Best AI tools for< Investigate Data Breaches >

CrowdStrike is a cloud-based cybersecurity platform that provides endpoint protection, threat intelligence, and incident response services. It uses artificial intelligence (AI) to detect and prevent cyberattacks. CrowdStrike's platform is designed to be scalable and easy to use, and it can be deployed on-premises or in the cloud. CrowdStrike has a global customer base of over 23,000 organizations, including many Fortune 500 companies.

CrowdStrike is a leading cybersecurity platform that uses artificial intelligence (AI) to protect businesses from cyber threats. The platform provides a unified approach to security, combining endpoint security, identity protection, cloud security, and threat intelligence into a single solution. CrowdStrike's AI-powered technology enables it to detect and respond to threats in real-time, providing businesses with the protection they need to stay secure in the face of evolving threats.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

Quantexa News Intelligence is an AI-powered news data application that provides fast and powerful access to global news content. It offers real-time access to enriched, tagged, and structured news feeds, enabling users to build intelligent news-driven applications and workflows. With features like AI-powered search, data visualizations, and instant insights, Quantexa News API aggregates news from 90,000+ sources and 1.3M NLP-enriched articles daily. It helps users investigate events, enhance risk monitoring processes, and deliver news data to relevant apps and models efficiently.

SecureLabs is an AI-powered platform that offers comprehensive security, privacy, and compliance management solutions for businesses. The platform integrates cutting-edge AI technology to provide continuous monitoring, incident response, risk mitigation, and compliance services. SecureLabs helps organizations stay current and compliant with major regulations such as HIPAA, GDPR, CCPA, and more. By leveraging AI agents, SecureLabs offers autonomous aids that tirelessly safeguard accounts, data, and compliance down to the account level. The platform aims to help businesses combat threats in an era of talent shortages while keeping costs down.

Hatchet is an AI companion designed to assist on-call engineers in incident response by providing intelligent insights and suggestions based on logs, communications channels, and code analysis. It helps save time and money by automating the triaging and investigation process during critical incidents. The tool is built by engineers with a focus on data security, offering self-hosted deployments, permissions, audit trails, SSO, and version control. Hatchet aims to streamline incident resolution for tier-1 services, enabling faster response and potential problem resolution.

Megagon Labs is an AI research lab focusing on Knowledge Representation & Reasoning, Natural Language Processing, Human-Centered AI, and Data AI Symbiosis. They empower users with better information to make informed decisions through cutting-edge research and technologies. The lab's work includes investigating symbiotic systems, data management for AI, human-centered AI tools, and enhancing NLP capabilities for various domains.

GitHub Next is a research and development team at GitHub that explores the future of software development. The team prototypes tools and technologies that will change the way we build software, and identifies new approaches to building healthy, productive software engineering teams.

Darktrace is a cybersecurity platform that leverages AI technology to provide proactive protection against cyber threats. It offers cloud-native AI security solutions for networks, emails, cloud environments, identity protection, and endpoint security. Darktrace's AI Analyst investigates alerts at the speed and scale of AI, mimicking human analyst behavior. The platform also includes services such as 24/7 expert support and incident management. Darktrace's AI is built on a unique approach where it learns from the organization's data to detect and respond to threats effectively. The platform caters to organizations of all sizes and industries, offering real-time detection and autonomous response to known and novel threats.

Overwatch Data is a comprehensive intelligence platform that provides real-time, global understanding for cyber, fraud, security, supply chain, and market intelligence needs. The platform offers concise, actionable insights tailored to the user's requirements, cutting through noise to deliver essential information. Users can build custom monitoring solutions for various intelligence areas and benefit from intuitive data visualizations, executive summaries, and free-form chat with news data. Overwatch Data aims to save time and enhance decision-making by providing contextualized intelligence for fraud, security, and insights teams.

Wondershare Recoverit is a comprehensive data recovery software that can restore lost files from various devices and storage media. It offers advanced features such as enhanced photo and video recovery, hard drive and location recovery, system crashed computer recovery, NAS data recovery, and Linux data recovery. Recoverit supports over 1000 file formats and 2000 storage devices, with a high recovery rate of 98%. It is trusted by over 5 million users across 160 countries and has been awarded 35 advanced patents for its innovative data recovery methods.

Relativity is an AI-powered eDiscovery and legal search software solution that helps customers organize data, discover truth, and act on it. It offers a range of features such as proactive security, user experience enhancements, open platform for customization, legendary support, and AI-powered review tools. Relativity is trusted by thousands of organizations to handle sensitive data and streamline data discovery processes.

Aura is an all-in-one digital safety platform that uses artificial intelligence (AI) to protect your family online. It offers a wide range of features, including financial fraud protection, identity theft protection, VPN & online privacy, antivirus, password manager & smart vault, parental controls & safe gaming, and spam call protection. Aura is easy to use and affordable, and it comes with a 60-day money-back guarantee.

Brighterion AI, a Mastercard company, offers advanced AI solutions for financial institutions, merchants, and healthcare providers. With over 20 years of experience, Brighterion has revolutionized AI by providing market-ready models that enhance customer experience, reduce financial fraud, and mitigate risks. Their solutions are enriched with Mastercard's global network intelligence, ensuring scalability and powerful personalization. Brighterion's AI applications cater to acquirers, PSPs, issuers, and healthcare providers, offering custom AI solutions for transaction fraud monitoring, merchant monitoring, AML & compliance, and healthcare fraud detection. The company has received several prestigious awards for its excellence in AI and financial security.

Quantifind is an AI-powered financial crimes automation platform that specializes in Anti-Money Laundering (AML) and Know Your Customer (KYC) solutions. It offers end-to-end automation impact, best-in-class accuracy, and powerful APIs and applications for risk screening, investigations, and compliance in the financial services and public sector industries. Quantifind's Graphyte platform leverages AI and external data to streamline AML-KYC processes, providing comprehensive data coverage, dynamic risk typologies, and seamless integrations with case management systems.

EchoMark is a cloud-based data leak prevention solution that uses invisible forensic watermarks to protect sensitive information from unauthorized access and exfiltration. It allows organizations to securely share and collaborate on documents and emails without compromising privacy and security. EchoMark's advanced investigation tools can trace the source of a leaked document or email, even if it has been shared via printout or photo.

Amped Software develops solutions for the analysis and enhancement of images and videos for forensic, security, and investigative applications. Their tools are used by top forensic labs, law enforcement, military, security, and government agencies worldwide.

ScamAlert is an AI-powered application designed to help users avert scams in a smarter way. By adopting the power of AI and building smart systems, ScamAlert protects users from being scammed by analyzing risks, conducting manual reviews, providing timely alerts, and fostering a social community to prevent similar scams. The application enhances the online experience by taking care of risky aspects while empowering users to make well-informed decisions.

Emotion Logic Ltd is an AI application that specializes in genuine emotion detection from voice data. Their technology elevates applications across diverse sectors, including fraud investigations, healthcare, education, and customer service. Emotion Logic provides valuable insights into users' genuine emotions through voice analysis, surpassing tone, language, and cultural barriers.

SafeSpeak is an AI-powered mobile security solution that protects users from phone scams, SIM swaps, and other malicious activities. It uses advanced machine learning and large language models to detect and block threats in real-time. SafeSpeak offers a range of features for both personal and business use, including malicious behavior detection, community immunity, SIM swap detection, weekly and monthly reporting, quick and easy setup, admin dashboard, extensible API, custom reporting, and visibility into tactics, techniques, and procedures (TTPs).

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

AgentGym is a framework designed to help the AI community evaluate and develop generally-capable Large Language Model-based agents. It features diverse interactive environments and tasks with real-time feedback and concurrency. The platform supports 14 environments across various domains like web navigating, text games, house-holding tasks, digital games, and more. AgentGym includes a trajectory set (AgentTraj) and a benchmark suite (AgentEval) to facilitate agent exploration and evaluation. The framework allows for agent self-evolution beyond existing data, showcasing comparable results to state-of-the-art models.

This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Autonomous agents are designed to achieve specific objectives through self-guided instructions. With the emergence and growth of large language models (LLMs), there is a growing trend in utilizing LLMs as fundamental controllers for these autonomous agents. This repository conducts a comprehensive survey study on the construction, application, and evaluation of LLM-based autonomous agents. It explores essential components of AI agents, application domains in natural sciences, social sciences, and engineering, and evaluation strategies. The survey aims to be a resource for researchers and practitioners in this rapidly evolving field.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

ResumeFlow is an automated system utilizing Large Language Models (LLMs) to streamline the job application process. It aims to reduce human effort in various steps of job hunting by integrating LLM technology. Users can access ResumeFlow as a web tool, install it as a Python package, or download the source code. The project focuses on leveraging LLMs to automate tasks such as resume generation and refinement, making job applications smoother and more efficient.

BentoML is an open-source model serving library for building performant and scalable AI applications with Python. It comes with everything you need for serving optimization, model packaging, and production deployment.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

MMMU is a benchmark designed to evaluate multimodal models on college-level subject knowledge tasks, covering 30 subjects and 183 subfields with 11.5K questions. It focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. The evaluation of various models highlights substantial challenges, with room for improvement to stimulate the community towards expert artificial general intelligence (AGI).

This repository contains the training code of LLM-QAT for large language models. The work investigates quantization-aware training for LLMs, including quantizing weights, activations, and the KV cache. Experiments were conducted on LLaMA models of sizes 7B, 13B, and 30B, at quantization levels down to 4-bits. Significant improvements were observed when quantizing weight, activations, and kv cache to 4-bit, 8-bit, and 4-bit, respectively.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

Knowledge Conflicts for LLMs: A Survey is a repository containing a survey paper that investigates three types of knowledge conflicts: context-memory conflict, inter-context conflict, and intra-memory conflict within Large Language Models (LLMs). The survey reviews the causes, behaviors, and possible solutions to these conflicts, providing a comprehensive analysis of the literature in this area. The repository includes detailed information on the types of conflicts, their causes, behavior analysis, and mitigating solutions, offering insights into how conflicting knowledge affects LLMs and how to address these conflicts.

Private Investigators and Security Firms, given the nature of their work, handle highly sensitive information and must maintain strict confidentiality and data privacy standards.

Comprehensive analysis of Google API Content Warehouse Leak

Your guide through the digital frontier, unveiling cyber secrets with expertise.

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Aid in decrypting text with guidance and security awareness.

UFO/UAP reporting assistant with real-time satellite & flight data analysis.

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Expert in UFO/UAP analysis, employing scientific methods for realistic interpretations.

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A detective investigating the mystery of Satoshi Nakamoto. Uncovering the secrets of Bitcoin's and Crypto creator. Powered by Breebs (www.breebs.com)

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Approachable OSINT guide focusing on ethical practices.

Best Tools, Techniques and Tactics for Tracking Down Cyber Criminals.

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I am a detective simulator, inspired by Hercule Poirot.

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Investigates global issues and proposes efficient, practical solutions.

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