Best AI tools for< Detect Ransomware >

Spin.AI is an AI-powered SaaS security platform that provides full visibility and control over mission-critical applications. With features such as SSPM, DSPM, ransomware detection & response, data leak prevention, and backup & disaster recovery, Spin.AI offers comprehensive protection for SaaS data. Trusted by over 1,500 organizations across 100+ countries, Spin.AI helps enhance cyber resilience, security operations, and cost efficiency for businesses.

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.

ZeroGPT is a trusted AI detector tool that specializes in detecting AI-generated content like ChatGPT, GPT4, and Gemini. It offers advanced features such as AI summarization, paraphrasing, grammar and spell checking, translation, word counting, and citation generation. The tool is designed to provide highly accurate results and supports multiple languages. ZeroGPT stands out for its highlighted sentences feature, batch file upload capability, high accuracy model, and automatically generated reports. It utilizes DeepAnalyse™ Technology, a multi-stage methodology that optimizes accuracy while minimizing false positives and negatives. Users can unlock premium features and API access to enhance their writing skills and integrate the tool on a large scale.

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.

The GPT-2 Output Detector is an online tool that helps users identify whether a given text was generated by the GPT-2 language model. The tool is based on the RoBERTa implementation of Transformers, a popular natural language processing library. Users can enter text into the text box, and the tool will predict the probability that the text was generated by GPT-2. The results start to get reliable after around 50 tokens.

GRAIL is a healthcare company innovating to solve medicine’s most important challenges. Our team of leading scientists, engineers and clinicians are on an urgent mission to detect cancer early, when it is more treatable and potentially curable. GRAIL's Galleri® test is a first-of-its-kind multi-cancer early detection (MCED) test that can detect a signal shared by more than 50 cancer types and predict the tissue type or organ associated with the signal to help healthcare providers determine next steps.

AIDetect is a powerful AI content detector tool that allows users to identify AI-generated writing within any text. It offers cutting-edge features and high accuracy, comparable to Turnitin, to help users verify the authenticity of content. With advanced technology, AIDetect ensures that users can distinguish between human and AI-generated content effortlessly.

AI Detector is an online tool that uses advanced algorithms and machine learning to check if your written text is generated by AI or a human writer. It analyzes the writing style, sentence structure, and other linguistic patterns to determine the likelihood of AI authorship. The tool provides a percentage score indicating the probability of AI-generated content, helping users identify potential plagiarism or AI-assisted writing.

AIDP is a comprehensive platform that helps you find and remove the fingerprints of AI in documents. It includes automatic and manual tools for revising content that was written by ChatGPT and other AI models. With AIDP, you can: * Detect and wipe the traces of AI instantly. * See what triggers AI detection. * Get suggestions for wording changes and rewrites. * Make AI sound human. * Get a tone analysis to determine how your document sounds. * Find and wipe AI from any document.

BladeRunner is a browser plug-in that highlights AI-generated text directly on the page. It helps users detect AI-generated content in various contexts such as social media, news, education, e-commerce, and government communications. In the age of AI, where distinguishing between human and AI-generated content is challenging, BladeRunner aims to assist users in identifying AI impostors and maintaining a higher standard of accuracy in digital interactions.

AI Checker is a free tool and plagiarism detector that accurately identifies if a text is generated by AI tools like GPT-3, GPT-4, Gemini, OpenAI, and others. It helps users protect their content by detecting AI-generated text and human-written content. The tool uses advanced algorithms to provide accurate results and percentage analysis of AI-generated content within a text. AI Checker is beneficial for writers, students, educators, content marketers, freelancers, editors, publishers, researchers, and content consumers across different languages and contexts.

GPTKit is a free AI text generation detection tool that utilizes six different AI-based content detection techniques to identify and classify text as either human- or AI-generated. It provides reports on the authenticity and reality of the analyzed content, with an accuracy of approximately 93%. The first 2048 characters in every request are free, and users can register for free to get 2048 characters/request.

Decopy AI Content Detector is an AI tool designed to help users determine if a given text was written by a human or generated by AI. It accurately identifies AI-generated, paraphrased, and human-written content. The tool offers features such as AI content highlighting, superior detection accuracy, user-friendly interface, free AI detection, instant access without sign-up, and guaranteed privacy. Users can utilize the AI Detector for tasks like academic integrity checks, content creation, journalism verification, publishing standards maintenance, SEO content uniqueness, social media reliability checks, legal document originality verification, and corporate training material quality assurance.

AI Scam Detective is an AI tool designed to help users detect and prevent online scams. Users can paste messages or conversations into the tool, which then provides a score from 1-10 on the likelihood of it being a scam. Created by Sam Meehan, this tool aims to empower users to identify and avoid potential scams in their online interactions.

Unholy.ai is an AI tool designed to detect any 'unholiness' in the music you listen to. It uses advanced algorithms to analyze audio tracks and identify any elements that may be considered inappropriate or offensive. The tool is currently under construction and being developed by Saud with the help of GPT Bros. Unholy.ai aims to provide users with a unique way to ensure the music they listen to aligns with their preferences and values.

TrueBees is a deepfakes detector application designed to verify the trustworthiness of images shared on social media. It utilizes AI technology to detect AI-generated portraits and prevent their dissemination online. The tool is specifically tailored for media professionals and law firms to ensure the authenticity of images used in news articles, legal cases, and social media posts. TrueBees aims to combat the spread of deepfakes and disinformation by providing a reliable solution for image verification.

The AI Content Detector is an online tool that helps users determine the similarity score of AI-generated content and whether it was written by a human or an AI tool. It utilizes advanced algorithms and natural language processing to analyze text, providing a percentage-based authenticity result. Users can input text for analysis and receive accurate results regarding the likelihood of AI authorship. The tool compares syntax, vocabulary, and semantics with AI and human models, offering high accuracy in identifying paraphrased content.

ZeroGPT is a comprehensive AI detection tool that helps users identify AI-generated content. It offers a range of features, including sentence highlighting, batch file upload, high accuracy, and support for multiple languages. ZeroGPT's DeepAnalyse™ Technology employs a multi-stage methodology to analyze text and determine its origin. The tool is designed to minimize false positives and negatives, providing users with reliable results. ZeroGPT also offers a user-friendly API for organizations, enabling them to integrate the tool into their systems.

AI Voice Detector is an advanced tool designed to protect individuals and businesses from audio manipulation and AI voice scams. It offers a high model accuracy of 92% in identifying whether an audio is real or AI-generated. The tool can be used to detect AI voices in various platforms like YouTube, WhatsApp, TikTok, Zoom, and Google Meet. With features such as multilanguage support, background noise removal, and browser extension integration, AI Voice Detector stands out as a reliable solution for authenticating audio files.

Quetext is a plagiarism checker and AI content detector that helps students, teachers, and professionals identify potential plagiarism and AI in their work. With its deep search technology, contextual analysis, and smart algorithms, Quetext makes checking writing easier and more accurate. Quetext also offers a variety of features such as bulk uploads, source exclusion, enhanced citation generator, grammar & spell check, and Deep Search. With its rich and intuitive feedback, Quetext helps users find plagiarism and AI with less stress.

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.

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.

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.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

xGitGuard is an AI-based system developed by Comcast Cybersecurity Research and Development team to detect secrets (e.g., API tokens, usernames, passwords) exposed on GitHub repositories. It uses advanced Natural Language Processing to detect secrets at scale and with appropriate velocity. The tool provides workflows for detecting credentials and keys/tokens in both enterprise and public GitHub accounts. Users can set up search patterns, configure API access, run detections with or without ML filters, and train ML models for improved detection accuracy. xGitGuard also supports custom keyword scans for targeted organizations or repositories. The tool is licensed under Apache 2.0.

ShieldLM is a bilingual safety detector designed to detect safety issues in LLMs' generations. It aligns with human safety standards, supports customizable detection rules, and provides explanations for decisions. Outperforming strong baselines, ShieldLM is impressive across 4 test sets.

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.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

This leaderboard evaluates the hallucination rate of various Large Language Models (LLMs) when summarizing documents. It uses a model trained by Vectara to detect hallucinations in LLM outputs. The leaderboard includes models from OpenAI, Anthropic, Google, Microsoft, Amazon, and others. The evaluation is based on 831 documents that were summarized by all the models. The leaderboard shows the hallucination rate, factual consistency rate, answer rate, and average summary length for each model.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

Safeguards Shield is a security and alignment toolkit designed to detect unwanted inputs and LLM outputs. It provides tools to optimize RAG pipelines for accuracy and ensure trustworthy AI needs are met. The SDK aims to make LLMs accurate and secure, unlocking value faster by unifying a set of tools.

AITom is an open-source platform for AI-driven cellular electron cryo-tomography analysis. It is developed to process large amounts of Cryo-ET data, reconstruct, detect, classify, recover, and spatially model different cellular components using state-of-the-art machine learning approaches. The platform aims to automate cellular structure discovery and provide new insights into molecular biology and medical applications.

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

Detect logical fallacies and lapses in critical thinking to help avoid misinformation in the style of Socrates

AI Detector GPT is powered by Winston AI and created to help identify AI generated content. It is designed to help you detect use of AI Writing Chatbots such as ChatGPT, Claude and Bard and maintain integrity in academia and publishing. Winston AI is the most trusted AI content detector.

I help detect food allergies by analyzing eating habits.

Plagiarism Checker GPT is powered by Winston AI and created to help identify plagiarized content. It is designed to help you detect instances of plagiarism and maintain integrity in academia and publishing. Winston AI is the most trusted AI and Plagiarism Checker.

I find logical fallacies in texts.

AI content analysis expert for detecting AI authorship.

Detects and measures information credibility. Provides a "BS Score" (0-100) based on content analysis for misinformation signs, including factual inaccuracies and sensationalist language. Real-time feedback.

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

A virtual SOC analyst aiding in incident response.

To assist individuals seeking to learn about or work with Microsoft's Defender for Endpoint. I provide detailed explanations, step-by-step guides, troubleshooting advice, cybersecurity best practices, and demonstrations, all specifically tailored to Microsoft Defender for Endpoint.

Mit KI gegen Kartelle

GPT used to classify prompts as valid inputs or injection attempts. Json output.

Spam expert with comprehensive scam detection and education.

it is a meticulously crafted arsenal of knowledge, insights, and guidelines that is shaped to empower organizations in crafting, enhancing, and refining their cybersecurity defenses

I'm PhishCatcher, an expert in identifying phishing attempts.

A tool to help you decide if a website is part of a PBN or link network, created solely for link building. >> Get in touch with Gareth if you need a Freelance SEO for link building <<

I can guess your emotions! Tell me "Hi"

Expert på att hantera desinformation och misinformation

Multiple Environment Threat Evaluation of Resources (METEOR)™ Space Threats and Operational Risks to Mission (STORM)™ non-profit product AI co-pilot