Alternatives to beSTORM

Software for continuous performance testing to automate API load and application testing. For complex applications, you can design code-free performance tests. Script performance tests in automated pipelines for API test. You can design, maintain, and run performance tests in code. Then analyze the results within continuous integration pipelines with pre-packaged plugins for CI/CD tools or the NeoLoad API. You can quickly create test scripts for large, complex applications with a graphical user interface. This allows you to skip the tedious task of manually coding new or updated tests. SLAs can be defined based on the built-in monitoring metrics. To determine the app's performance, put pressure on it and compare SLAs with server-level statistics. Automate pass/fail triggers using SLAs. Contributes to root cause analysis. Automatic test script updates make it easier to update test scripts. For easy maintenance, update only the affected part of the test and re-use any remaining.

Testsigma is a low-code end-to-end test automation platform for Agile teams. It lets SDETs, manual testers, SMEs, and QAs collaboratively plan, develop, execute, analyze, debug, and report on their automated testing for websites, native Android and iOS apps, and APIs. It is available as a fully managed, cloud-based solution as well as a self-hosted instance that is open source (Testsigma Community Edition). The platform is built with Java, but the automated tests are code-agnostic. Through built-in NLP Grammar, teams can automate user actions in simple English, or generate airtight test scripts with the Test Recorder. With features like built-in visual testing, parametrized or data-driven testing, 2FA testing, and an AI that automatically fixes unstable elements and test steps, identifies and isolates regression-affected scripts, and provides suggestions to help you find and fix test failures, Testsigma can replace tens of different tools in the QA toolchain to enable teams to test easily, continuously, and collaboratively.

It works: Codeless testing Give your entire team the ability to create and maintain automated tests. Not just developers. Meet your testing demands fast. You can get full coverage of your tests in days and not months. Our natural-language tests are very resistant to code changes. Our AI will quickly repair any test failures. Continuous Testing is a key component of Agile/DevOps. Push features to production in the same day. Boozang supports the following test approaches: - Codeless Record/Replay interface - BDD / Cucumber - API testing - Model-based testing - HTML Canvas testing The following features makes your testing a breeze - In-browser console debugging - Screenshots to show where test fails - Integrate to any CI server - Test with unlimited parallel workers to speed up tests - Root-cause analysis reports - Trend reports to track failures and performance over time - Test management integration (Xray / Jira)

Parasoft's mission is to provide automated testing solutions and expertise that empower organizations to expedite delivery of safe and reliable software. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

Qualibrate, the cloud solution for SAP & Web Apps test automation, is like Salesforce. It has the power to be simple, customized, and integrate with most CI/CD tools. Test cases can be reused many times and are easy to maintain. It is risky to embark on a journey of software transformation. We offer a simple, yet powerful, solution to reduce risk and implement resources up to 80%. Recording a Business Process is all you have to do: user actions, test data and technical information will all be recorded. This recording will serve as your only source of truth for Automated and Manual tests, as well for Learning. Visit the website to learn more about Qualibrate's innovative approach to SAP and web app testing.

Testim is the fastest way to create resilient end-to-end test cases, whether they are codeless or coded. Testim allows you to create codeless, stable tests that leverage our AI. You also have the option to export your tests as code. Testim's JavaScript API is available to you and your IDE. This allows you to debug, modify, or refactor your tests. To keep them in sync, store them in your version control system. Run tests on every commit. Testim is used by millions of customers every month, including NetApp, Wix and JFrog. Find out more on our website.

Defensics Fuzz Testing is a robust and flexible automated black box fuzzer that helps organizations efficiently identify and address vulnerabilities in their software. This generational fuzzer employs a smart, focused methodology for negative testing, allowing users to create custom test cases through advanced file and protocol templates. Additionally, the software development kit (SDK) empowers proficient users to leverage the Defensics framework to craft their own unique test scenarios. Being a black box fuzzer means that Defensics operates without the need for source code, which adds to its accessibility. By utilizing Defensics, organizations can enhance the security of their cyber supply chain, ensuring that their software and devices are interoperable, resilient, high-quality, and secure prior to deployment in IT or laboratory settings. This versatile tool seamlessly integrates into various development workflows, including both traditional Software Development Life Cycle (SDL) and Continuous Integration (CI) environments. Furthermore, its API and data export functions facilitate smooth integration with other technologies, establishing it as a truly plug-and-play solution for fuzz testing. As a result, Defensics not only enhances security but also streamlines the overall software development process.

Invicti (formerly Netsparker) dramatically reduces your risk of being attacked. Automated application security testing that scales like none other. Your team's security problems grow faster than your staff. Security testing automation should be integrated into every step in your SDLC. Automate security tasks to save your team hundreds of hours every month. Identify the critical vulnerabilities and then assign them to remediation. Whether you are running an AppSec, DevOps or DevSecOps program, help security and development teams to get ahead of their workloads. It's difficult to prove that you are doing everything possible to reduce your company's risk without full visibility into your apps, vulnerabilities and remediation efforts. You can find all web assets, even those that have been forgotten or stolen. Our unique dynamic + interactive (DAST+ IAST) scanning method allows you to scan the corners of your apps in a way that other tools cannot.

Black Duck, a segment of the Synopsys Software Integrity Group, stands out as a prominent provider of application security testing (AST) solutions. Their extensive array of offerings encompasses tools for static analysis, software composition analysis (SCA), dynamic analysis, and interactive analysis, which assist organizations in detecting and addressing security vulnerabilities throughout the software development life cycle. By streamlining the identification and management of open-source software, Black Duck guarantees adherence to security and licensing regulations. Their solutions are meticulously crafted to enable organizations to foster trust in their software while effectively managing application security, quality, and compliance risks at a pace that aligns with business demands. With Black Duck, businesses are equipped to innovate with security in mind, delivering software solutions confidently and efficiently. Furthermore, their commitment to continuous improvement ensures that clients remain ahead of emerging security challenges in a rapidly evolving technological landscape.

Mayhem is an innovative fuzz testing platform that integrates guided fuzzing with symbolic execution, leveraging a patented technology developed at CMU. This sophisticated solution significantly minimizes the need for manual testing by autonomously detecting and validating defects in software. By facilitating the delivery of safe, secure, and reliable software, it reduces the time, cost, and effort typically required. One of Mayhem's standout features is its capability to gather intelligence about its targets over time; as its understanding evolves, it enhances its analysis and maximizes overall code coverage. Every vulnerability identified is an exploitable and confirmed risk, enabling teams to prioritize their efforts effectively. Furthermore, Mayhem aids in remediation by providing comprehensive system-level insights, including backtraces, memory logs, and register states, which expedite the diagnosis and resolution of issues. Its ability to generate custom test cases in real-time, based on target feedback, eliminates the need for any manual test case creation. Additionally, Mayhem ensures that all generated test cases are readily accessible, making regression testing not only effortless but also a continuous and integral part of the development process. This seamless integration of automated testing and intelligent feedback sets Mayhem apart in the realm of software quality assurance.

PFLB specializes exclusively in performance testing. We help companies identify and resolve performance bottlenecks, such as slow database queries or API calls that are not performing well. We are the company of choice for clients who need performance testing across a wide range of technologies, such as web and mobile applications and core banking systems. We offer a wide range of solutions for JMeter, LoadRunner and other environments. PFLB is a load testing platform that allows companies to perform efficient and scalable performance test. PFLB is a global leader in performance testing with over 15 years' experience.

Upload your application to Waldo and navigate through it just as you would on your mobile device. Waldo captures each screen along with the logic that links them, providing insights into your app's structure. This process is accessible to everyone. Are you preparing to release an updated version of your app? We've got you covered. Waldo efficiently replays your tests for every new iteration of your app automatically. If any test encounters a failure, Waldo promptly informs you about the exact location of the problem, enabling you to either modify the failed test or notify your team to address the issue. This is particularly beneficial for agile mobile teams that are looking to reap the rewards of automation without the necessary resources, time, or inclination to set up scripting tools. Additionally, larger app development teams can focus more on enhancing code quality and adding new features rather than getting bogged down in bug tracking. Ultimately, Waldo streamlines the testing process, allowing teams to prioritize innovation and efficiency.

OSS-Fuzz provides ongoing fuzz testing for open source applications, a method renowned for identifying programming flaws. Such flaws, including buffer overflow vulnerabilities, can pose significant security risks. Through the implementation of guided in-process fuzzing on Chrome components, Google has discovered thousands of security weaknesses and stability issues, and now aims to extend this beneficial service to the open source community. The primary objective of OSS-Fuzz is to enhance the security and stability of frequently used open source software by integrating advanced fuzzing methodologies with a scalable and distributed framework. For projects that are ineligible for OSS-Fuzz, there are alternatives available, such as running personal instances of ClusterFuzz or ClusterFuzzLite. At present, OSS-Fuzz is compatible with languages including C/C++, Rust, Go, Python, and Java/JVM, with the possibility of supporting additional languages that are compatible with LLVM. Furthermore, OSS-Fuzz facilitates fuzzing for both x86_64 and i386 architecture builds, ensuring a broad range of applications can benefit from this innovative testing approach. With this initiative, we hope to build a safer software ecosystem for all users.

Appium serves as an open-source framework designed for automating tests on native, hybrid, and mobile web applications. It interfaces with apps on iOS, Android, and Windows platforms through the WebDriver protocol. The foundation of Appium rests on the principle that testing native applications should not necessitate integrating an SDK or recompiling the application. Moreover, it allows users to utilize their preferred testing methodologies, frameworks, and tools. As a community-driven open-source initiative, Appium has made strategic design choices to foster active contributions from developers. The framework's goal is to enable automation for any mobile application using any programming language and testing framework, while providing complete access to back-end APIs and databases through test scripts. You can create tests with your favorite development tools across various programming languages, enhancing flexibility, and likely even more options with the help of the Selenium WebDriver API and dedicated client libraries for different languages. This versatility makes Appium a popular choice among developers looking for robust mobile application testing solutions.

Awesome Fuzzing serves as a comprehensive compilation of resources for those interested in the field of fuzzing, encompassing an array of materials such as books, both free and paid courses, videos, tools, tutorials, and vulnerable applications ideal for hands-on practice to enhance one's understanding of fuzzing and the early stages of exploit development, including root cause analysis. It features instructional videos focused on fuzzing methodologies, essential tools, and recommended practices, alongside conference presentations, tutorials, and blogs dedicated to the subject. Additionally, it includes software tools that facilitate fuzzing of applications, particularly those utilizing network protocols like HTTP, SSH, and SMTP. Users are encouraged to search for and select exploits linked to downloadable applications, where they can then recreate the exploits with their preferred fuzzer. The resource also encompasses a range of tests tailored for fuzzing engines, highlighting various well-known vulnerabilities and providing a corpus of diverse file formats to enable fuzzing across multiple targets found in the existing fuzzing literature. Ultimately, this collection aims to empower learners with the necessary knowledge and skills to effectively engage with fuzzing techniques and develop their expertise in security testing.

Go-fuzz serves as a coverage-guided fuzzing tool designed specifically for testing Go packages, making it particularly effective for those that handle intricate inputs, whether they are textual or binary in nature. This method of testing is crucial for strengthening systems that need to process data from potentially harmful sources, such as network interactions. Recently, go-fuzz has introduced initial support for fuzzing Go Modules, inviting users to report any issues they encounter with detailed descriptions. It generates random input data, which is often invalid, and the function must return a value of 1 to indicate that the fuzzer should elevate the priority of that input in future fuzzing attempts, provided that it should not be stored in the corpus, even if it uncovers new coverage; a return value of 0 signifies the opposite, while other values are reserved for future enhancements. The fuzz function is required to reside in a package that go-fuzz can recognize, meaning the code under test cannot be located within the main package, although fuzzing of internal packages is permitted. This structured approach ensures that the testing process remains efficient and focused on identifying vulnerabilities in the code.

HCL AppScan for Application Security Testing. To minimize attack exposure, adopt a scalable security test strategy that can identify and fix application vulnerabilities at every stage of the development process. HCL AppScan provides the best security testing tools available to protect your business and customers from attack. Rapidly identify, understand, and fix security vulnerabilities. App vulnerability detection and remediation is key to avoiding problems. Cloud-based application security testing suite for performing static, dynamic, and interactive testing on web and mobile. Multi-user, multiapp dynamic application security (DAST), large-scale, multiuser, multi-app security for applications (DAST), to identify, understand, and remediate vulnerabilities and attain regulatory compliance.

APIFuzzer analyzes your API specifications and systematically tests the fields to ensure your application can handle modified parameters, all without the need for programming. It allows you to import API definitions from either local files or remote URLs, supporting both JSON and YAML formats. Every HTTP method is accommodated, and it can fuzz the request body, query strings, path parameters, and request headers. Utilizing random mutations, it also integrates seamlessly with continuous integration systems. The tool can produce test reports in JUnit XML format and has the capability to send requests to alternative URLs. It supports HTTP basic authentication through configuration settings and stores reports of any failed tests in JSON format within a designated folder, thus ensuring that all results are easily accessible for review. Additionally, this enhances your ability to identify vulnerabilities and improve the reliability of your API.

Honggfuzz is a software fuzzer focused on enhancing security through its advanced fuzzing techniques. It employs evolutionary and feedback-driven methods that rely on both software and hardware-based code coverage. This tool is designed to operate in a multi-process and multi-threaded environment, allowing users to maximize their CPU's potential without needing to launch multiple fuzzer instances. The file corpus is seamlessly shared and refined across all processes undergoing fuzzing, which greatly enhances efficiency. When persistent fuzzing mode is activated, Honggfuzz exhibits remarkable speed, capable of executing a simple or empty LLVMFuzzerTestOneInput function at an impressive rate of up to one million iterations per second on modern CPUs. It has a proven history of identifying security vulnerabilities, including the notable discovery of the only critical vulnerability in OpenSSL to date. Unlike other fuzzing tools, Honggfuzz can detect and report on hijacked or ignored signals that result from crashes, making it a valuable asset for identifying hidden issues within fuzzed programs. Its robust features make it an essential tool for security researchers aiming to uncover hidden flaws in software systems.

Echidna is a Haskell-based tool created for fuzzing and property-based testing of Ethereum smart contracts. It employs advanced grammar-driven fuzzing strategies that leverage a contract's ABI to challenge user-defined predicates or Solidity assertions. Designed with a focus on modularity, Echidna allows for easy extensions to incorporate new mutations or to target specific contracts under particular conditions. The tool generates inputs that are specifically adapted to your existing codebase, and it offers optional features for corpus collection, mutation, and coverage guidance to uncover more elusive bugs. It utilizes Slither to extract critical information prior to launching the fuzzing process, ensuring a more effective campaign. With source code integration, Echidna can pinpoint which lines of code are exercised during testing, and it provides an interactive terminal UI along with text-only or JSON output formats. Additionally, it includes automatic test case minimization for efficient triage and integrates seamlessly into the development workflow. The tool also reports maximum gas usage during fuzzing activities and supports complex contract initialization through Etheno and Truffle, enhancing its usability for developers. Ultimately, Echidna stands out as a robust solution for ensuring the reliability and security of Ethereum smart contracts.

StackHawk evaluates your active applications, services, and APIs for potential security flaws introduced by your team, as well as for vulnerabilities in open-source components that could be exploited. In today's engineering landscape, automated testing suites integrated within CI/CD processes have become standard practice. So, why should application security not follow suit? StackHawk is designed to identify vulnerabilities right within your development pipeline. The phrase "built for developers" embodies the core philosophy of StackHawk, emphasizing the importance of integrating security into the development process. As application security evolves to keep pace with the rapid tempo of modern engineering teams, developers require tools that enable them to assess and remediate security issues effectively. With StackHawk, security can advance in tandem with development, allowing teams to detect vulnerabilities at the stage of pull requests and implement fixes swiftly, whereas traditional security tools often lag behind, waiting for manual scans to be initiated. This tool not only meets the needs of developers but is also backed by the most widely adopted open-source security scanner available, ensuring it remains a favorite among users. Ultimately, StackHawk empowers developers to embrace security as an integral part of their workflow.

American fuzzy lop is a security-focused fuzzer that utilizes a unique form of compile-time instrumentation along with genetic algorithms to automatically generate effective test cases that can uncover new internal states within the targeted binary. This approach significantly enhances the functional coverage of the code being fuzzed. Additionally, the compact and synthesized test cases produced by the tool can serve as a valuable resource for initiating other, more demanding testing processes in the future. Unlike many other instrumented fuzzers, afl-fuzz is engineered for practicality, boasting a minimal performance overhead while employing a diverse array of effective fuzzing techniques and strategies for minimizing effort. It requires almost no setup and can effortlessly manage complicated, real-world scenarios, such as those found in common image parsing or file compression libraries. As an instrumentation-guided genetic fuzzer, it excels at generating complex file semantics applicable to a wide variety of challenging targets, making it a versatile choice for security testing. Its ability to adapt to different environments further enhances its appeal for developers seeking robust solutions.

Every minute, a multitude of autonomously generated tests is executed to identify vulnerabilities and facilitate swift remediation. Mayhem eliminates uncertainty surrounding untested code by autonomously creating test suites that yield practical outcomes. There is no requirement to recompile the code, as Mayhem operates seamlessly with dockerized images. Its self-learning machine learning technology continuously executes thousands of tests each second, searching for crashes and defects, allowing developers to concentrate on enhancing features. Background continuous testing detects new defects and expands code coverage effectively. For each defect identified, Mayhem provides a detailed reproduction and backtrace, prioritizing them according to your risk assessment. Users can view all results, organized and prioritized based on immediate needs for fixes. Mayhem integrates effortlessly into your existing development tools and build pipeline, granting developers access to actionable insights regardless of the programming language or tools utilized by the team. This adaptability ensures that teams can maintain their workflow without disruption while enhancing their code quality.

Our platform uses a variety of security techniques, including feedback-based fuzz testing and coverage-guided fuzz testing, in order to generate millions upon millions of test cases that trigger difficult-to-find bugs deep in your application. This white-box approach helps to prevent edge cases and speed up development. Advanced fuzzing engines produce inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Only uncover true vulnerabilities. You will need the stack trace and input to prove that you can reproduce errors reliably every time. AI white-box testing is based on data from all previous tests and can continuously learn the inner workings of your application. This allows you to trigger security-critical bugs with increasing precision.

Automated Continuous Testing without the need for coding is made possible with Tricentis Tosca, recognized as the leading platform in this domain, which enhances the testing process through its script-free, no-code methodology for comprehensive test automation. Supporting a vast range of over 160 technologies and enterprise applications, Tosca ensures robust test automation suited for various use cases. Discover the advantages of Tricentis Tosca, which include: - Rapid feedback mechanisms tailored for Agile and DevOps environments - Significant reduction in regression testing durations to mere minutes - Enhanced reusability and maintenance of test assets - Clear visibility into potential business risks - Seamless integration and extension of existing testing resources such as HPE UFT, Selenium, and SoapUI, among others. By leveraging these capabilities, organizations can streamline their testing processes and improve overall quality assurance.

Discover all the essential tools to construct dependable software with confidence through Chaos Engineering. Take advantage of Gremlin's extensive range of failure scenarios to conduct experiments throughout your entire infrastructure, whether it's bare metal, cloud platforms, containerized setups, Kubernetes, applications, or serverless architectures. You can manipulate resources by throttling CPU, memory, I/O, and disk usage, reboot hosts, terminate processes, and even simulate time travel. Additionally, you can introduce network latency, create blackholes for traffic, drop packets, and simulate DNS failures. Ensure your code is resilient by testing for potential failures and delays in serverless functions. Furthermore, you have the ability to limit the effects of these experiments to specific users, devices, or a certain percentage of traffic, enabling precise assessments of your system's robustness. This approach allows for a thorough understanding of how your software reacts under various stress conditions.

TestProject is the first cloud-based, community-powered, free test automation platform. TestProject makes testing easier by allowing testers to work quickly and to collaborate with other testers using popular open-source frameworks (e.g. Selenium and Appium). This allows them to achieve quality and speed. TestProject is shaping the future for software testing by creating a community that can work together as individuals and in groups. TestProject was founded in Israel in 2015. It aims to create an environment that is powerful and collaborative for all test automation communities, without any barriers and completely free. Learn more at https://testproject.io.

MaTeLo offers a straightforward yet powerful approach to testing intricate systems. It allows you to effortlessly keep your tests current without the hassle of manually regenerating every test case, as MaTeLo handles all the necessary updates for you! A diagram is undoubtedly more accessible than a block of code, enabling you to quickly grasp the testing mechanics whether they were created by you or others. You can revisit and refresh your tests at any time without wasting hours on recreating everything from scratch. Experience the advantages of a collaborative and visual environment, where you can modify your tests seamlessly through an interface designed for ease of use. There's no requirement to possess advanced coding skills! With MaTeLo, developing your tests is simpler than ever. Utilize the built-in widgets to outline your tasks and transitions efficiently. The Drag&Drop feature lets you prioritize the logic of your tests by illustrating your system with visual elements. You can test countless scenarios using your data sets and create unlimited variations within your data, ensuring thorough examination and flexibility. MaTeLo truly redefines the testing process, making it both engaging and accessible.

All members of the team can perform robust automated testing on desktop, mobile, and web applications. This is regardless of whether they have any experience with functional test automation tools. Ranorex Studio is an all in one solution that provides codeless automation tools and a complete IDE. Ranorex Studio's industry-leading object recognition system and shareable object repository make it possible to automate GUI testing, regardless of whether you are using legacy applications or the latest mobile and web technologies. Ranorex Studio supports cross browser testing with integrated Selenium WebDriver integration. Easy data-driven testing can be done using CSV files, Excel spreadsheets, or SQL database files. Ranorex Studio supports keyword-driven testing. Our tools for collaboration enable test automation engineers to create reusable code modules, and share them with their team. Get a 30-day free trial to get started with automation testing.

End-to-end testing of any web-based application is fast, simple and reliable.

ProdPerfect is the first fully-managed, autonomous, end-to–end (E2E), regression testing solution that continually builds, maintains, evolves E2E test sets via data-driven, machine–led analysis of user behavior data. It is the only fully managed solution that covers critical gaps in test coverage, eliminates lengthy test suite runtimes, and eliminates costly bugs in production. Additionally, it removes the QA burden which consumes large engineering resources.

BlazeMeter offers an enterprise-ready platform that is open-source based, integrating all essential features to facilitate both left and right shift testing. With a user-friendly interface, you can easily create tests or adapt your existing scripts to execute them at scale as a part of your ongoing testing strategy. Generate comprehensive reports and analyze historical trends to enhance your testing process. This allows you to dedicate more time to innovation instead of toolchain upkeep. Continuous testing plays a crucial role in achieving quality, volume, and speed in your deliverables. However, the challenges of integrating, managing, learning, and switching between various tools can consume precious time and resources. BlazeMeter simplifies this process with a highly intuitive platform that encompasses everything you need. It guarantees a complete shift left testing experience, enabling you to impress the market with your advancements. BlazeMeter equips you with all necessary elements for continuous shift left testing, providing options to work with CLIs, APIs, UI, open-source tools, and beyond. As a result, you can significantly reduce the time spent on setup, maintenance, training, and everyday usage, ultimately streamlining your workflow. This efficiency not only enhances productivity but also empowers teams to focus on what truly matters: delivering exceptional products.

DefenseCode WebScanner serves as a Dynamic Application Security Testing (DAST) tool, specializing in thorough security evaluations of active websites. By simulating a multitude of attacks using sophisticated methods akin to those employed by actual hackers, WebScanner effectively assesses a website's defenses. This versatile tool is compatible with any web application development platform and can function even when the source code of the application is inaccessible. It accommodates a variety of prevalent web technologies like HTML, HTML5, Web 2.0, AJAX/jQuery, JavaScript, and Flash. With the capability to perform over 5,000 tests for Common Vulnerabilities and Exposures, WebScanner identifies more than 60 distinct types of vulnerabilities, including SQL Injection, Cross Site Scripting, and Path Traversal, as well as those outlined in the OWASP Top 10. Additionally, it is an essential resource for organizations seeking to enhance their web application security posture.

When you engage with a web page, Screenster captures your interactions seamlessly. There’s no need for coding, referencing element IDs, or inserting checks and assertions. After recording your test, you can rerun it while allowing Screenster to enhance its performance. It automatically identifies parameters, and self-healing selectors are saved for every action taken. You can review and approve any alterations to the baseline, updating the default state of the user interface as needed. Additionally, you have the option to exclude specific UI elements from the comparison process. Forget about browser plugins, desktop installations, or complicated manuals; just enter a URL for a Screenster server and start your experience. Screenster is adept at detecting both visual and content modifications, utilizing advanced algorithms to compare test outcomes against the baseline and identify new, removed, or modified elements. Its intelligent selectors can effortlessly track moved or altered page components. Furthermore, Screenster intelligently adjusts timeouts and employs AI to determine the optimal moment to proceed to the next action. You can choose to execute your tests on our cloud platform or opt to download and install Screenster Server locally for on-premise use. Not only does Screenster simplify the testing process, but it also enhances efficiency and accuracy, making it an invaluable tool for developers and testers alike.

LibFuzzer serves as an in-process, coverage-guided engine for evolutionary fuzzing. By being linked directly with the library under examination, it injects fuzzed inputs through a designated entry point, or target function, allowing it to monitor the code paths that are executed while creating variations of the input data to enhance code coverage. The coverage data is obtained through LLVM’s SanitizerCoverage instrumentation, ensuring that users have detailed insights into the testing process. Notably, LibFuzzer continues to receive support, with critical bugs addressed as they arise. To begin utilizing LibFuzzer with a library, one must first create a fuzz target—this function receives a byte array and interacts with the API being tested in a meaningful way. Importantly, this fuzz target operates independently of LibFuzzer, which facilitates its use alongside other fuzzing tools such as AFL or Radamsa, thereby providing versatility in testing strategies. Furthermore, the ability to leverage multiple fuzzing engines can lead to more robust testing outcomes and clearer insights into the library's vulnerabilities.

Proteus is a cutting-edge software testing solution designed to automatically detect and remediate vulnerabilities without generating false positives, targeting development teams, testing agencies, and cybersecurity professionals. It identifies potential weaknesses that may arise from harmful files or network data, addressing numerous entries listed in the Common Weakness Enumeration (CWE). This versatile tool supports both Windows and Linux native binaries, enhancing its usability across various platforms. By effectively incorporating and streamlining the utilization of state-of-the-art binary analysis and transformation tools, Proteus reduces costs while boosting the efficiency and effectiveness of software testing, reverse engineering, and ongoing maintenance efforts. Its capabilities include binary analysis, mutational fuzzing, and symbolic execution, all achievable without access to the source code, complemented by a professional-grade user interface for collating and displaying results. Moreover, it offers advanced reporting on exploitability and reasoning, making it suitable for deployment in both virtualized environments and on physical host systems, ultimately enhancing overall security processes. By ensuring comprehensive coverage of potential vulnerabilities, Proteus equips teams to better safeguard their software applications.

Fuzz testing, commonly referred to as fuzzing, is a technique used in software testing that aims to discover implementation errors by injecting malformed or semi-malformed data in an automated way. For example, consider a scenario involving an integer variable within a program that captures a user's selection among three questions; the user's choice can be represented by the integers 0, 1, or 2, resulting in three distinct cases. Since integers are typically stored as fixed-size variables, a failure to implement the default switch case securely could lead to program crashes and various traditional security vulnerabilities. Fuzzing serves as an automated method for uncovering software implementation issues, enabling the identification of bugs when they occur. A fuzzer is a specialized tool designed to automatically inject semi-random data into the program stack, aiding in the detection of anomalies. The process of generating this data involves the use of generators, while the identification of vulnerabilities often depends on debugging tools that can analyze the program's behavior under the influence of the injected data. These generators typically utilize a mixture of established static fuzzing vectors to enhance the testing process, ultimately contributing to more robust software development practices.

The Fuzzbuzz workflow closely resembles other continuous integration and continuous delivery (CI/CD) testing processes, but it stands out because it necessitates the concurrent execution of multiple jobs, adding several additional steps. As a dedicated fuzz testing platform, Fuzzbuzz simplifies the integration of fuzz tests into developers' code, enabling them to execute these tests within their CI/CD pipelines, which is essential for identifying critical bugs and security vulnerabilities before they reach production. Fuzzbuzz seamlessly blends into your existing environment, providing support from the terminal through to CI/CD. You can easily write a fuzz test using your preferred IDE, terminal, or build tools, and once you push your code changes to CI/CD, Fuzzbuzz will automatically initiate the fuzz testing process on the latest updates. You'll receive notifications about any bugs detected through various channels like Slack, GitHub, or email, ensuring you're always informed. Additionally, as new changes are introduced, regressions are automatically tested and compared against previous results, allowing for continuous monitoring of code stability. The moment a change is detected, Fuzzbuzz builds and instruments your code, ensuring that your development process remains efficient and responsive. This proactive approach helps maintain high-quality code and reduces the risk of deploying flawed software.

CI Fuzz guarantees that your code is both robust and secure, achieving test coverage levels as high as 100%. You can utilize CI Fuzz through the command line or within your preferred integrated development environment (IDE) to automatically generate a vast number of test cases. Similar to a unit test, CI Fuzz analyzes code during execution, leveraging AI to ensure every code path is effectively covered. This tool helps you identify genuine bugs in real-time, eliminating the need to deal with hypothetical problems and erroneous positives. It provides all the necessary details to help you swiftly reproduce and resolve actual issues. By maximizing your code coverage, CI Fuzz also automatically identifies common security vulnerabilities, such as injection flaws and remote code execution risks, all in a single process. Ensure your software is of the highest quality by achieving comprehensive test coverage. With CI Fuzz, you can elevate your unit testing practices, as it harnesses AI for thorough code path analysis and the seamless creation of numerous test cases. Ultimately, it enhances your pipeline's efficiency without sacrificing the integrity of the software being produced. This makes CI Fuzz an essential tool for any developer aiming to improve code quality and security.

The Solidity Fuzzing Boilerplate serves as a foundational template designed to simplify the fuzzing process for various components within Solidity projects, particularly libraries. By writing tests just once, developers can easily execute them using both Echidna and Foundry's fuzzing tools. In instances where components require different versions of Solidity, these can be deployed into a Ganache instance with the help of Etheno. To generate intricate fuzzing inputs or to conduct differential fuzzing by comparing outputs with non-EVM executables, HEVM's FFI cheat code can be utilized effectively. Additionally, you can publish the results of your fuzzing experiments without concerns about licensing issues by modifying the shell script to retrieve specific files. If you do not plan to use shell commands from your Solidity contracts, it is advisable to disable FFI since it can be slow and should primarily serve as a workaround. This functionality proves beneficial when testing against complex implementations that are challenging to replicate in Solidity but are available in other programming languages. It is essential to review the commands being executed before running tests in projects that have FFI activated, ensuring a clear understanding of the operations taking place. Always prioritize clarity in your testing approach to maintain the integrity and effectiveness of your fuzzing efforts.

AFL-Unicorn provides the capability to fuzz any binary that can be emulated using the Unicorn Engine, allowing you to target specific code segments for testing. If you can emulate the desired code with the Unicorn Engine, you can effectively use AFL-Unicorn for fuzzing purposes. The Unicorn Mode incorporates block-edge instrumentation similar to what AFL's QEMU mode employs, enabling AFL to gather block coverage information from the emulated code snippets to drive its input generation process. The key to this functionality lies in the careful setup of a Unicorn-based test harness, which is responsible for loading the target code, initializing the state, and incorporating data mutated by AFL from its disk storage. After establishing these parameters, the test harness emulates the binary code of the target, and upon encountering a crash or error, triggers a signal to indicate the issue. While this framework has primarily been tested on Ubuntu 16.04 LTS, it is designed to be compatible with any operating system that can run both AFL and Unicorn without issues. With this setup, developers can enhance their fuzzing efforts and improve their binary analysis workflows significantly.

BFuzz is a tool designed for input-based fuzzing that utilizes HTML as its source input, launching a new instance of your browser to execute various test cases created by the domato generator located in the recurve directory. In addition, BFuzz automates the process by repeatedly performing the same operations without altering any of the test cases. When you run BFuzz, it prompts you to choose between fuzzing Chrome or Firefox; however, it specifically opens Firefox from the recurve directory and generates logs in the terminal. This lightweight script facilitates the opening of a browser and the execution of test cases, which are systematically generated by the domato tool and include the main scripting functionality. Furthermore, the script incorporates supplementary helper code that is essential for effective DOM fuzzing, enhancing the overall testing process. Its streamlined design makes it an efficient choice for developers looking to perform thorough web application testing.

Atheris is a Python fuzzing engine guided by coverage, designed to test both Python code and native extensions developed for CPython. It is built on the foundation of libFuzzer, providing an effective method for identifying additional bugs when fuzzing native code. Atheris is compatible with Linux (both 32- and 64-bit) and Mac OS X, supporting Python versions ranging from 3.6 to 3.10. Featuring an integrated libFuzzer, it is well-suited for fuzzing Python applications, but when targeting native extensions, users may need to compile from source to ensure compatibility between the libFuzzer version in Atheris and their Clang installation. Since Atheris depends on libFuzzer, which is a component of Clang, users of Apple Clang will need to install a different version of LLVM, as the default does not include libFuzzer. The implementation of Atheris as a coverage-guided, mutation-based fuzzer (LibFuzzer) simplifies the setup process by eliminating the need for input grammar definition. However, this approach can complicate the generation of inputs for code that processes intricate data structures. Consequently, while Atheris offers ease of use in many scenarios, it may face challenges when dealing with more complex parsing requirements.

FuzzDB was developed to enhance the chances of identifying security vulnerabilities in applications through dynamic testing methods. As the first and most extensive open repository of fault injection patterns, along with predictable resource locations and regex for server response matching, it serves as an invaluable resource. This comprehensive database includes detailed lists of attack payload primitives aimed at fault injection testing. The patterns are organized by type of attack and, where applicable, by the platform, and they are known to lead to vulnerabilities such as OS command injection, directory listings, directory traversals, source code exposure, file upload bypass, authentication bypass, cross-site scripting (XSS), HTTP header CRLF injections, SQL injection, NoSQL injection, and several others. For instance, FuzzDB identifies 56 patterns that might be interpreted as a null byte, in addition to offering lists of frequently used methods and name-value pairs that can activate debugging modes. Furthermore, the resource continuously evolves as it incorporates new findings and community contributions to stay relevant against emerging threats.

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ToothPicker serves as an innovative in-process, coverage-guided fuzzer specifically designed for iOS, focusing on the Bluetooth daemon and various Bluetooth protocols. Utilizing FRIDA as its foundation, this tool can be tailored to function on any platform compatible with FRIDA. The repository also features an over-the-air fuzzer that showcases an example implementation for fuzzing Apple's MagicPairing protocol through InternalBlue. Furthermore, it includes the ReplayCrashFile script, which aids in confirming any crashes identified by the in-process fuzzer. This simple fuzzer operates by flipping bits and bytes in inactive connections, lacking coverage or injection, yet it serves effectively as a demonstration and is stateful. It requires only Python and Frida to operate, eliminating the need for additional modules or installations. Built upon the frizzer codebase, it's advisable to establish a virtual Python environment for optimal performance with frizzer. Notably, with the introduction of the iPhone XR/Xs, the PAC (Pointer Authentication Code) feature has been implemented. This advancement underscores the necessity for continuous adaptation of fuzzing tools like ToothPicker to keep pace with evolving iOS security measures.

Enhance your software delivery speed and quality with integrated test management and automation within Jira, driven by HaloAI. Benefit from cross-project hierarchical test libraries, customizable parameters, shared test steps, and virtually limitless storage capabilities. Gain insights through 70 different cross-project reports, comprehensive change tracking, and test case versioning, all ensuring 360-degree traceability. Experience AI-powered no-code test automation alongside intelligent test step recommendations, record-and-playback features, BDD, and CI/CD integrations. As release cycles become more rapid and feature-rich, a more strategic approach to test case design is essential. Utilizing test modularization in Zephyr Scale dramatically minimizes redundancy during the design process while enhancing reusability for extensive test case libraries. You can streamline manual test automation with SmartBear HaloAI, as Zephyr Scale offers in-depth visibility throughout your entire test management journey, seamlessly integrated within Jira. Users can efficiently create and link test cases to user stories, initiating test executions directly from the issue screen for a more fluid workflow. This unified approach not only simplifies the testing process but also fosters collaboration among teams, ultimately leading to higher quality software releases.

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The Avo Quality Automation System sets the benchmark for effective, intelligent, and resilient automation, empowering individuals to move away from tedious manual tasks and focus on what truly excites them. Avo Assure, which is both highly intelligent and adaptable across various applications, elevates quality assurance beyond the capabilities of existing software test automation solutions without the need for coding. It allows for the instant auto-generation of test automation for web, mobile, desktop, ERP applications, and mainframes, all without any coding requirements. With access to over 1400 prebuilt keywords, users can swiftly and effortlessly construct test cases tailored to their needs. The system also introduces a unique mind map feature, enabling users to visualize their test landscape clearly. Additionally, it facilitates quick updates and upgrades to test scenarios, which enhances coverage while minimizing maintenance efforts. As applications evolve over time, Avo Assure helps in eliminating errors that may arise from changes and updates. With its advanced features, Avo Assure redefines quality assurance, making it a must-have tool in the realm of test automation. This innovative approach not only streamlines the testing process but also significantly boosts productivity and efficiency in quality assurance practices.

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