Best AI tools for< Vulnerability Researcher >

OpenBuckets is a web application designed to help users find and secure open buckets in cloud storage systems. It provides a user-friendly interface for scanning and identifying publicly accessible buckets, allowing users to take necessary actions to secure their data. With OpenBuckets, users can easily detect misconfigured buckets and prevent potential data breaches. The application offers a simple yet effective solution for enhancing cloud security and protecting sensitive information stored in cloud storage platforms.

Huntr is the world's first bug bounty platform for AI/ML. It provides a single place for security researchers to submit vulnerabilities, ensuring the security and stability of AI/ML applications, including those powered by Open Source Software (OSS).

CensysGPT Beta is a tool that simplifies building queries and empowers users to conduct efficient and effective reconnaissance operations. It enables users to quickly and easily gain insights into hosts on the internet, streamlining the process and allowing for more proactive threat hunting and exposure management.

Protect AI is a comprehensive platform designed to secure AI systems by providing visibility and manageability to detect and mitigate unique AI security threats. The platform empowers organizations to embrace a security-first approach to AI, offering solutions for AI Security Posture Management, ML model security enforcement, AI/ML supply chain vulnerability database, LLM security monitoring, and observability. Protect AI aims to safeguard AI applications and ML systems from potential vulnerabilities, enabling users to build, adopt, and deploy AI models confidently and at scale.

Glog is an AI application focused on making software more secure by providing remediation advice for security vulnerabilities in software code based on context. It is capable of automatically fixing vulnerabilities, thus reducing security risks and protecting against cyber attacks. The platform utilizes machine learning and AI to enhance software security and agility, ensuring system reliability, integrity, and safety.

Horizon3.ai Solutions offers the NodeZero™ Platform, an AI-powered autonomous penetration testing tool designed to enhance cybersecurity measures. The platform combines expert human analysis by Offensive Security Certified Professionals with automated testing capabilities to streamline compliance processes and proactively identify vulnerabilities. NodeZero empowers organizations to continuously assess their security posture, prioritize fixes, and verify the effectiveness of remediation efforts. With features like internal and external pentesting, rapid response capabilities, AD password audits, phishing impact testing, and attack research, NodeZero is a comprehensive solution for large organizations, ITOps, SecOps, security teams, pentesters, and MSSPs. The platform provides real-time reporting, integrates with existing security tools, reduces operational costs, and helps organizations make data-driven security decisions.

The website offers an AI-powered binary vulnerability scanner that allows users to upload a binary file for analysis. The tool decompiles the executable, removes filler, formats the code, and checks for vulnerabilities by comparing against a database of historical vulnerabilities. It utilizes a finetuned CodeT5+ Embedding model to generate function-wise embeddings and checks for similarities against the DiverseVul Dataset. The tool also uses SemGrep to identify vulnerabilities in the code.

Snyk is a developer security platform powered by DeepCode AI, offering solutions for application security, software supply chain security, and secure AI-generated code. It provides comprehensive vulnerability data, license compliance management, and self-service security education. Snyk integrates AI models trained on security-specific data to secure applications and manage tech debt effectively. The platform ensures developer-first security with one-click security fixes and AI-powered recommendations, enhancing productivity while maintaining security standards.

DryRun Security is an AI-powered security tool designed to provide developers with security context and analysis for code changes in real-time. It offers a suite of analyzers to identify risky code changes, such as SQL injection, command injection, and sensitive file modifications. The tool integrates seamlessly with GitHub repositories, ensuring developers receive security feedback before merging code changes. DryRun Security aims to empower developers to write secure code efficiently and effectively.

Qwiet AI is a code vulnerability detection platform that accelerates secure coding by uncovering, prioritizing, and generating fixes for top vulnerabilities with a single scan. It offers features such as AI-enhanced SAST, contextual SCA, AI AutoFix, Container Security, SBOM, and Secrets detection. Qwiet AI helps InfoSec teams in companies to accurately pinpoint and autofix risks in their code, reducing false positives and remediation time. The platform provides a unified vulnerability dashboard, prioritizes risks, and offers tailored fix suggestions based on the full context of the code.

CloudDefense.AI is an industry-leading multi-layered Cloud Native Application Protection Platform (CNAPP) that safeguards cloud infrastructure and cloud-native apps with expertise, precision, and confidence. It offers comprehensive cloud security solutions, vulnerability management, compliance, and application security testing. The platform utilizes advanced AI technology to proactively detect and analyze real-time threats, ensuring robust protection for businesses against cyber threats.

MobiHeals is a mobile application focused on security analysis and vulnerability checks for mobile apps. It offers comprehensive security vulnerability analysis, cloud-based static and dynamic application security testing, and integrated vulnerability assessment in one platform. MobiHeals helps users comply with global cybersecurity guidelines and manage security vulnerabilities throughout the development, testing, and operation stages of mobile applications.

BigBear.ai is an AI-powered decision intelligence solutions provider that offers services across various industries including Government & Defense, Manufacturing & Warehouse Operations, Healthcare & Life Sciences. They specialize in optimizing operational efficiency, force deployment, supply chain management, autonomous systems management, and vulnerability detection. Their solutions are designed to improve situational awareness, streamline production processes, and enhance patient care delivery settings.

DepsHub is an AI-powered tool designed to simplify dependency updates for software development teams. It offers automatic dependency updates, license checks, and security vulnerability scanning to ensure team security and efficiency. With noise-free dependency management, cross-repository overview, license compliance, and security alerts, DepsHub streamlines the process of keeping dependencies up-to-date. The tool leverages AI to analyze library changelogs, release notes, and codebases to automatically update dependencies, including handling breaking changes. DepsHub supports a wide range of languages and frameworks, making it suitable for teams of all sizes to save time and focus on writing code that matters.

Equixly is an AI-powered application designed to help secure APIs by identifying vulnerabilities and weaknesses through continuous security testing. It offers features such as scalable API PenTesting, rapid remediation, attack simulation, mapping attack surfaces, compliance simplification, and data exposure minimization. Equixly aims to provide users with a comprehensive solution to enhance the security of their APIs and streamline compliance processes.

Vulnscanner AI is an AI-powered WordPress security tool that offers affordable and user-friendly website security solutions. It provides instant, jargon-free security reports, step-by-step resolution guides, and customizable security solutions to prevent future attacks. The tool is designed to help small/medium businesses, web professionals, and individuals safeguard their online presence without breaking the bank. With advanced algorithms and military-grade encryption, Vulnscanner AI aims to protect websites from cyber threats and vulnerabilities.

ZeroThreat is a web app and API security scanner that helps businesses identify and fix vulnerabilities in their web applications and APIs. It uses a combination of static and dynamic analysis techniques to scan for a wide range of vulnerabilities, including OWASP Top 10, CWE Top 25, and SANS Top 25. ZeroThreat also provides continuous monitoring and alerting, so businesses can stay on top of new vulnerabilities as they emerge.

Pixeebot is an automated product security engineer that helps developers fix vulnerabilities, harden code, squash bugs, and improve code quality. It integrates with your existing workflow and can be used locally via CLI or through the GitHub app. Pixeebot is powered by the open source Codemodder framework, which allows you to build your own custom codemods.

Smaty.xyz is a comprehensive platform that provides a suite of tools for code generation and security auditing. With Smaty.xyz, developers can quickly and easily generate high-quality code in multiple programming languages, ensuring consistency and reducing development time. Additionally, Smaty.xyz offers robust security auditing capabilities, enabling developers to identify and address vulnerabilities in their code, mitigating risks and enhancing the overall security of their applications.

VIDOC is an AI-powered security engineer that automates code review and penetration testing. It continuously scans and reviews code to detect and fix security issues, helping developers deliver secure software faster. VIDOC is easy to use, requiring only two lines of code to be added to a GitHub Actions workflow. It then takes care of the rest, providing developers with a tailored code solution to fix any issues found.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

HackBot is an AI-powered cybersecurity chatbot designed to provide accurate answers to cybersecurity-related queries, conduct code analysis, and scan analysis. It utilizes the Meta-LLama2 AI model through the 'LlamaCpp' library to respond coherently. The chatbot offers features like local AI/Runpod deployment support, cybersecurity chat assistance, interactive interface, clear output presentation, static code analysis, and vulnerability analysis. Users can interact with HackBot through a command-line interface and utilize it for various cybersecurity tasks.

Awesome LLM Security is a curated collection of tools, documents, and projects related to Large Language Model (LLM) security. It covers various aspects of LLM security including white-box, black-box, and backdoor attacks, defense mechanisms, platform security, and surveys. The repository provides resources for researchers and practitioners interested in understanding and safeguarding LLMs against adversarial attacks. It also includes a list of tools specifically designed for testing and enhancing LLM security.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

IPEX-LLM is a PyTorch library for running Large Language Models (LLMs) on Intel CPUs and GPUs with very low latency. It provides seamless integration with various LLM frameworks and tools, including llama.cpp, ollama, Text-Generation-WebUI, HuggingFace transformers, and more. IPEX-LLM has been optimized and verified on over 50 LLM models, including LLaMA, Mistral, Mixtral, Gemma, LLaVA, Whisper, ChatGLM, Baichuan, Qwen, and RWKV. It supports a range of low-bit inference formats, including INT4, FP8, FP4, INT8, INT2, FP16, and BF16, as well as finetuning capabilities for LoRA, QLoRA, DPO, QA-LoRA, and ReLoRA. IPEX-LLM is actively maintained and updated with new features and optimizations, making it a valuable tool for researchers, developers, and anyone interested in exploring and utilizing LLMs.

This repository contains materials for the paper 'How Far Have We Gone in Vulnerability Detection Using Large Language Model'. It provides a tool for evaluating vulnerability detection models using datasets such as d2a, ctf, magma, big-vul, and devign. Users can query the model 'Llama-2-7b-chat-hf' and store results in a SQLite database for analysis. The tool supports binary and multiple classification tasks with concurrency settings. Additionally, users can evaluate the results and generate a CSV file with metrics for each dataset and prompt type.

FigStep is a black-box jailbreaking algorithm against large vision-language models (VLMs). It feeds harmful instructions through the image channel and uses benign text prompts to induce VLMs to output contents that violate common AI safety policies. The tool highlights the vulnerability of VLMs to jailbreaking attacks, emphasizing the need for safety alignments between visual and textual modalities.

Agentic Security is an open-source vulnerability scanner designed for safety scanning, offering customizable rule sets and agent-based attacks. It provides comprehensive fuzzing for any LLMs, LLM API integration, and stress testing with a wide range of fuzzing and attack techniques. The tool is not a foolproof solution but aims to enhance security measures against potential threats. It offers installation via pip and supports quick start commands for easy setup. Users can utilize the tool for LLM integration, adding custom datasets, running CI checks, extending dataset collections, and dynamic datasets with mutations. The tool also includes a probe endpoint for integration testing. The roadmap includes expanding dataset variety, introducing new attack vectors, developing an attacker LLM, and integrating OWASP Top 10 classification.

This is a vulnerability mining engine purely based on GPT, requiring no prior knowledge base, no fine-tuning, yet its effectiveness can overwhelmingly surpass most of the current related research. The core idea revolves around being task-driven, not question-driven, driven by prompts, not by code, and focused on prompt design, not model design. The essence is encapsulated in one word: deception. It is a type of code understanding logic vulnerability mining that fully stimulates the capabilities of GPT, suitable for real actual projects.

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.

HaE is a framework project in the field of network security (data security) that combines artificial intelligence (AI) large models to achieve highlighting and information extraction of HTTP messages (including WebSocket). It aims to reduce testing time, focus on valuable and meaningful messages, and improve vulnerability discovery efficiency. The project provides a clear and visual interface design, simple interface interaction, and centralized data panel for querying and extracting information. It also features built-in color upgrade algorithm, one-click export/import of data, and integration of AI large models API for optimized data processing.

SploitCraft is a curated collection of security exploits, penetration testing techniques, and vulnerability demonstrations intended to help professionals and enthusiasts understand and demonstrate the latest in cybersecurity threats and offensive techniques. The repository is organized into folders based on specific topics, each containing directories and detailed READMEs with step-by-step instructions. Contributions from the community are welcome, with a focus on adding new proof of concepts or expanding existing ones while adhering to the current structure and format of the repository.

Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.

LF AI & Data Landscape is a map to explore open source projects in the AI & Data domains, highlighting companies that are members of LF AI & Data. It showcases members of the Foundation and is modelled after the Cloud Native Computing Foundation landscape. The landscape includes current version, interactive version, new entries, logos, proper SVGs, corrections, external data, best practices badge, non-updated items, license, formats, installation, vulnerability reporting, and adjusting the landscape view.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

Expert in CVEs and cybersecurity vulnerabilities, providing precise information from the National Vulnerability Database.

AppSec & Bug Bounty

Detailed CVE analysis, focusing on chaining and APTs, using a fixed schema.

GPT expert on CISA's KEV Catalog and CVE existence check

Your personal Ethereum magician — Simply ask a question or provide a code sample for insights into vulnerabilities, gas optimizations, and best practices. Don't be shy to ask about tooling and legendary attacks.

Cybersecurity simulation

Updates on CVEs from GitHub repo in table format.

Expert in analyzing vulnerabilities with ransomware focus with intelligence powered by Phoenix Security

Web Vulnerability Academy (WVA) is an interactive tutor designed to introduce users to web vulnerabilities while also providing them with opportunities to assess and enhance their knowledge through testing.

Your ally in navigating the CVE deluge. Expert insights for prioritizing and remediating vulnerabilities.

Ensures software security through comprehensive testing techniques.

A PHP Security Expert offering guidance on secure coding practices.

ChatGPT Especializado em DevSecOps

Assists in writing detailed security reports.

Cyber Asset Identification Expert

Your AI-powered sentinel for code! Scans for vulnerabilities, offers security tips, and educates on best practices in cybersecurity. 🔍🔐

Assistant for pentesting apis

Your personal security tool

Comprehensive threat modeling

Betterscan.io DevSecOps