Best AI tools for< Honeypot Researcher >

Beelzebub is an advanced honeypot framework designed to provide a highly secure environment for detecting and analyzing cyber attacks. It offers a low code approach for easy implementation and utilizes virtualization techniques powered by OpenAI Generative Pre-trained Transformer. Key features include OpenAI Generative Pre-trained Transformer acting as Linux virtualization, SSH Honeypot, HTTP Honeypot, TCP Honeypot, Prometheus openmetrics integration, Docker integration, RabbitMQ integration, and kubernetes support. Beelzebub allows easy configuration for different services and ports, enabling users to create custom honeypot scenarios. The roadmap includes developing Beelzebub into a robust PaaS platform. The project welcomes contributions and encourages adherence to the Code of Conduct for a supportive and respectful community.

Awesome ChatGPT is an artificial intelligence chatbot developed by OpenAI. It offers a wide range of applications, web apps, browser extensions, CLI tools, bots, integrations, and packages for various platforms. Users can interact with ChatGPT through different interfaces and use it for tasks like generating text, creating presentations, summarizing content, and more. The ecosystem around ChatGPT includes tools for developers, writers, researchers, and individuals looking to leverage AI technology for different purposes.

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.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

Awesome GPT + Security is a curated list of awesome security tools, experimental case or other interesting things with LLM or GPT. It includes tools for integrated security, auditing, reconnaissance, offensive security, detecting security issues, preventing security breaches, social engineering, reverse engineering, investigating security incidents, fixing security vulnerabilities, assessing security posture, and more. The list also includes experimental cases, academic research, blogs, and fun projects related to GPT security. Additionally, it provides resources on GPT security standards, bypassing security policies, bug bounty programs, cracking GPT APIs, and plugin security.

Trapster Community is a low-interaction honeypot designed for internal networks or credential capture. It monitors and detects suspicious activities, providing deceptive security layer. Features include mimicking network services, asynchronous framework, easy configuration, expandable services, and HTTP honeypot engine with AI capabilities. Supported protocols include DNS, HTTP/HTTPS, FTP, LDAP, MSSQL, POSTGRES, RDP, SNMP, SSH, TELNET, VNC, and RSYNC. The tool generates various types of logs and offers HTTP engine with AI capabilities to emulate websites using YAML configuration. Contributions are welcome under AGPLv3+ license.

Galah is an LLM-powered web honeypot designed to mimic various applications and dynamically respond to arbitrary HTTP requests. It supports multiple LLM providers, including OpenAI. Unlike traditional web honeypots, Galah dynamically crafts responses for any HTTP request, caching them to reduce repetitive generation and API costs. The honeypot's configuration is crucial, directing the LLM to produce responses in a specified JSON format. Note that Galah is a weekend project exploring LLM capabilities and not intended for production use, as it may be identifiable through network fingerprinting and non-standard responses.