Best AI tools for< detect fraud activities >

Overwatch Data is a comprehensive open-source intelligence platform that provides real-time, global understanding for cyber, fraud, security, supply chain, and market intelligence needs. The platform offers actionable insights, customizable monitoring, intuitive data visualizations, and executive summaries to help organizations cut through the noise and stay informed. With features like freeform chat, customizable monitoring, and a wide range of data sources, Overwatch Data empowers users to make informed decisions and stay ahead of evolving threats.

Schwarzthal Tech's Wunderschild is an AI-driven platform for financial crime intelligence that revolutionizes compliance and investigation techniques. It provides intelligence solutions based on network assessment, data linkage, flow aggregation, and machine learning. The platform offers insights on strategic risks related to Politically Exposed Persons, Serious Organised Crime, Terrorism Financing, and more. Wunderschild's data backbone is a global business registry enriched with information extracted using advanced machine learning techniques, allowing for deep dives into complex transnational crime cases.

CARCO is an advanced Mobile AI Fraud Prevention application designed to protect insurance carriers and consumers by identifying and preventing risk events and fraudulent activities. The application streamlines the inspection process through integrated AI and fraud alert validation technology, providing a back-office solution that is easily integrated into mobile platforms, cost-effective, and fraud-detecting. CARCO also offers NMVTIS, a premier system in the U.S. that requires reporting of vehicle title data. With over 50 million transactions completed to date, CARCO has a proven track record in fraud prevention and risk mitigation for the insurance industry.

AI Scam Detective is an AI tool designed to help users detect and prevent online scams. Users can paste their messages or conversations into the provided box, and the tool will provide a score from 1-10 indicating the likelihood of it being a scam. Created by Sam Meehan, AI Scam Detective is a reliable resource for individuals looking to protect themselves from fraudulent activities online.

AI or Not is an AI-powered tool that helps businesses and individuals detect AI-generated images and audio. It uses advanced machine learning algorithms to analyze content and determine the likelihood of AI manipulation. With AI or Not, users can protect themselves from fraud, misinformation, and other malicious activities involving AI-generated content.

Greip is an AI-powered fraud prevention service that offers various tools to detect and prevent fraudulent activities in payments. It provides services such as credit card fraud detection, BIN/IIN lookup, IBAN validation, profanity detection, VPN/proxy detection, IP geolocation, ASN lookup, and country lookup. Greip also offers resources like educational articles, industry trends, and documentation. Users can integrate Greip with thousands of apps and access the latest service enhancements through the changelog. The platform helps users prevent identity theft, validate data, and gain valuable insights through real-time monitoring.

CUBE3.AI is a real-time crypto fraud prevention tool that utilizes AI technology to identify and prevent various types of fraudulent activities in the blockchain ecosystem. It offers features such as risk assessment, real-time transaction security, automated protection, instant alerts, and seamless compliance management. The tool helps users protect their assets, customers, and reputation by proactively detecting and blocking fraud in real-time.

LoginLlama is an AI-powered suspicious login detection tool designed for developers to enhance customer security effortlessly by preventing fraudulent logins. It evaluates login attempts through multiple ranking factors, including historic behavior, AI analysis, request origin, and user agent. The tool helps combat top login threats such as unauthorized access, account takeover, credential stuffing, brute force attacks, phishing attacks, and insider threats. LoginLlama offers different pricing plans with features like AI-powered suspicious login detection, weekly summary emails, 2FA, and more.

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).

Fraud.net is an AI-powered fraud detection and prevention platform designed for enterprises. It offers a comprehensive and customizable solution to manage and prevent various types of fraud, such as account takeover, application fraud, and payment fraud. The platform utilizes AI and machine learning technologies to provide real-time monitoring, analytics, and reporting, helping businesses reduce fraud losses and improve customer trust. Fraud.net is trusted by various industries, including financial services, e-commerce, gaming, and government, to combat fraud schemes and ensure secure transactions.

Sardine is an AI-powered platform for fraud prevention and compliance. It offers a comprehensive suite of products to help banks, retailers, and fintechs detect fraud patterns, prevent money laundering, and stop sophisticated scams. Sardine combines deep device intelligence, behavior biometrics, and identity signals to provide a precise risk score for every customer interaction. The platform also features machine learning models, a rules engine, network graph analysis, anomaly detection, and generative AI capabilities to fight modern threats. Sardine helps reduce fraud rates, decrease false positives, and streamline risk operations with its fully integrated solutions.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It helps businesses combat various fraud and financial crimes in real time. DataVisor's platform provides comprehensive fraud detection and prevention capabilities, including account onboarding, application fraud, ATO prevention, card fraud, check fraud, FinCrime and AML, and ACH and wire fraud detection. The platform is designed to adapt to new fraud incidents immediately with real-time data signal orchestration and end-to-end workflow automation, minimizing fraud losses and maximizing fraud detection coverage.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It provides a comprehensive suite of capabilities to combat a variety of fraud and financial crimes in real time. DataVisor's hyper-scalable, modern architecture allows you to leverage transaction logs, user profiles, dark web and other identity signals with real-time analytics to enrich and deliver high quality detection in less than 100-300ms. The platform is optimized to scale to support the largest enterprises with ultra-low latency. DataVisor enables early detection and adaptive response to new and evolving fraud attacks combining rules, machine learning, customizable workflows, device and behavior signals in an all-in-one platform for complete protection. Leading with an Unsupervised approach, DataVisor is the only proven, production-ready solution that can proactively stop fraud attacks before they result in financial loss.

ChainAware.ai is an AI-based Crypto Wallet Auditor that offers fraud detection, intention calculation, and analytics for various blockchain networks such as Ethereum, Polygon, BSC, and TON. Users can leverage AI algorithms for wallet auditing, predictive rug pull detection, and credit scoring. The platform provides detailed wallet analytics and predictive power of 98% for fraud detection, aiming to build trust in the crypto space.

Unit21 is a customizable no-code platform designed for risk and compliance operations. It empowers organizations to combat financial crime by providing end-to-end lifecycle risk analysis, fraud prevention, case management, and real-time monitoring solutions. The platform offers features such as AI Copilot for alert prioritization, Ask Your Data for data analysis, Watchlist & Sanctions for ongoing screening, and more. Unit21 focuses on fraud prevention and AML compliance, simplifying operations and accelerating investigations to respond to financial threats effectively and efficiently.

Peslac is a leading insurance solution provider in Africa, offering innovative and reliable insurance technology to reshape the insurance landscape. With a focus on streamlining processes, improving customer experiences, and combating insurance fraud, Peslac empowers businesses with comprehensive solutions tailored to meet the evolving needs of the insurance industry. From InsurSphere for insurance distribution to Auto for motor claims and Medical for medical claims processing, Peslac leverages advanced technology and skilled professionals to drive efficiency and productivity in the insurance sector.

Flagright is an AI-native AML compliance and fraud prevention solution designed for EU and UK fintech startups. It offers a comprehensive platform powered by AI to screen, monitor, and investigate AML compliance and fraud use cases. With real-time transaction monitoring, case management, AI forensics, customer risk assessment, and merchant monitoring, Flagright provides tailored solutions for AML program design, audit, and fintech licensing support. The platform aims to streamline compliance efforts, reduce false positives, and enhance risk management capabilities for financial institutions.

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.

hCaptcha Enterprise is a comprehensive AI-powered security platform designed to detect and deter human and automated threats, including bot detection, fraud protection, and account defense. It offers highly accurate bot detection, fraud protection without false positives, and account takeover detection. The platform also provides privacy-preserving abuse detection with zero personally identifiable information (PII) required. hCaptcha Enterprise is trusted by category leaders in various industries worldwide, offering universal support, comprehensive security, and compliance with global privacy standards like GDPR, CCPA, and HIPAA.

Emotion Logic Ltd is an AI application specializing in genuine emotion detection through voice data analysis. The platform offers services such as Emotional Diamond for analyzing emotional states in video and audio files, FeelGPT for actionable AI insights, Love Detector for unveiling romance potential, and more. Emotion Logic leverages Affective Computing to enhance user experiences and provide valuable insights across various sectors like fraud investigations, healthcare, education, and customer service.

MiniAiLive provides system integrators with fast, flexible and extremely precise facial recognition with 3D passive face liveness detection (face anti-spoofing) that can be deployed across a number of scenarios, including security, access control, public safety, fintech, smart retail and home protection.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

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 repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

last_layer is a security library designed to protect LLM applications from prompt injection attacks, jailbreaks, and exploits. It acts as a robust filtering layer to scrutinize prompts before they are processed by LLMs, ensuring that only safe and appropriate content is allowed through. The tool offers ultra-fast scanning with low latency, privacy-focused operation without tracking or network calls, compatibility with serverless platforms, advanced threat detection mechanisms, and regular updates to adapt to evolving security challenges. It significantly reduces the risk of prompt-based attacks and exploits but cannot guarantee complete protection against all possible threats.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

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.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

This repository contains code and configurations for the LLM - Detect AI Generated Text competition. It includes setup instructions for hardware, software, dependencies, and datasets. The training section covers scripts and configurations for training LLM models, DeBERTa ranking models, and an embedding model. Text generation section details fine-tuning LLMs using the CLM objective on the PERSUADE corpus to generate student-like essays.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

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.

This repository contains a C++ application that demonstrates face recognition capabilities using computer vision techniques. The demo utilizes OpenCV and dlib libraries for efficient face detection and recognition with 3D passive face liveness detection (face anti-spoofing). Key Features: Face detection: The SDK utilizes advanced computer vision techniques to detect faces in images or video frames, enabling a wide range of applications. Face recognition: It can recognize known faces by comparing them with a pre-defined database of individuals. Age estimation: It can estimate the age of detected faces. Gender detection: It can determine the gender of detected faces. Liveness detection: It can detect whether a face is from a live person or a static image.

AudioSeal is a method for speech localized watermarking, designed with state-of-the-art robustness and detector speed. It jointly trains a generator to embed a watermark in audio and a detector to detect watermarked fragments in longer audios, even in the presence of editing. The tool achieves top-notch detection performance at the sample level, generates minimal alteration of signal quality, and is robust to various audio editing types. With a fast, single-pass detector, AudioSeal surpasses existing models in speed, making it ideal for large-scale and real-time applications.

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.

fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenStreetMap Team (HOT) to improve mapping efficiency and accuracy for humanitarian purposes. It uses AI models, specifically computer vision techniques, to detect objects like buildings, roads, waterways, and trees from satellite and UAV imagery. The service allows OSM community members to create and train their own AI models for mapping in their region of interest and ensures models are relevant to local communities. Constant feedback loop with local communities helps eliminate model biases and improve model accuracy.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

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.

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Friendly scam guide with threat level indicator.

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