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Context for your AI agents
Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.

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1

Atheris

A Coverage-Guided, Native Python Fuzzer

Atheris is a coverage-guided fuzzer for CPython that treats Python as a first-class fuzzing target, enabling rapid discovery of crashes and logic errors in pure-Python code and native extensions. It hooks into Python’s interpreter to collect fine-grained coverage and uses that signal to evolve inputs, pushing programs into previously unexplored code paths. Because many Python libraries are thin wrappers over C/C++ code, Atheris is equally adept at surfacing memory safety issues in extension modules compiled with sanitizers. ...

Downloads: 0 This Week

Last Update: 2025-11-25
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2

FuzzBench

FuzzBench - Fuzzer benchmarking as a service

...By running experiments at Google scale, FuzzBench ensures consistent, unbiased, and data-driven evaluations that support academic and industrial fuzzing research.

Downloads: 0 This Week

Last Update: 2 days ago
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3

HotFuzz

Automatic fuzzing proxy.

Downloads: 0 This Week

Last Update: 2013-04-26
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4

FileSull

A beginning of adaptation of Sulley Fuzzing Framework for file fuzzing and working on Unix.

Downloads: 0 This Week

Last Update: 2014-04-26
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Cloud data warehouse to power your data-driven innovation
BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.

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