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Source channel @githubredteam · Post #84404 · 5月16日

🚨 GitHub 监控消息提醒 🚨发现关键词:#漏洞#检测#分析 📦项目名称:Open-Audit 👤项目作者:elegent-administrator 🛠开发语言: Python ⭐Star数量: 0 | 🍴Fork数量: 0 📅更新时间: 2026-05-16 03:56:40 📝项目描述: Open Audit是面向企业研发、开发者群体的AI智能明文代码安全审计工具,基于Python语言开发、FastCGI架构搭建,融合Semgrep工具链与自主研发的AI Agent,精准匹配数字时代代码安全审计的市场核心需求。工具直击行业传统审计工具误报率高、扩展能力弱、无法检测逻辑漏洞三大痛点,通过AI Agent深度分析漏洞代码上下文实现误报过滤,开放标准化接口支持企业自定义扩展漏洞检测方向,依托Agent的逻辑推理能力突破常规工具技术瓶颈,实现逻辑漏洞精准审计,同时完成跨平台适配,为中小微企业、互联网研发团队、个人开发者提供高效、可定制、高精准的代码安全审计解决方案,全方位筑牢代码研发安全防线。 🔗点击访问项目地址

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搜索 #memcached

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djangoproject

@djangoproject · Post #411 · 2017/08/13 12:08

http://sendapatch.se/projects/pylibmc/ #pylibmc is a client in Python for #memcached. It is a wrapper around TangentOrg‘s libmemcached library. The interface is intentionally made as close to python-memcached as possible, so that applications can drop-in replace it. pylibmc leverages among other things configurable behaviors, data pickling, data compression, battle-tested GIL retention, consistent distribution, and the binary memcached protocol.

djangoproject

@djangoproject · Post #410 · 2017/08/13 11:53

https://pypi.python.org/pypi/python-memcached This software is a 100% Python interface to the #memcached#memory#cache daemon. It is the #client side software which allows storing values in one or more, possibly remote, memcached servers. Search google for memcached for more information.

GitHub Trends

@githubtrending · Post #14772 · 2025/06/01 00:00

#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4]. https://github.com/dragonflydb/dragonfly