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Black Duck Coverity vs Netzob

Black Duck Coverity

blackduck.com

Netzob

netzob.org

Side by side

FigureBlack Duck CoverityNetzob
Price from—Free
Free plan—Yes
Free trial——
Open source——
WebYes—
WindowsYesYes
macOSYes—
LinuxYesYes
Self-hostedYes—
Plans published11
Spec score · Fuzz Testing Software7.8 (#11)7.5 (#15)
PurposeCoverity is an enterprise-grade static analysis solution that finds and fixes security vulnerabilities and code quality defects before software ships.Netzob is an open source tool for reverse engineering, traffic generation, and fuzzing of communication protocols.

Plans

Black Duck Coverity

  • Coverity Static AnalysisPriced on request

Black Duck Coverity pricing →

Netzob

  • NetzobFree

Netzob pricing →

In their own words

Black Duck Coverity

Black Duck Coverity is a paid static analysis solution for finding security vulnerabilities and code quality defects in source code before software ships. It analyzes code without executing it, scanning across files and libraries in entire codebases. Black Duck lists support for 22 programming languages and more than 250 frameworks, along with standards including MISRA, AUTOSAR, ISO 26262, PCI DSS, CERT C/C++/Java, DISA STIG, OWASP Top 10, and CWE Top 25. Coverity is TÜV SÜD certified for IEC 61508-3 support-tool requirements and qualified for use up to ASIL D under ISO 26262 and Level A under DO-178C. The Code Sight IDE plug-in offers real-time results, issue summaries, and code fixes. IDE, SCM, and CI integrations can trigger scans on commits and pull requests; listed connections include GitHub, GitLab, Bitbucket, Azure DevOps, Jenkins, and others. Deployment can be fully air-gapped on premises, including Kubernetes clusters. Pricing is customized to team size and codebase and supplied by quote.

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Netzob

Netzob is a free, GPLv3-licensed open-source tool for reverse engineering, traffic generation, and fuzzing of communication protocols. It infers message formats and protocol state machines through passive and active processes. Vocabulary inference learns formats from supplied traces, while grammar inference supports semi-automatic state-machine learning. With those models, its simulator can act as a client, server, or both to generate traffic. The fuzzing module creates optimized test cases by mutation or generation. Inputs can include live network traffic, PCAP captures, IPC, text and binary files, and API flows through supported formats. Exports include XML, human-readable output, and Peach fuzzer formats, with custom exporters possible. Netzob runs locally on Linux and Windows and supports Python 3. It targets network protocols, structured files, text protocols, drivers, devices, and other listed target types. Version 0.4.1 is listed as the latest stable release, with packages dated February 2, 2013.

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