SAST - Static Application Security Testing
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Static Reviewer and Quality Reviewer, released in the Security Reviewer Suite, are provided both On Premise (Desktop, CI Plugins, Maven / Gradle / SBT / SonarQube Plugins, Ant Task and CLI Interface tested with many CI/CD platforms) and in Cloud (as Virtual Desktop or REST API Server), as Container (Docker, Kubernetes, OpenShift or any other APPC-compliant), executes code checks according most relevant Secure Coding Standards for commonly used Programming Languages. It offers a unique, full integration between Static Analysis (SAST) and DAST (Dynamic) analysis, directly inside Programmers IDE.
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Security Reviewer recognizes all programming languages that are composing the analyzed app.
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The analysis will be done automatically. Optionally, you can set the following:
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Audit Date
You can change the Audit Date as you want, selecting the proper date in the calendar.
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Target COBOL Version. For a precise parsing of the right COBOL Dialect.
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Security Reviewer supports the largest number of COBOL platforms in the market.
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Secure Code Analysis
Static Reviewer, can run either at Client side or at Server side. You can run it using our Desktop application, Developer's IDE, via command line or using our DevOps CI/CD plugins. Developers can run Secure Code Analysis also at server side via automated integration with our REST API server. See REST API Hardware Requirements for further details.
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SCM Integrations
You can directly checkout (push) source code from the following SCM platforms:
SubVersion (SVN)
IBM Rational ClearCase
Perforce
Mercurial
AccuRev
The source code will be stored temporary in an encrypted folder and loaded in a secure buffer.
Analysis Results can be stored in the above SCM platforms.
You can do that using our Jenkins plugin or directly from our Desktop app.
File Servers
All our products can work accessing files on local file system, as well as the following File Sharing Systems:
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Static Reviewer does not need RBDMS to run, and it is fully extensible via XML. It is able to analyze SQL code written on different SQL Dialects.
Our unified Dashboard, named Team Reviewer supports (configurable) the following RDBMS:
Oracle MySQL 5.6 or higher
Oracle Database RAC 12 or newer
Microsoft SQL Server 2012 or newer
PostgreSQL 9.0 and higher
Alpine H2 1.4.196 or newer
MariaDB 10.x
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Requests and Responses log. Our CI Plugins rely on your CI Platform for this kind of logging. See: https://jenkins.io/doc/pipeline/steps/http_request/ and https://confluence.atlassian.com/bamboo/logging-in-bamboo-289277239.html
Audit log. Our CI Plugins rely on your CI Platform for this kind of logging. See: https://plugins.jenkins.io/audit-log and https://confluence.atlassian.com/bamboo/logging-in-bamboo-289277239.html
Application log. Our Ci Plugin write XML cloned as plain-text in the current CI Workspace, using slf4j. Further the application log is written in the standard CI Console Output
Access log. See https://wiki.jenkins.io/display/JENKINS/Access+Logging and https://confluence.atlassian.com/bamboo/logging-in-bamboo-289277239.html
Vulnerability detection log. Two Vulnerability logging ways are provided: Inside Application log (see above) and a separate XML log in the current CI Workspace, using slf4j
The above logs are customizable according the customer needs.
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C#, Vb.NET, VB6, ASP, ASPX, Java, JSP, JavaScript (client side & server side), TypeScript, Java Server Faces, Ruby, Python, R, GO, Clojure, Groovy, Flex, ActionScript, PowerShell, Rust, LUA, Auto-IT, HTML5, XML, XPath, C, C++ (see C/C++ Options), PHP, SCALA,, IBM Streams Processing Language, Shell (bash, sh, csh, ksh), BPMN, BPEL, PowerBuilder, COBOL (see COBOL Options), JCL, RPG, PL/I, ABAP, SAP-HANA
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Supported Libraries and Frameworks (Static Analysis):
JAVA: 146 Frameworks
https://en.wikipedia.org/wiki/List_of_Java_Frameworks
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Parameters: Parameters in Naive Bayes are the estimates of the true distribution of whatever we're trying to classify. The variables your algorithm is trying to tune to build an accurate model..
Classifier: Classifiers are also referred to group of attributes. .
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Security Reviewer uses Blockchain to publish anonymous Effort Estimation data, under permission of voluntary organizations using our products. It maintains a repository of data from numerous organizations' completed software projects. In particular, the repository has provided research data on several topics, including APPW metrics, COCOMO, COSMIC, SLOC, LLOC, WMC, Cyclomatic Complexity, Technical Debt, Function Points, Country, Industry, Application Type, Project duration, and Cost estimation. A software benhmarking experiment performed by Security Reviewer determined whether using anonymous data provides any valuable information to an organization. The organization's completed projects are compared to similar projects in a Blockchain to establish averages for the organization and the industry as a whole. A critical aspect of the repository is confidentiality. Each organization is represented by a code (for example, “contributed by Organization X”) so that Security Reviewer can identify projects without revealing the organization itself. Codes are not available to the public.
CI PLUGINS
Security Reviewer Static Analysis
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