Best AI tools for< Detect Bugs >

Greptile is an AI tool designed to assist developers in code review processes. It integrates with GitHub to review pull requests and identify bugs, antipatterns, and other issues in the codebase. By leveraging AI technology, Greptile aims to streamline the code review process and improve code quality.

The website seems to be experiencing an application error, which indicates a technical issue with the application. It may be a temporary problem that needs to be resolved by the website's developers. An application error can occur due to various reasons such as bugs in the code, server issues, or database problems. Users encountering this error may need to refresh the page, clear their cache, or contact the website's support team for assistance.

Refraction is a code generation tool that uses AI to help developers write better code. It can be used to generate unit tests, documentation, refactor code, and more. Refraction is designed for developers of all levels and can be used with a variety of programming languages and frameworks.

Senior AI is a platform that leverages Artificial Intelligence to help individuals and companies develop and manage software products more efficiently and securely. It offers codebase awareness, bug analysis, security optimization, and productivity enhancements, making software development faster and more reliable. The platform provides different pricing tiers suitable for individuals, power users, small teams, growing teams, and large teams, with the option for enterprise solutions. Senior AI aims to supercharge software development with an AI-first approach, guiding users through the development process and providing tailored code suggestions and security insights.

Trag is an AI-powered tool designed to review pull requests in minutes, empowering engineering teams to save time and focus on building products. With Trag, users can create custom patterns for code review, ensuring best practices are followed and bugs are caught early. The tool offers features like autofix with AI, monitoring progress, connecting multiple repositories, pull request review, analytics, and team workspaces. Trag stands out from traditional linters by providing complex code understanding, semantic code analysis, predictive bug detection, and refactoring suggestions. It aims to streamline code reviews and help teams ship faster with AI-powered reviews.

Anecdote is a customer feedback analytics hub that leverages automated AI tagging and precision NLP clustering to help businesses uncover product insights, detect bugs, analyze competitor feedback, and provide real-time feedback alerts. The platform offers semantic search, survey analysis, and integrates with over 65 sources to deliver accurate clusters from customer feedback. Anecdote is used by top customer-centric companies to save time, improve customer experiences, and track feedback in multiple languages securely.

Wasps is an AI code review tool that integrates seamlessly into VSCode, providing developers with a fast and efficient way to understand their codebase, detect and fix code issues using AI and Gitsecure. With Wasps, developers can identify and fix buggy & vulnerable code in minutes, receive clear and actionable feedback driven by deep analysis, and get recommendations for potential issues and improvements within their codebase. The tool allows developers to keep coding as usual while Wasps analyzes their code for them, making it easier to maintain code quality and keep bugs out of their code.

Refraction is an AI-powered code generation tool designed to help developers learn, improve, and generate code effortlessly. It offers a wide range of features such as bug detection, code conversion, function creation, CSP generation, CSS style conversion, debug statement addition, diagram generation, documentation creation, code explanation, code improvement, concept learning, CI/CD pipeline creation, SQL query generation, code refactoring, regex generation, style checking, type addition, and unit test generation. With support for 56 programming languages, Refraction is a versatile tool trusted by innovative companies worldwide to streamline software development processes using the magic of AI.

GiteAI is an AI-powered tool designed to enhance collaboration and productivity for software development teams. It leverages machine learning algorithms to automate code reviews, identify bugs, and suggest improvements in real-time. With GiteAI, developers can streamline their workflow, reduce manual efforts, and ensure code quality. The platform integrates seamlessly with popular version control systems like GitHub, GitLab, and Bitbucket, providing actionable insights and analytics to drive continuous improvement.

Evinced is an AI-powered accessibility tool that helps developers identify and address accessibility issues in websites and mobile apps. By utilizing AI and machine learning, Evinced can automatically find, cluster, and track accessibility problems that would typically require manual audits. The tool provides a comprehensive solution for developers to ensure their digital products are accessible to all users. Evinced offers features such as advanced bug detection, organization of issues, lifecycle tracking, easy integration with existing testing systems, and more.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

Slips is a powerful endpoint behavioral intrusion prevention and detection system that uses machine learning to detect malicious behaviors in network traffic. It can work with network traffic in real-time, PCAP files, and network flows from tools like Suricata, Zeek/Bro, and Argus. Slips threat detection is based on machine learning models, threat intelligence feeds, and expert heuristics. It gathers evidence of malicious behavior and triggers alerts when enough evidence is accumulated. The tool is Python-based and supported on Linux and MacOS, with blocking features only on Linux. Slips relies on Zeek network analysis framework and Redis for interprocess communication. It offers a graphical user interface for easy monitoring and analysis.

CredSweeper is a tool designed to detect credentials like tokens, passwords, and API keys in directories or files. It helps users identify potential exposure of sensitive information by scanning lines, filtering, and utilizing an AI model. The tool reports lines containing possible credentials, their location, and the expected type of credential.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

WP-Autoplugin is a free WordPress plugin that uses AI to assist in generating, fixing, and extending plugins on-demand. It enables users to quickly create functional plugins from simple descriptions, addressing specific needs without unnecessary bloat. Users can generate plugins using AI, fix and extend existing plugins, have full control over the generation process, view the list of generated plugins for easy management, and auto-detect fatal errors. The plugin offers practical solutions for creating lightweight alternatives, custom solutions, and developer foundations. It supports various AI models like GPT-3.5 Turbo, GPT-4, Claude 3.5 Sonnet, Google Gemini Flash 2.0, xAI Grok-beta, and more. WP-Autoplugin is completely free, open-source, privacy-focused, and allows users to bring their own API key for AI usage.

AIDE (Advanced Intrusion Detection Environment) is a tool for monitoring file system changes. It can be used to detect unauthorized changes to monitored files and directories. AIDE was written to be a simple and free alternative to Tripwire. Features currently included in AIDE are as follows: o File attributes monitored: permissions, inode, user, group file size, mtime, atime, ctime, links and growing size. o Checksums and hashes supported: SHA1, MD5, RMD160, and TIGER. CRC32, HAVAL and GOST if Mhash support is compiled in. o Plain text configuration files and database for simplicity. o Rules, variables and macros that can be customized to local site or system policies. o Powerful regular expression support to selectively include or exclude files and directories to be monitored. o gzip database compression if zlib support is compiled in. o Free software licensed under the GNU General Public License v2.

Claude Code Neovim Plugin is a seamless integration between Claude Code AI assistant and Neovim. It allows users to toggle Claude Code in a terminal window with a single key press, automatically detect and reload files modified by Claude Code, provide real-time buffer updates when files are changed externally, offer customizable window position and size, integrate with which-key, use git project root as working directory, maintain a modular code structure, provide type annotations with LuaCATS for better IDE support, offer configuration validation, and include a testing framework for reliability. The plugin creates a terminal buffer running the Claude Code CLI, sets up autocommands to detect file changes on disk, automatically reloads files modified by Claude Code, provides keymaps and commands for toggling the terminal, and detects git repositories to set the working directory to the git root.

Dataflow-oriented robotic application (dora-rs) is a framework that makes creation of robotic applications fast and simple. Building a robotic application can be summed up as bringing together hardwares, algorithms, and AI models, and make them communicate with each others. At dora-rs, we try to: make integration of hardware and software easy by supporting Python, C, C++, and also ROS2. make communication low latency by using zero-copy Arrow messages. dora-rs is still experimental and you might experience bugs, but we're working very hard to make it stable as possible.

This repository contains Refact WebUI for fine-tuning and self-hosting of code models, which can be used inside Refact plugins for code completion and chat. Users can fine-tune open-source code models, self-host them, download and upload Lloras, use models for code completion and chat inside Refact plugins, shard models, host multiple small models on one GPU, and connect GPT-models for chat using OpenAI and Anthropic keys. The repository provides a Docker container for running the self-hosted server and supports various models for completion, chat, and fine-tuning. Refact is free for individuals and small teams under the BSD-3-Clause license, with custom installation options available for GPU support. The community and support include contributing guidelines, GitHub issues for bugs, a community forum, Discord for chatting, and Twitter for product news and updates.

The 'llm-misinformation-survey' repository is dedicated to the survey on combating misinformation in the age of Large Language Models (LLMs). It explores the opportunities and challenges of utilizing LLMs to combat misinformation, providing insights into the history of combating misinformation, current efforts, and future outlook. The repository serves as a resource hub for the initiative 'LLMs Meet Misinformation' and welcomes contributions of relevant research papers and resources. The goal is to facilitate interdisciplinary efforts in combating LLM-generated misinformation and promoting the responsible use of LLMs in fighting misinformation.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

Ultralytics YOLO for Flutter is a Flutter plugin that allows you to integrate Ultralytics YOLO computer vision models into your mobile apps. It supports both Android and iOS platforms, providing APIs for object detection and image classification. The plugin leverages Flutter Platform Channels for seamless communication between the client and host, handling all processing natively. Before using the plugin, you need to export the required models in `.tflite` and `.mlmodel` formats. The plugin provides support for tasks like detection and classification, with specific instructions for Android and iOS platforms. It also includes features like camera preview and methods for object detection and image classification on images. Ultralytics YOLO thrives on community collaboration and offers different licensing paths for open-source and commercial use cases.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. It supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled APIs. The tool generates JUnit tests in Java or Kotlin, focusing on fault detection, self-contained tests, SQL handling, and authentication. Known limitations include manual driver creation for whitebox testing and longer execution times for better results. EvoMaster has been funded by ERC and RCN grants.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses an Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. The tool supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled languages. It generates JUnit tests, detects faults, handles SQL databases, and supports authentication. EvoMaster has been funded by the European Research Council and the Research Council of Norway.

wacat is a tool designed to challenge web applications by simulating chaotic user behavior, such as random navigation, form input, and button clicks. It also incorporates AI-powered error detection, supporting features like detecting error messages, generating AI-driven content, and detecting HTTP errors and console log errors. wacat can be configured for various testing scenarios, including authentication, excluding specific pages, running in headless mode, and setting wait times and timeouts. It is built using TypeScript, oclif, Playwright, and Next.js for test applications.

Vercel AI Provider for running Large Language Models locally using Ollama. This module is under development and may contain errors and frequent incompatible changes. It provides the capability of generating and streaming text and objects, with features like image input, object generation, tool usage simulation, tool streaming simulation, intercepting fetch requests, and provider management. The provider can be customized with optional settings like baseURL and headers.

This is a development tutorial for eBPF based on CO-RE (Compile Once, Run Everywhere). It provides practical eBPF development practices from beginner to advanced, including basic concepts, code examples, and real-world applications. The tutorial focuses on eBPF examples in observability, networking, security, and more. It aims to help eBPF application developers quickly grasp eBPF development methods and techniques through examples in languages such as C, Go, and Rust. The tutorial is structured with independent eBPF tool examples in each directory, covering topics like kprobes, fentry, opensnoop, uprobe, sigsnoop, execsnoop, exitsnoop, runqlat, hardirqs, and more. The project is based on libbpf and frameworks like libbpf, Cilium, libbpf-rs, and eunomia-bpf for development.

Kobold-Assistant is a fully offline voice assistant interface to KoboldAI's large language model API. It can work online with the KoboldAI horde and online speech-to-text and text-to-speech models. The assistant, called Jenny by default, uses the latest coqui 'jenny' text to speech model and openAI's whisper speech recognition. Users can customize the assistant name, speech-to-text model, text-to-speech model, and prompts through configuration. The tool requires system packages like GCC, portaudio development libraries, and ffmpeg, along with Python >=3.7, <3.11, and runs on Ubuntu/Debian systems. Users can interact with the assistant through commands like 'serve' and 'list-mics'.

Detect logical fallacies and lapses in critical thinking to help avoid misinformation in the style of Socrates

AI Detector GPT is powered by Winston AI and created to help identify AI generated content. It is designed to help you detect use of AI Writing Chatbots such as ChatGPT, Claude and Bard and maintain integrity in academia and publishing. Winston AI is the most trusted AI content detector.

I help detect food allergies by analyzing eating habits.

Plagiarism Checker GPT is powered by Winston AI and created to help identify plagiarized content. It is designed to help you detect instances of plagiarism and maintain integrity in academia and publishing. Winston AI is the most trusted AI and Plagiarism Checker.

I find logical fallacies in texts.

AI content analysis expert for detecting AI authorship.

Detects and measures information credibility. Provides a "BS Score" (0-100) based on content analysis for misinformation signs, including factual inaccuracies and sensationalist language. Real-time feedback.

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

A virtual SOC analyst aiding in incident response.

To assist individuals seeking to learn about or work with Microsoft's Defender for Endpoint. I provide detailed explanations, step-by-step guides, troubleshooting advice, cybersecurity best practices, and demonstrations, all specifically tailored to Microsoft Defender for Endpoint.

Mit KI gegen Kartelle

GPT used to classify prompts as valid inputs or injection attempts. Json output.

Spam expert with comprehensive scam detection and education.

it is a meticulously crafted arsenal of knowledge, insights, and guidelines that is shaped to empower organizations in crafting, enhancing, and refining their cybersecurity defenses

I'm PhishCatcher, an expert in identifying phishing attempts.

A tool to help you decide if a website is part of a PBN or link network, created solely for link building. >> Get in touch with Gareth if you need a Freelance SEO for link building <<

I can guess your emotions! Tell me "Hi"

Expert på att hantera desinformation och misinformation

Multiple Environment Threat Evaluation of Resources (METEOR)™ Space Threats and Operational Risks to Mission (STORM)™ non-profit product AI co-pilot

CSIRT que lidera un equipo especializado en detectar y responder a incidentes de seguridad, maneja la contención y recuperación, organiza entrenamientos y simulacros, elabora reportes para optimizar estrategias de seguridad y coordina con entidades legales cuando es necesario