The Exploit Database is a CVE compliant archive of public exploits and corresponding vulnerable software, developed for use by penetration testers and vulnerability researchers. Our aim is to serve the most comprehensive collection of exploits gathered through direct submissions, mailing lists, as well as other public sources, and present them in a freely-available and easy-to-navigate database. The Exploit Database is a repository for exploits and proof-of-concepts rather than advisories, making it a valuable resource for those who need actionable data right away.
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SAS (previously "Statistical Analysis System")[1] is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation,[2] and predictive analytics.
SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it.[3] SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.[3]
The DATA step has executable statements that result in the software taking an action, and declarative statements that provide instructions to read a data set or alter the data's appearance.[4] The DATA step has two phases: compilation and execution. In the compilation phase, declarative statements are processed and syntax errors are identified. Afterwards, the execution phase processes each executable statement sequentially.[6] Data sets are organized into tables with rows called "observations" and columns called "variables". Additionally, each piece of data has a descriptor and a value.[4][7]
The development of SAS began in 1966 after North Carolina State University re-hired Anthony Barr[15] to program his analysis of variance and regression software so that it would run on IBM System/360 computers.[16] The project was funded by the National Institutes of Health.[17] and was originally intended to analyze agricultural data[12][18] to improve crop yields.[19] Barr was joined by student James Goodnight, who developed the software's statistical routines, and the two became project leaders.[15][16][20] In 1968, Barr and Goodnight integrated new multiple regression and analysis of variance routines.[21][22] In 1972, after issuing the first release of SAS, the project lost its funding.[17] According to Goodnight, this was because NIH only wanted to fund projects with medical applications.[23] Goodnight continued teaching at the university for a salary of $1 and access to mainframe computers for use with the project,[17] until it was funded by the University Statisticians of the Southern Experiment Stations the following year.[16][23] John Sall joined the project in 1973 and contributed to the software's econometrics, time series, and matrix algebra. Another early participant, Caroll G. Perkins, contributed to SAS' early programming. Jolayne W. Service and Jane T. Helwig created SAS' first documentation.[21]
SAS version 4 had limited features, but made SAS more accessible. Version 5 introduced a complete macro language, array subscripts, and a full-screen interactive user interface called Display Manager.[24] In 1985, SAS was rewritten in the C programming language. This allowed for the SAS' Multivendor Architecture that allows the software to run on UNIX, MS-DOS, and Windows. It was previously written in PL/I, Fortran, and assembly language.[20][24]
In 2002, the Text Miner software was introduced. Text Miner analyzes text data like emails for patterns in business intelligence applications.[40] In 2004, SAS Version 9.0 was released, which was dubbed "Project Mercury" and was designed to make SAS accessible to a broader range of business users.[41][42] Version 9.0 added custom user interfaces based on the user's role and established the point-and-click user interface of SAS Enterprise Guide as the software's primary graphical user interface (GUI).[41] The Customer Relationship Management (CRM) features were improved in 2004 with SAS Interaction Management.[43] In 2008 SAS announced Project Unity, designed to integrate data quality, data integration and master data management.[44]
A free version was introduced for students in 2010.[47] SAS Social Media Analytics, a tool for social media monitoring, engagement and sentiment analysis, was also released that year.[48][49] SAS Rapid Predictive Modeler (RPM), which creates basic analytical models using Microsoft Excel, was introduced that same year.[49][50] JMP 9 in 2010 added a new interface for using the R programming language from JMP and an add-in for Excel.[51][52] The following year, a High Performance Computing appliance was made available in a partnership with Teradata and EMC Greenplum.[53][54] In 2011, the company released Enterprise Miner 7.1.[55] The company introduced 27 data management products from October 2013 to October 2014 and updates to 160 others.[56] At the 2015 SAS Global Forum, it announced several new products that were specialized for different industries, as well as new training software.[57]
SAS' products for monitoring and managing the operations of IT systems are collectively referred to as SAS IT Management Solutions.[67] SAS collects data from various IT assets on performance and utilization, then creates reports and analyses.[68] SAS' Performance Management products consolidate and provide graphical displays for key performance indicators (KPIs) at the employee, department and organizational level.[69][70] The SAS Supply Chain Intelligence product suite is offered for supply chain needs, such as forecasting product demand, managing distribution and inventory and optimizing pricing.[71] There is also a "SAS for Sustainability Management" set of software to forecast environmental, social and economic effects and identify causal relationships between operations and an impact on the environment or ecosystem.[72]
According to IDC, SAS is the largest market-share holder in "advanced analytics" with 35.4 percent of the market as of 2013.[81] It is the fifth largest market-share holder for business intelligence (BI) software with a 6.9% share[82] and the largest independent vendor. It competes in the BI market against conglomerates, such as SAP BusinessObjects, IBM Cognos, SPSS Modeler, Oracle Hyperion, and Microsoft Power BI.[83] SAS has been named in the Gartner Leader's Quadrant for Data Integration Tool and for Business Intelligence and Analytical Platforms.[84]A study published in 2011 in BMC Health Services Research found that SAS was used in 42.6 percent of data analyses in health service research, based on a sample of 1,139 articles drawn from three journals.[85]
Disassembling or debugging commercial programs is usually prohibited by international laws. When practicing reversing and when we need to study a kind of software protection, reverse engineers usually make some stand alone applications which implement only the protection, in other words it simulates the behavior of a software protection, nothing more nothing less!
We are here in front of a very basic protection type; just before the address 00404402 (before the beginning of passing parameters to the first message box) we can see curious CALL, TEST and JNZ (You can find more information about this in my first article here -to-break-simple-software-protections/):
Soufiane Tahiri is is an InfoSec Institute contributor and computer security researcher, specializing in reverse code engineering and software security. He is also founder of www.itsecurity.ma and practiced reversing for more then 8 years. Dynamic and very involved, Soufiane is ready to catch any serious opportunity to be part of a workgroup.Contact Soufiane in whatever way works for you: Email: soufianetahiri@gmail.comTwitter: : :
This article was co-authored by wikiHow staff writer, Nicole Levine, MFA. Nicole Levine is a Technology Writer and Editor for wikiHow. She has more than 20 years of experience creating technical documentation and leading support teams at major web hosting and software companies. Nicole also holds an MFA in Creative Writing from Portland State University and teaches composition, fiction-writing, and zine-making at various institutions. This article has been viewed 778,788 times.Learn more...
The phased array (PA) probe model implemented in a UT simulation software, simSUNDT, developed by the Chalmers University of Technology, had been validated to some extent in terms of maximum echo amplitude towards well-defined artificial defects, i.e. side-drilled holes (SDHs) [6]. In the current paper, the model is to be further validated by comparing the data presentations (A-, B- and C-scan). These are retrieved from both experiments and corresponding simulations, which address some well-defined artificial defects in noise-free test specimens. Satisfactory correlations can be observed from the comparisons and the model can be concluded as an alternative to the corresponding experiments. The generated sound fields towards a certain type of defect, i.e. surface breaking crack, are optimized with the help of this validated model as an applied practice. The optimization in this work aims at retrieving a maximized echo amplitude by adjusting the combination of probe angle and focusing distance, which is easy and essential to change in the phased array configuration. The possibility and procedure of using the simulation model in sound field optimization work is hereby investigated. 2ff7e9595c
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