Alternatives to FuzzDB
Compare FuzzDB alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to FuzzDB in 2025. Compare features, ratings, user reviews, pricing, and more from FuzzDB competitors and alternatives in order to make an informed decision for your business.
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1
OWASP WSFuzzer
OWASP
Fuzz testing or fuzzing is a software testing technique, that basically consists in finding implementation bugs using malformed/semi-malformed data injection in an automated fashion. Let’s consider an integer in a program, which stores the result of a user’s choice between 3 questions. When the user picks one, the choice will be 0, 1, or 2, which makes three practical cases. Integers are stored as a static size variable. If the default switch case hasn’t been implemented securely, the program may crash and lead to “classical” security issues. Fuzzing is the art of automatic bug finding, and its role is to find software implementation faults and identify them if possible. A fuzzer is a program that automatically injects semi-random data into a program/stack and detects bugs. The data-generation part is made of generators, and vulnerability identification relies on debugging tools. Generators usually use combinations of static fuzzing vectors. -
2
API Fuzzer
Fuzzapi
API Fuzzer allows to fuzz-request attributes using common pentesting techniques and lists vulnerabilities. API Fuzzer gem accepts an API request as input and returns vulnerabilities possible in the API. Cross-site scripting vulnerability, SQL injection, blind SQL injection, XML external entity vulnerability, IDOR, API rate limiting, open redirect vulnerabilities, information disclosure flaws, info leakage through headers, and cross-site request forgery vulnerability.Starting Price: Free -
3
Wfuzz
Wfuzz
Wfuzz provides a framework to automate web application security assessments and could help you secure your web applications by finding and exploiting web application vulnerabilities. You can also run Wfuzz from the official Docker image. Wfuzz is based on the simple concept that it replaces any reference to the fuzz keyword with the value of a given payload. A payload in Wfuzz is a source of data. This simple concept allows any input to be injected in any field of an HTTP request, allowing it to perform complex web security attacks in different web application components such as parameters, authentication, forms, directories/files, headers, etc. Wfuzz’s web application vulnerability scanner is supported by plugins. Wfuzz is a completely modular framework and makes it easy for even the newest Python developers to contribute. Building plugins is simple and takes little more than a few minutes.Starting Price: Free -
4
CI Fuzz
Code Intelligence
CI Fuzz ensures robust and secure code with test coverage up to 100%. Use CI Fuzz from the command line or in the IDE of choice to generate thousands of test cases automatically. CI Fuzz analyzes code as it runs, just like a unit test, but with AI support to efficiently cover all paths through the code. Uncover real bugs in real-time and say goodbye to theoretical issues and false positives. Find real issues with all the information needed to quickly reproduce and fix them. Test your code with maximum code coverage and automatically detect typical security-relevant bugs like injections and remote code executions automatically in one go. Get fully covered to deliver the highest quality software. Conduct real-time code analysis with CI Fuzz. Take unit tests to the next level. It employs AI for comprehensive code path coverage and the automatic generation of thousands of test cases. Maximize pipeline performance that doesn't compromise software integrity.Starting Price: €30 per month -
5
Wapiti
Wapiti
Wapiti is a web application vulnerability scanner. Wapiti allows you to audit the security of your websites or web applications. It performs "black-box" scans (it does not study the source code) of the web application by crawling the webpages of the deployed web app, looking for scripts and forms where it can inject data. Once it gets the list of URLs, forms, and their inputs, Wapiti acts like a fuzzer, injecting payloads to see if a script is vulnerable. Search for potentially dangerous files on the server. Wapiti supports both GET and POST HTTP methods for attacks. It also supports multipart forms and can inject payloads in filenames (upload). Warnings are raised when an anomaly is found (for example 500 errors and timeouts). Wapiti is able to make the difference between permanent and reflected XSS vulnerabilities. Generates vulnerability reports in various formats (HTML, XML, JSON, TXT, CSV).Starting Price: Free -
6
ToothPicker
Secure Mobile Networking Lab
ToothPicker is an in-process, coverage-guided fuzzer for iOS. It was developed to specifically target iOS's Bluetooth daemon and to analyze various Bluetooth protocols on iOS. As it is built using FRIDA, it can be adapted to target any platform that runs FRIDA. This repository also includes an over-the-air fuzzer with an exemplary implementation to fuzz Apple's MagicPairing protocol using InternalBlue. Additionally, it contains the ReplayCrashFile script that can be used to verify crashes the in-process fuzzer has found. This is a very simple fuzzer that only flips bits and bytes of inactive connections. No coverage, no injection, but nice as a demo and stateful. Runs just with Python and Frida, no modules or installation are required. ToothPicker is built on the codebase of frizzer. It is recommended to set up a virtual Python environment for frizzer. Starting from the iPhone XR/Xs, PAC has been introduced.Starting Price: Free -
7
Sulley
OpenRCE
Sulley is a fuzzing engine and fuzz testing framework consisting of multiple extensible components. Sulley (IMHO) exceeds the capabilities of most previously published fuzzing technologies, commercial and public domain. The goal of the framework is to simplify not only data representation but to simplify data transmission and instrumentation. A pure-Python fully automated and unattended fuzzing framework. Sulley not only has impressive data generation but has taken this a step further and includes many other important aspects a modern fuzzer should provide. Sulley watches the network and methodically maintains records. Sulley instruments and monitors the health of the target, capable of reverting to a known good state using multiple methods. Sulley detects, tracks, and categorizes detected faults. Sulley can fuzz in parallel, significantly increasing test speed. Sulley can automatically determine what unique sequence of test cases triggers faults.Starting Price: Free -
8
WebReaver
Websecurify
WebReaver is an elegant, easy to use and fully-automated, web application security security testing tool for Mac, Windows and Linux, suitable for novice as well as advanced users. WebReaver allows you easily test any web application for a large variety of web vulnerabilities from the sever kinds such as SQL Injection, local and remote file Includes, command Injection, cross-site scripting and expression Injection to the less severe ones such as variety of session and headers problems, information leakage and many more. Automated security testing technologies, such as those, which rely on scanning, fuzzing, sending arbitrary malicious data to detect security defects, can seriously damage the web applications they are used against. Therefore, it is often recommended to perform automated tests only against systems in demo, testing or pre-production environments. -
9
LibFuzzer
LLVM Project
LibFuzzer is an in-process, coverage-guided, evolutionary fuzzing engine. LibFuzzer is linked with the library under test, and feeds fuzzed inputs to the library via a specific fuzzing entry point (or target function); the fuzzer then tracks which areas of the code are reached, and generates mutations on the corpus of input data in order to maximize the code coverage. The code coverage information for libFuzzer is provided by LLVM’s SanitizerCoverage instrumentation. LibFuzzer is still fully supported in that important bugs will get fixed. The first step in using libFuzzer on a library is to implement a fuzz target, a function that accepts an array of bytes and does something interesting with these bytes using the API under test. Note that this fuzz target does not depend on libFuzzer in any way so it is possible and even desirable to use it with other fuzzing engines like AFL and/or Radamsa.Starting Price: Free -
10
Awesome Fuzzing
secfigo
Awesome Fuzzing is a list of fuzzing resources including books, courses, both free and paid, videos, tools, tutorials, and vulnerable applications to practice in order to learn fuzzing and initial phases of exploit development like root cause analysis. Courses/training videos on fuzzing, videos talking about fuzzing techniques, tools, and best practices. Conference talks and tutorials, blogs, tools that help in fuzzing applications, and fuzzers that help in fuzzing applications that use network-based protocols like HTTP, SSH, SMTP, etc. Search and pick the exploits, that have respective apps available for download, and reproduce the exploit by using the fuzzer of your choice. Set of tests for fuzzing engines. Includes different well-known bugs. A corpus, including various file formats for fuzzing multiple targets in the fuzzing literature.Starting Price: Free -
11
ClusterFuzz
Google
ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection. -
12
Google ClusterFuzz
Google
ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection.Starting Price: Free -
13
go-fuzz
dvyukov
Go-fuzz is a coverage-guided fuzzing solution for testing Go packages. Fuzzing is mainly applicable to packages that parse complex inputs (both text and binary) and is especially useful for hardening systems that parse inputs from potentially malicious users (anything accepted over a network). go-fuzz has recently added preliminary support for fuzzing Go Modules. If you encounter a problem with modules, please file an issue with details. Data is a random input generated by go-fuzz, note that in most cases it is invalid. The function must return 1 if the fuzzer should increase the priority of the given input during subsequent fuzzing if the input must not be added to the corpus even if it gives new coverage, and 0 otherwise; other values are reserved for future use. The fuzz function must be in a package that go-fuzz can import. This means the code you want to test can't be in package main. Fuzzing internal packages is supported, however.Starting Price: Free -
14
Google OSS-Fuzz
Google
OSS-Fuzz offers continuous fuzzing for open source software. Fuzz testing is a well-known technique for uncovering programming errors in software. Many of these detectable errors, like buffer overflow, can have serious security implications. Google has found thousands of security vulnerabilities and stability bugs by deploying guided in-process fuzzing of Chrome components, and we now want to share that service with the open source community. OSS-Fuzz aims to make common open source software more secure and stable by combining modern fuzzing techniques with scalable, distributed execution. Projects that do not qualify for OSS-Fuzz can run their own instances of ClusterFuzz or ClusterFuzzLite. Currently, OSS-Fuzz supports C/C++, Rust, Go, Python, and Java/JVM code. Other languages supported by LLVM may work too. OSS-Fuzz supports fuzzing x86_64 and i386 builds.Starting Price: Free -
15
APIFuzzer
PyPI
APIFuzzer reads your API description and step-by-step fuzzes the fields to validate if your application can cope with the fuzzed parameters, and it does not require coding. Parse API definition from a local file or remote URL. JSON and YAML file format support. All HTTP methods are supported. Fuzzing of the request body, query string, path parameter, and request header is supported. Relies on random mutations and supports CI integration. Generate JUnit XML test report format. Send a request to an alternative URL. Support HTTP basic auth from the configuration. Save the report of the failed test in JSON format into the pre-configured folder.Starting Price: Free -
16
Solidity Fuzzing Boilerplate
patrickd
Solidity Fuzzing Boilerplate is a template repository intended to ease fuzzing components of Solidity projects, especially libraries. Write tests once and run them with both Echidna and Foundry's fuzzing. Fuzz components that use incompatible Solidity versions by deploying those into a Ganache instance via Etheno. Use HEVM's FFI cheat code to generate complex fuzzing inputs or to compare outputs with non-EVM executables while doing differential fuzzing. Publish your fuzzing experiments without worrying about licensing by extending the shell script to download specific files. Turn off FFI if you don't intend to make use of shell commands from your Solidity contracts. Note that FFI is slow and should only be used as a workaround. It can be useful for testing against things that are difficult to implement within Solidity and already exist in other languages. Before executing tests of a project that has FFI enabled, be sure to check what commands are actually being executed.Starting Price: Free -
17
Peach Fuzzer
Peach Tech
Peach is a SmartFuzzer that is capable of performing both generation and mutation-based fuzzing. Peach requires the creation of Peach Pit files that define the structure, type information, and relationships in the data to be fuzzed. It additionally allows for the configuration of a fuzzing run including selecting a data transport (publisher), logging interface, etc. Peach has been under active development since 2004 and is in its third major version. Fuzzing continues to be the fastest way to find security issues and test for bugs. Effective hardware fuzzing with Peach will introduce students to the fundamentals of device fuzzing. Peach was designed to fuzz any type of data consumer from servers to embedded devices. Researchers, corporations, and governments already use Peach to find vulnerabilities in hardware. This course will focus on using Peach to target embedded devices and collect information from the device in the event of a crash.Starting Price: Free -
18
Fuzzbuzz
Fuzzbuzz
The Fuzzbuzz workflow is very similar to other CI/CD testing workflows. However, unlike other testing workflows, fuzz testing requires multiple jobs to run simultaneously, which results in a few extra steps. Fuzzbuzz is a fuzz testing platform. We make it trivial for developers to add fuzz tests to their code and run them in CI/CD, helping them catch critical bugs and vulnerabilities before they hit production. Fuzzbuzz completely integrates into your environment, following you from the terminal to CI/CD. Write a fuzz test in your environment and use your own IDE, terminal, or build tools. Push to CI/CD and Fuzzbuzz will automatically start running your fuzz tests against your latest code changes. Get notified when bugs are found through Slack, GitHub, or email. Catch regressions as new changes are automatically tested and compared to previous runs. Code is built and instrumented by Fuzzbuzz as soon as a change is detected.Starting Price: Free -
19
Echidna
Crytic
Echidna is a Haskell program designed for fuzzing/property-based testing of Ethereum smart contracts. It uses sophisticated grammar-based fuzzing campaigns based on a contract ABI to falsify user-defined predicates or Solidity assertions. We designed Echidna with modularity in mind, so it can be easily extended to include new mutations or test specific contracts in specific cases. Generates inputs tailored to your actual code. Optional corpus collection, mutation and coverage guidance to find deeper bugs. Powered by Slither to extract useful information before the fuzzing campaign. Source code integration to identify which lines are covered after the fuzzing campaign. Interactive terminal UI, text-only or JSON output. Automatic test case minimization for quick triage. Seamless integration into the development workflow. Maximum gas usage reporting of the fuzzing campaign. Support for a complex contract initialization with Etheno and Truffle.Starting Price: Free -
20
BFuzz
RootUp
BFuzz is an input-based fuzzer tool that takes HTML as an input, opens up your browser with a new instance, and passes multiple test cases generated by domato which is present in the recurve folder of BFuzz, more over BFuzz is an automation that performs the same task repeatedly and it doesn't mangle any test cases. Running BFuzz will ask for the option of whether to fuzz Chrome or Firefox, however, this will open Firefox from recurve and create the logs on the terminal. BFuzz is a small script that enables you to open the browser and run test cases. The test cases in recurve are generated by the domato generator and contain the main script. It contains additional helper code for DOM fuzzing.Starting Price: Free -
21
Honggfuzz
Google
Honggfuzz is a security-oriented software fuzzer. Supports evolutionary, feedback-driven fuzzing based on code coverage (SW and HW-based). It’s multi-process and multi-threaded, there’s no need to run multiple copies of your fuzzer, as Honggfuzz can unlock the potential of all your available CPU cores with a single running instance. The file corpus is automatically shared and improved between all fuzzed processes. It’s blazingly fast when the persistent fuzzing mode is used. A simple/empty LLVMFuzzerTestOneInput function can be tested with up to 1mo iteration per second on a relatively modern CPU. Has a solid track record of uncovered security bugs, the only (to date) vulnerability in OpenSSL with the critical score mark was discovered by Honggfuzz. As opposed to other fuzzers, it will discover and report hijacked/ignored signals from crashes (intercepted and potentially hidden by a fuzzed program).Starting Price: Free -
22
AWS Fault Injection Service
Amazon
Find performance bottlenecks or other unknown weaknesses missed by traditional software tests. Define specific conditions to stop an experiment or roll back to the pre-experiment state. Run experiments in minutes using pre-built scenarios from the FIS scenario library. Get superior insights by generating real-world failure conditions, such as impaired performance of different resources. Part of AWS Resilience Hub, AWS Fault Injection Service (FIS) is a fully managed service for running fault injection experiments to improve an application’s performance, observability, and resilience. FIS simplifies the process of setting up and running controlled fault injection experiments across a range of AWS services, so teams can build confidence in their application behavior. FIS provides the controls and guardrails that teams need to run experiments in production, such as automatically rolling back or stopping the experiment if specific conditions are met.Starting Price: $0.10 per action-minute -
23
GPT GES
GPT
Block H125 mainly develops Qingshankou oil layer. The top structure of the Qing 1st sublayer is a broken nose structure blocked by reverse normal faults. The reservoir type is a layered lithological structure reservoir. The current injection-production scale is an encryption five-point well pattern, including 27 injection wells and 38 production wells. The main target layers in the north of Block H125 are delta front deposits. The main microfacies types of each sublayer are bars. Reservoir geological modeling technology is mainly divided into two major workflows structural modeling and property modeling. The property modeling includes sedimentary facies modeling, porosity modeling, permeability modeling, oil saturation modeling, and NTG modeling. In geological modeling, the first step is to use the well header and well picks to establish a structural model and to set the increment in I and J direction to control the grid quality and well pattern. -
24
Mayhem
ForAllSecure
Advanced fuzzing solution that combines guided fuzzing with symbolic execution, a patented technology from CMU. Mayhem is an advanced fuzz testing solution that dramatically reduces manual testing efforts with autonomous defect detection and validation. Deliver safe, secure, reliable software with less time, cost, and effort. Mayhem’s unique advantage is in its ability to acquire intelligence of its targets over time. As Mayhem’s knowledge grows, it deepens its analysis and maximizes its code coverage. All reported vulnerabilities are exploitable, confirmed risks. Mayhem guides remediation efforts with in-depth system level information, such as backtraces, memory logs, and register state, expediting issue diagnosis and fixes. Mayhem utilizes target feedback to custom generate test cases on the fly -- meaning no manual test case generation required. Mayhem offers access to all of its test cases to make regression testing effortless and continuous. -
25
american fuzzy lop
Google
American fuzzy lop is a security-oriented fuzzer that employs a novel type of compile-time instrumentation and genetic algorithms to automatically discover clean, interesting test cases that trigger new internal states in the targeted binary. This substantially improves the functional coverage for the fuzzed code. The compact synthesized corpora produced by the tool are also useful for seeding other, more labor or resource-intensive testing regimes down the road. Compared to other instrumented fuzzers, afl-fuzz is designed to be practical, it has a modest performance overhead, uses a variety of highly effective fuzzing strategies and effort minimization tricks, requires essentially no configuration, and seamlessly handles complex, real-world use cases, say, common image parsing or file compression libraries. It's an instrumentation-guided genetic fuzzer capable of synthesizing complex file semantics in a wide range of non-trivial targets.Starting Price: Free -
26
Atheris
Google
Atheris is a coverage-guided Python fuzzing engine. It supports fuzzing of Python code, but also native extensions written for CPython. Atheris is based on libFuzzer. When fuzzing native code, Atheris can be used to catch extra bugs. Atheris supports Linux (32- and 64-bit) and Mac OS X, with Python versions 3.6-3.10. It comes with a built-in libFuzzer, which is fine for fuzzing Python code. If you plan to fuzz native extensions, you may need to build from source to ensure the libFuzzer version in Atheris matches your Clang version. Atheris relies on libFuzzer, which is distributed with Clang. Apple Clang doesn't come with libFuzzer, so you'll need to install a new version of LLVM. Atheris is based on a coverage-guided mutation-based fuzzer (LibFuzzer). This has the advantage of not requiring any grammar definition for generating inputs, making its setup easier. The disadvantage is that it will be harder for the fuzzer to generate inputs for code that parses complex data types.Starting Price: Free -
27
PHP Secure
PHP Secure
PHP Secure is a FREE code scanner that analyzes your PHP code for critical security vulnerabilities. Free online scanner: - Quickly and qualitatively finds web app vulnerabilities - Gives explicit reports and recommendations to fix vulnerabilities - Easy to use and requires no specialized knowledge - Reduces risk, saves budget, and boosts productivity PHP Secure Scanner is suitable for analyzing sites on Php, framework Laravel, and CMS Wordpress, Drupal and Joomla. PHP Secure detects the most common and dangerous types: -SQL injection vulnerabilities -Command Injection -Cross-Site Scripting (XSS) Vulnerabilities -PHP Serialize Injections -Remote Code Executions -Double Escaping -Directory Traversal -Regular Expression Denial of Service (ReDos) -
28
afl-unicorn
Battelle
afl-unicorn lets you fuzz any piece of binary that can be emulated by Unicorn Engine. If you can emulate the code you’re interested in using the Unicorn Engine, you can fuzz it with afl-unicorn. Unicorn Mode works by implementing the block-edge instrumentation that AFL’s QEMU mode normally does into Unicorn Engine. Basically, AFL will use block coverage information from any emulated code snippet to drive its input generation. The whole idea revolves around the proper construction of a Unicorn-based test harness. The Unicorn-based test harness loads the target code, sets up the initial state, and loads in data mutated by AFL from disk. The test harness then emulates the target binary code, and if it detects that a crash or error occurred it throws a signal. AFL will do all its normal stuff, but it’s actually fuzzing the emulated target binary code. Only tested on Ubuntu 16.04 LTS, but it should work smoothly with any OS capable of running both AFL and Unicorn.Starting Price: Free -
29
BlackArch Fuzzer
BlackArch
BlackArch is a Linux pentesting distribution based on ArchLinux. BlackArch Fuzzer provides packages that use the fuzz testing principle. -
30
Boofuzz
Boofuzz
Boofuzz is a fork of and the successor to the venerable Sulley fuzzing framework. Besides numerous bug fixes, Boofuzz aims for extensibility. Like Sulley, Boofuzzincorporates all the critical elements of a fuzzer like easy and quick data generation, instrumentation and failure detection, target reset after failure, and recording of test data. Much easier install experience and support for arbitrary communications mediums. Built-in support for serial fuzzing, ethernet- and IP-layer, UDP broadcast. Better recording of test data, consistent, thorough, and clear. Test result CSV export and extensible instrumentation/failure detection. Boofuzz installs as a Python library used to build fuzzer scripts. It is strongly recommended to set up Boofuzz in a virtual environment.Starting Price: Free -
31
Code Intelligence
Code Intelligence
Our platform uses various security techniques, including coverage-guided and feedback-based fuzz testing, to automatically generate millions of test cases that trigger hard-to-find bugs deep within your application. This white-box approach protects against edge cases and speeds up development. Advanced fuzzing engines generate inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Uncover true vulnerabilities only. Get the input and stack trace as proof, so you can reliably reproduce errors every time. AI white-box testing uses data from all previous test runs to continuously learn the inner-workings of your application, triggering security-critical bugs with increasingly high precision. -
32
Fuzzing Project
Fuzzing Project
Fuzzing is a powerful strategy to find bugs in software. The idea is quite simple, which is to generate a large number of randomly malformed inputs for the software to parse and see what happens. If the program crashes then something is likely wrong. While fuzzing is a well-known strategy, it is surprisingly easy to find bugs, often with security implications, in widely used software. Memory access errors are the errors most likely to be exposed when fuzzing software that is written in C/C++. While they differ in the details, the core problem is often the same, the software reads or writes to the wrong memory locations. A modern Linux or BSD system ships a large number of basic tools that do some kind of file displaying and parsing. In their current state, most of these tools are not suitable for untrusted inputs. On the other hand, we have powerful tools these days that allow us to find and analyze these bugs.Starting Price: Free -
33
IDLive Face Plus
ID R&D
IDLive Face Plus complements IDLive Face presentation attack detection with injection attack detection, providing comprehensive protection from deepfakes and other types of fraudulent digital imagery. Detect injection attacks that use virtual and external cameras. Prevent browser JavaScript code modifications on both desktops and mobile devices. Prevent man-in-the-middle replay attacks. Protect from emulators, cloning apps, and other software used for fraud. Improve presentation attack detection performance. Facial recognition security relies on presentation attack detection (PAD) to ensure that a biometric selfie is not actually a fraudster presenting a non-live facial image to the camera, such as a printed copy, screen replay, or 3D mask. IDLive Face Plus combines award-winning presentation attack detection with a unique approach to injection attack detection to prevent deepfakes and other fraudulent digital content. -
34
Huawei Database Security Service (DBSS)
Huawei Cloud
Database Security Service (DBSS) uses machine learning and big data technologies to protect your databases on the cloud, intelligently auditing them and detecting risky behaviors like SQL injection. Purchase and get started with DBSS quickly without the need to manually install the service or adapt your database configurations. DBSS complies with the HIPAA, SOX, and PCI DSS, meeting your auditing requirements. Take advantage of algorithm models to detect SQL injection and abnormal behaviors, fast and accurate. DBSS works in bypass mode, having zero impact on your business. A wide range of policies are available to help you detect SQL injection and audit database behaviors. Monitor databases and detect anomalies in performance, data, and user actions. Audit reports are customized for different scenarios (pre-event and post-event) and roles (common users and administrators). Perform comprehensive database audit to comply with laws and regulation. -
35
syzkaller
Google
syzkaller is an unsupervised coverage-guided kernel fuzzer. Supports FreeBSD, Fuchsia, gVisor, Linux, NetBSD, OpenBSD, and Windows. Initially, syzkaller was developed with Linux kernel fuzzing in mind, but now it's being extended to support other OS kernels as well. Once syzkaller detects a kernel crash in one of the VMs, it will automatically start the process of reproducing this crash. By default, it will use 4 VMs to reproduce the crash and then minimize the program that caused it. This may stop the fuzzing, since all of the VMs might be busy reproducing detected crashes. The process of reproducing one crash may take from a few minutes up to an hour depending on whether the crash is easily reproducible or non-reproducible at all.Starting Price: Free -
36
MockLab
MockLab
Craft your simulation using the friendly, no-code UI or go fully automated with the 100% WireMock-compatible API. Simulate stateful behaviour in your mocked API using a simple finite state machine model. Test your app to destruction by injecting delays, dropped connections, drip-drip responses and corrupt HTTP payloads. A MockLab plan's collaborator limit is the total number of individual collaborators + team members that can be added by the owning account so e.g. if your subscription has a collaborator limit of 2, this means that you and 2 colleagues can work on your APIs. Test your app to destruction by injecting delays, dropped connections, drip-drip responses and corrupt HTTP payloads.Starting Price: $29 per month -
37
NoPromptInjections
NoPromptInjections
AI apps are all the rage these days, but with them comes a new security danger: prompt injections. Similarly to code injections, they allow nefarious alteration of an app's function. The NoPromptInjection API allows developers to easily protect their apps. -
38
MockK
MockK
Mocking is a technique to make testing code readable and maintainable. In three consequent articles, I would like to show the basics, features, and quirks of the MockK library. It is a new open-source library (github repository) focused on making mocking in Kotlin great. Injection first tries to match properties by name, then by class or superclass. Check the lookupType parameter for customization. Properties are injected even if private is applied. Constructors for injection are selected from the biggest number of arguments to lowest.Starting Price: Free -
39
beSTORM
Beyond Security (Fortra)
Discover code weaknesses and certify the security strength of any product without access to source code. Test any protocol or hardware with beSTORM, even those used in IoT, process control, CANbus compatible automotive and aerospace. Realtime fuzzing, doesn’t need access to the source code, no cases to download. One platform, one GUI to learn, with over 250+ prebuilt protocol testing modules and the ability to add custom and proprietary ones. Find the security weaknesses before deployment that are most often discovered by external actors after release. Certify vendor components and your own applications in your own testing center. Self-learning software module and propriety software testing. Customization and scalability for any business sizes up or down. Automatically generate and deliver near-infinite attack vectors and document any product failures. Record every pass/fail and hand engineering the exact command that produced each fail.Starting Price: $50,000.00/one-time -
40
Injective
Injective Labs
Create any financial market on Injective’s fast, cross-chain, low fee, secure, and fully decentralized exchange protocol. Injective revamps the traditional DEX model to create a protocol that is easy to use for both novice and advanced traders alike. Execute sophisticated trades in seconds with instant transaction finality. Trade as much as you want without any gas fees. Injective is able to avoid both network congestion and the associated high gas fees. You have the power to create any crypto or synthetic market of your choice on Injective. You can transact any asset of your choice without any friction across sovereign blockchain networks. Injective offers everyone the same familiar trading experience as centralized exchanges while remaining entirely decentralized. All transactions are secured by Tendermint-based proof-of-stake consensus and achieve instant finality. -
41
Koin
Kotzilla
Koin simplifies DI and empowers developers in the Kotlin landscape. Koin helps you build any kind of Kotlin & Kotlin multiplatform application, from Android mobile to backend Ktor server applications. Koin is built for the most demanding apps and is trusted by developers worldwide. Koin is an open source dependency injection framework tailored for Kotlin developers. With its intuitive DSL and lightweight container, Koin simplifies dependency injection for any Kotlin application and SDK. Koin framework lets you build your dependency injection in a breeze, with simple API and Kotlin DSL. Koin can help you create complex Android mobile applications, so you can focus on your business, not your tools. Koin connects on top of the Kotlin ecosystem. Using the power of Kotlin, Koin provides easy dependency injection across multiple platforms. Already used by thousands of companies in the world, Koin is ready to scale in production.Starting Price: Free -
42
sqlmap
sqlmap
sqlmap is an open source penetration testing tool that automates the process of detecting and exploiting SQL injection flaws and taking over of database servers. It comes with a powerful detection engine, many niche features for the ultimate penetration tester and a broad range of switches lasting from database fingerprinting, over data fetching from the database, to accessing the underlying file system and executing commands on the operating system via out-of-band connections. Support to directly connect to the database without passing via a SQL injection, by providing DBMS credentials, IP address, port and database name. Automatic recognition of password hash formats and support for cracking them using a dictionary-based attack. Support to dump database tables entirely, a range of entries or specific columns as per user's choice. The user can also choose to dump only a range of characters from each column's entry. -
43
Vega
Subgraph
Vega can help you find and validate SQL Injection, cross-site scripting, inadvertently disclosed sensitive information, and other vulnerabilities. It is written in Java, GUI based, and runs on Linux, OS X, and Windows. Vega can help you find vulnerabilities such as: reflected cross-site scripting, stored cross-site scripting, blind SQL injection, remote file include, shell injection, and others. Vega also probes for TLS / SSL security settings and identifies opportunities for improving the security of your TLS servers. Vega includes an automated scanner for quick tests and an intercepting proxy for tactical inspection. The Vega scanner finds, SQL injection, and other vulnerabilities. Vega includes a website crawler powering its automated scanner. Vega can automatically log into websites when supplied with user credentials. -
44
WebOrion Protector Plus
cloudsineAI
WebOrion Protector Plus is a GPU-powered GenAI firewall engineered to provide mission-critical protection for generative AI applications. It offers real-time defenses against evolving threats such as prompt injection attacks, sensitive data leakage, and content hallucinations. Key features include prompt injection attack protection, safeguarding intellectual property and personally identifiable information (PII) from exposure, content moderation and validation to ensure accurate and on-topic LLM responses, and user input rate limiting to mitigate risks of security vulnerability exploitation and unbounded consumption. At the core of its capabilities is ShieldPrompt, a multi-layered defense system that utilizes context evaluation through LLM analysis of user prompts, canary checks by embedding fake prompts to detect potential data leaks, pand revention of jailbreaks using Byte Pair Encoding (BPE) tokenization with adaptive dropout. -
45
Lakera
Lakera
Lakera Guard empowers organizations to build GenAI applications without worrying about prompt injections, data loss, harmful content, and other LLM risks. Powered by the world's most advanced AI threat intelligence. Lakera’s threat intelligence database contains tens of millions of attack data points and is growing by 100k+ entries every day. With Lakera guard, your defense continuously strengthens. Lakera guard embeds industry-leading security intelligence at the heart of your LLM applications so that you can build and deploy secure AI systems at scale. We observe tens of millions of attacks to detect and protect you from undesired behavior and data loss caused by prompt injection. Continuously assess, track, report, and responsibly manage your AI systems across the organization to ensure they are secure at all times. -
46
SpecFlow
SpecFlow
SpecFlow makes test automation easier by turning it into a team effort and allowing every role to better use their skills. Don’t waste your time searching for the correct definition across your binding classes, just right-click and jump to the relevant code. Hooks (event bindings) can be used to perform additional automation logic at specific times, such as any setup required prior to executing a scenario. SpecFlow supports a dependency injection framework that is able to instantiate and inject context for scenarios. This allows you to group the shared state in context classes, and inject them into every binding class that needs access to that shared state.Starting Price: Free -
47
Code VAUCH
VAUCH Information Technology Private Limited
Generates very clean code with proper comments. Also it uses the template design pattern, that can be extended for dependency injection. The code is generated in a proper object-oriented structure so that it can be injected with any design. Automatically generates the detail log with a timestamp. First is the Activity Log, which tracks add, update and delete operations for each user. Second is Error Log, which tracks all application errors with deep dive till code method. Third is Debug Log, tracks step by step reach progress. Code VAUCH will generate the UI layer with responsive design using bootstrap, so you can view your application in any device. Also bootstrap gives you an advantage that you can change the theme of your application in only one CSS. Powerful tool to generate your code with CRUD operations, dashboards, reports in one click with database first approach. -
48
Defensics Fuzz Testing
Black Duck
Defensics Fuzz Testing is a comprehensive, versatile, automated black box fuzzer that enables organizations to efficiently and effectively discover and remediate security weaknesses in software. The generational fuzzer takes an intelligent, targeted approach to negative testing. Advanced file and protocol template fuzzers enable users to build their own test cases. The SDK allows expert users to use the Defensics framework to develop their own test cases. Defensics is a black box fuzzer, meaning it doesn’t require source code to run. With Defensics, users can secure their cyber supply chain to ensure the interoperability, robustness, quality, and security of software and devices before introducing them into IT or lab environments. Defensics fits nearly any development workflow, whether in a traditional SDL or CI environment. Its API and data export capabilities also enable it to integrate with surrounding technologies, making it a true plug-and-play fuzzer. -
49
XBOW
XBOW
XBOW is an AI-powered offensive security platform that autonomously discovers, verifies, and exploits vulnerabilities in web applications without human intervention. By executing high-level commands against benchmark descriptions and reviewing outputs it solves a wide array of challenges, from CBC padding oracle and IDOR attacks to remote code execution, blind SQL injection, SSTI bypasses, and cryptographic exploits, achieving success rates up to 75 percent on standard web security benchmarks. Given only general instructions, XBOW orchestrates reconnaissance, exploit development, debugging, and server-side analysis, drawing on public exploits and source code to craft custom proofs-of-concept, validate attack vectors, and generate detailed exploit traces with full audit trails. Its ability to adapt to novel and modified benchmarks demonstrates robust scalability and continuous learning, dramatically accelerating penetration-testing workflows. -
50
Jazzer
Code Intelligence
Jazzer is a coverage-guided, in-process fuzzer for the JVM platform developed by Code Intelligence. It is based on libFuzzer and brings many of its instrumentation-powered mutation features to the JVM. You can use Docker to try out Jazzer's autofuzz mode, which automatically generates arguments to a given Java function and reports unexpected exceptions and detected security issues. You can also use GitHub release archives to run a standalone Jazzer binary that starts its own JVM configured for fuzzing.Starting Price: Free
