of SQL Injection in Web Applications: Vulnerabilities, Innovative Attacks, and Remedies
In today’s world, Web applications play a very important role in individual life as well as in any country’s development. Web applications have gone through a very rapid growth in the recent years and their adoption is moving faster than that was expected few years ago. Now-a-days, billions of transactions are done online with the aid of different Web applications. Though these applications are used by hundreds of people, in many cases the security level is weak, which makes them vulnerable to get compromised. In most of the scenarios, a user has to be identified before any communication is established with the backend database. An arbitrary user should not be allowed access to the system without proof of valid credentials. However, a crafted injection gives access to unauthorized users. This is mostly accomplished via SQL Injection input. In spite of the development of different approaches to prevent SQL injection, it still remains an alarming threat to Web applications. In this paper, we present a detailed survey on various types of SQL Injection vulnerabilities, attacks, and their prevention techniques. Alongside presenting our findings from the study, we also note down future expectations and possible development of countermeasures against SQL Injection attacks
An empirical comparison of commercial and open‐source web vulnerability scanners
Web vulnerability scanners (WVSs) are tools that can detect security vulnerabilities in web services. Although both commercial and open-source WVSs exist, their vulnerability detection capability and performance vary. In this article, we report on a comparative study to determine the vulnerability detection capabilities of eight WVSs (both open and commercial) using two vulnerable web applications: WebGoat and Damn vulnerable web application. The eight WVSs studied were: Acunetix; HP WebInspect; IBM AppScan; OWASP ZAP; Skipfish; Arachni; Vega; and Iron WASP. The performance was evaluated using multiple evaluation metrics: precision; recall; Youden index; OWASP web benchmark evaluation; and the web application security scanner evaluation criteria. The experimental results show that, while the commercial scanners are effective in detecting security vulnerabilities, some open-source scanners (such as ZAP and Skipfish) can also be effective. In summary, this study recommends improving the vulnerability detection capabilities of both the open-source and commercial scanners to enhance code coverage and the detection rate, and to reduce the number of false-positives
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