Best AI tools for< Vulnerability Researcher >

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, cleans, formats, and checks for historical vulnerabilities. It generates function-wise embeddings using a finetuned CodeT5+ Embedding model and checks for similarities against the DiverseVul Dataset. The tool also checks for vulnerabilities using SemGrep. The analysis process may take up to 10 minutes depending on the file size.

OpenBuckets is a web application designed to help users find and secure open buckets in cloud storage systems. It provides a simple and efficient way to identify and protect sensitive data that may be exposed due to misconfigurations in cloud storage settings. With OpenBuckets, users can easily scan their cloud storage accounts for publicly accessible buckets and take necessary actions to enhance data security.

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.

Rebuff AI is an AI tool designed as a self-hardening prompt injection detector. It is built to strengthen itself against attacks, making it a robust solution for detecting and preventing prompt injection vulnerabilities. The tool provides an API for developers to integrate prompt injection detection capabilities into their applications easily. Rebuff AI aims to protect the AI community by enhancing the security of AI systems and applications.

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.

AquilaX is an AI-powered DevSecOps platform that simplifies security and accelerates development processes. It offers a comprehensive suite of security scanning tools, including secret identification, PII scanning, SAST, container scanning, and more. AquilaX is designed to integrate seamlessly into the development workflow, providing fast and accurate results by leveraging AI models trained on extensive datasets. The platform prioritizes developer experience by eliminating noise and false positives, making it a go-to choice for modern Secure-SDLC teams worldwide.

Kindo is an AI-powered platform designed for DevSecOps teams to automate tasks, write doctrine, and orchestrate infrastructure responses. It offers AI-powered Runbook automations to streamline workflows, automate tedious tasks, and enhance security controls. Kindo enables users to offload time-consuming tasks to AI Agents, prioritize critical tasks, and monitor AI-related activities for compliance and informed decision-making. The platform provides a comprehensive vantage point for modern infrastructure defense and instrumentation, allowing users to create repeatable processes, automate vulnerability assessment and remediation, and secure multi-cloud IAM configurations.

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.

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 compliance with global cybersecurity guidelines. The platform helps users detect security vulnerabilities and quality issues in the mobile application source code, perform manual and automated testing, and manage security vulnerabilities effectively. MobiHeals aims to deliver trust by providing cost-efficient and scalable application security testing on the cloud.

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 teams stay secure and up-to-date. With noise-free dependency management, cross-repository overview, license compliance, and security alerts, DepsHub streamlines the process of managing dependencies for teams of any size. The tool saves time by analyzing 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 easy for teams to integrate and stay productive.

Escape is a comprehensive platform designed to discover and secure all APIs, SPAs, and Microservices efficiently. It offers modern application security solutions that match the speed of development processes. With features like API documentation, business logic vulnerability detection, and compliance reports, Escape ensures proactive security measures for your applications. The platform integrates seamlessly into CI/CD pipelines, providing full security observability and tailored remediations. Escape's innovative approach includes automated pentesting, GraphQL security, and a unique Business Logic Security Testing Algorithm, making it a valuable tool for enhancing API security at scale.

CyberUpgrade.net is an AI-powered platform that offers comprehensive cybersecurity and compliance solutions for organizations of all sizes. It provides automated compliance, risk management, vendor risk assessment, policy management, audit management, and 24/7 security support. The platform features a cloud vulnerability scanner, security awareness training, pentesting, business continuity planning, disaster recovery planning, and an AI-powered assistant for seamless security support. CyberUpgrade helps CTOs understand their organization's security status, proposes improvement plans, guides execution, and prepares compliance documentation with a push of a button. It engages every employee individually for evidence collection and situation analysis, ensuring real cybersecurity measures are in place.

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

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.

FiniteMonkey is an advanced vulnerability mining engine powered purely by GPT, requiring no prior knowledge base or fine-tuning. Its effectiveness significantly surpasses most current related research approaches. The tool is task-driven, prompt-driven, and focuses on prompt design, leveraging 'deception' and hallucination as key mechanics. It has helped identify vulnerabilities worth over $60,000 in bounties. The tool requires PostgreSQL database, OpenAI API access, and Python environment for setup. It supports various languages like Solidity, Rust, Python, Move, Cairo, Tact, Func, Java, and Fake Solidity for scanning. FiniteMonkey is best suited for logic vulnerability mining in real projects, not recommended for academic vulnerability testing. GPT-4-turbo is recommended for optimal results with an average scan time of 2-3 hours for medium projects. The tool provides detailed scanning results guide and implementation tips for users.

SinkFinder + LLM is a closed-source semi-automatic vulnerability discovery tool that performs static code analysis on jar/war/zip files. It enhances the capability of LLM large models to verify path reachability and assess the trustworthiness score of the path based on the contextual code environment. Users can customize class and jar exclusions, depth of recursive search, and other parameters through command-line arguments. The tool generates rule.json configuration file after each run and requires configuration of the DASHSCOPE_API_KEY for LLM capabilities. The tool provides detailed logs on high-risk paths, LLM results, and other findings. Rules.json file contains sink rules for various vulnerability types with severity levels and corresponding sink methods.

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.

CodeLLM Paper repository provides a curated list of research papers focused on Large Language Models (LLMs) for code. It aims to facilitate researchers and practitioners in exploring the rapidly growing body of literature on this topic. The papers are systematically collected from various top-tier venues, categorized, and labeled for easier navigation. The selection strategy involves abstract extraction, keyword matching, relevance check using LLMs, and manual labeling. The papers are categorized based on Application, Principle, and Research Paradigm dimensions. Contributions to expand the repository are welcome through PR submission, issue submission, or request for batch updates. The repository is intended solely for research purposes, with raw data sourced from publicly available information on ACM, IEEE, and corresponding conference websites.

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.

Garak is a vulnerability scanner designed for LLMs (Large Language Models) that checks for various weaknesses such as hallucination, data leakage, prompt injection, misinformation, toxicity generation, and jailbreaks. It combines static, dynamic, and adaptive probes to explore vulnerabilities in LLMs. Garak is a free tool developed for red-teaming and assessment purposes, focusing on making LLMs or dialog systems fail. It supports various LLM models and can be used to assess their security and robustness.

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.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

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