Search Results for "evidence"
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Showing 122 open source projects for "evidence"
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Quint Code
Structured reasoning framework for Claude Code, Gemini, and Cursor
Quint Code is a structured reasoning and decision-support framework aimed at making AI-assisted software engineering and decision workflows more rigorous and auditable. It implements the First Principles Framework (FPF) to guide users and AI tools through hypothesis generation, logical verification, evidence gathering, and documented decision making, reducing reliance on ad hoc or “vibe” coding. Instead of accepting the first plausible answer generated by an AI assistant, Quint Code encourages generating multiple competing hypotheses, verifying them, and validating them against real evidence stored in a structured “knowledge base” within your project. ... -
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Shannon
Fully autonomous AI hacker to find actual exploits in your web apps
...The project blends source-aware analysis with automated web interaction so it can validate issues like injection flaws, authentication bypasses, and other exploitable paths in a way that resembles an actual attacker’s workflow. Instead of requiring you to manually reproduce findings, Shannon is designed to produce actionable evidence that a weakness can be weaponized, which helps teams prioritize what truly matters. It positions itself as a pre-attacker safety net, aiming to break your web app before someone else does and thereby reduce the gap between “potentially vulnerable” and “confirmed exploitable.” -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
...The overall workflow aims to minimize hallucinations by grounding outputs in retrieved material and then applying structured reasoning over that evidence before generating a final report. -
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CampusShame
Crowdsource and document the reputational history of companies
...It compiles lists of companies that have had so-called “shameful” behaviors, such as rescinding offers, canceling intention letters, or terminating three-party agreements after acceptance, alongside a parallel list of companies without reported negative incidents. The project draws on publicly available anecdotes, snapshots, and forum posts from platforms such as NowCoder, Maimai, and Zhihu to provide evidence and context for each entry, preserving details that might otherwise be lost as threads get deleted or censored. It also includes commentary on recruitment pitfalls and encourages contributors to share their own experiences or corrections to keep the list up to date. -
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MemProcFS Analyzer
Automated Forensic Analysis of Windows Memory Dumps for DFIR
...The Analyzer layer adds higher-level parsing and extraction routines—for example, carving strings, locating injected modules, enumerating handles, or reconstructing network sockets—so investigators can go from raw memory to actionable evidence more quickly. It emphasizes automation and reproducibility: parsers can be chained, results exported, and reports templated to fit incident workflows. Because memory contains transient but critical traces of running malware or misuse, the project focuses on robust parsing in the face of corruption and mismatched OS versions. -
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MetaScreener
AI-powered tool for efficient abstract and PDF screening
MetaScreener is an open-source AI-assisted tool designed to streamline the screening process in systematic literature reviews and academic research workflows. The system helps researchers analyze large collections of academic abstracts and research papers to determine which studies are relevant for inclusion in evidence synthesis projects. Instead of manually reviewing hundreds or thousands of documents, researchers can use MetaScreener to apply machine learning techniques that assist with classification and prioritization of candidate papers. The platform can analyze both abstracts and full PDF documents, enabling automated filtering based on research criteria defined by the user. ... -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. ... -
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ResultTypes.jl
A Result type for Julia—it's like Nullables for Exceptions
ResultTypes provides a Result type that can hold either a value or an error. This allows us to return a value or an error in a type-stable manner without throwing an exception. -
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AbstractGPs.jl
Abstract types and methods for Gaussian Processes
AbstractGPs.jl is a package that defines a low-level API for working with Gaussian processes (GPs), and basic functionality for working with them in the simplest cases. As such it is aimed more at developers and researchers who are interested in using it as a building block than end-users of GPs. You may want to go through the main API design documentation. -
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Mobile Verification Toolkit
Helps with conducting forensics of mobile devices
...It has been developed and released by the Amnesty International Security Lab in July 2021 in the context of the Pegasus project along with a technical forensic methodology and forensic evidence. MVT is a forensic research tool intended for technologists and investigators. Using it requires understanding the basics of forensic analysis and using command-line tools. This is not intended for end-user self-assessment. If you are concerned with the security of your device please seek expert assistance. Compare extracted records to a provided list of malicious indicators in STIX2 format. ... -
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Tailslayer
Library for reducing tail latency in RAM reads
Tailslayer is a cybersecurity and forensic analysis tool designed to extract and analyze artifacts from Tails OS environments. It focuses on uncovering traces of activity in systems that are designed to be privacy-preserving and ephemeral. The tool helps investigators identify residual data such as logs, configurations, or usage traces that may persist despite Tails’ security features. It is particularly relevant for digital forensics and research into privacy systems. Tailslayer emphasizes... -
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HolmesGPT
CNCF Sandbox Project
...The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. The project is developed by Robusta and has been accepted as a Cloud Native Computing Foundation Sandbox project, highlighting its relevance to the cloud-native ecosystem. It is designed to operate as an automated troubleshooting assistant that can analyze incidents continuously and support on-call engineers during outages. -
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Codex Autoresearch
A codex plugin for running optimization loops inside a codebase
...The framework supports multiple operational modes, including debugging, planning, security auditing, and release validation. It can run unattended for extended periods, producing logs of experiments and improvements. This approach transforms software development into an iterative, evidence-driven optimization process rather than manual trial and error. -
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MiroThinker
MiroThinker is an open source deep research agent
...Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that involve searching for information, analyzing evidence, and synthesizing conclusions. The platform is optimized for research tasks such as financial forecasting, knowledge discovery, and large-scale information synthesis. MiroThinker has been evaluated on several agent benchmarks and has demonstrated strong performance on tests designed to measure deep research capabilities. -
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ArchiveBox
Open source self-hosted web archiving
...ArchiveBox is an open source tool that lets organizations & individuals archive both public & private web content while retaining control over their data. It can be used to save copies of bookmarks, preserve evidence for legal cases, backup photos from FB/Insta/Flickr or media from YT/Soundcloud/etc., save research papers, and more. ArchiveBox is an open-source, self-hosted web archiving tool for saving websites offline. It helps organizations and individuals preserve bookmarks, research papers, and social media content, among others. -
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Scira
AI-powered search engine that helps you find information
Scira is an open source AI-powered search and research assistant designed to provide fast, conversational answers grounded in web and knowledge sources. The project combines a modern web interface with retrieval-augmented generation techniques to deliver responses that are both natural language friendly and evidence oriented. It is built for developers who want to deploy their own Perplexity-style or AI search experience without relying on proprietary hosted services. Scira emphasizes speed, clean UI design, and extensibility so teams can customize data sources, models, and ranking logic. The architecture typically supports real-time querying, streaming responses, and modular backend components. ... -
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Tailsnitch
A security auditor for Tailscale configurations
...Tailsnitch supports authentication via the Tailscale API (including OAuth or API keys) and provides options to filter findings, run only high-severity checks, and produce compliance artifacts like SOC 2 evidence exports. -
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Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. It uses a mix of synthetic data generation, fine-tuning and reinforcement learning; supports benchmarks like web search, document understanding, question answering, “agentic” tasks; provides inference tools, evaluation scripts, and “web agent” style interfaces. ... -
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web-eval-agent MCP Server
An MCP server that autonomously evaluates web applications
web-eval-agent is a Model Context Protocol (MCP) server that spins up a browser-use–capable debugging agent to autonomously run and evaluate web apps straight from your editor. It’s positioned as a “let the coding agent debug itself” companion: the agent launches the app, navigates flows, captures evidence, and iterates on failures without manual copy-pasting of logs. The repository focuses on developer ergonomics, exposing typed MCP tools so clients like Claude Desktop can start sessions, gather traces, and reason over failures with structured artifacts. Marketing and README material emphasize supercharging local debugging loops by combining live browser execution with LLM-driven hypotheses and fixes. ... -
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Open Deep Research
An AI-powered research assistant that performs iterative research
...It is intentionally kept compact, with a codebase under roughly 500 lines, making it highly approachable for experimentation and learning. The architecture demonstrates how modern agent pipelines can continuously gather evidence, extract learnings, and adjust research direction over time. -
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Trillian
A transparent, highly scalable and cryptographically verifiable data
...The system is designed for horizontal scale with gRPC APIs, enabling multiple frontends and sequencers to operate over a shared backend. Common use cases include certificate transparency, package registries, and audit logs where public verifiability or tamper evidence is required. Trillian exposes both “log” and “map” primitives so developers can choose between append-only timelines or verifiable dictionaries depending on their data model. By making verification independent of trust in the operator, trillian helps build systems that are auditable by external parties. -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
...It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. The result is a repeatable process for scoping questions, collecting evidence, and producing a concise report with citations and reasoning steps. -
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BrowserTools MCP
Monitor browser logs directly from Cursor
...It can capture console/network logs, DOM snapshots, and screenshots, and expose them as typed resources the agent can query or act on. The design aims to make IDE agents (e.g., Cursor, Claude Desktop) more “web-aware,” enabling workflows like reproducing a bug, collecting evidence, and proposing fixes without copy-pasting. Documentation and community guides outline a quick setup, including the extension, the MCP server process, and common troubleshooting steps. The project is actively maintained, with public commit activity and discussions around connectivity and reliability in different IDEs. Overall, it bridges the gap between local coding agents and the real browser they need to observe and manipulate. -
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Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
...This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. Simply plugin your neural network, specifying (1) the image dimensions as well as (2) the name (or index) of the hidden layer, whose output is used as the latent representation used for self-supervised training. -
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Rogue
AI Agent Evaluator & Red Team Platform
...During testing, Rogue records conversations and produces detailed reports that explain whether the agent passed or failed each scenario. These reports include reasoning and evidence, helping developers understand why a particular failure occurred.
