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Source channel @githubtrending · Post #14992 · Jul 23

#go#aws#azure#cncf#cost#cost_optimization#finops#gcp#k8s#kubernetes#monitoring#opencost#prometheus OpenCost is a free, open-source tool that helps you see and understand the costs of running Kubernetes clusters and cloud services in real time. It breaks down costs by cluster, node, namespace, pod, and more, across multiple cloud providers like AWS, Azure, and GCP, and even supports on-premises setups. This lets you track where your money is going, spot expensive resources, and manage your cloud spending better. It integrates with Prometheus for metrics and offers a user-friendly web interface and APIs for easy cost monitoring and exporting. Using OpenCost helps you control and optimize your cloud and Kubernetes expenses efficiently[1][2][3][4]. https://github.com/opencost/opencost

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AIGC

@aigcrubbish · Post #16 · 12/25/2024, 06:34 PM

libxml2 在 2.11.9、2.12.9 和 2.13.3 之前的版本中存在一个安全漏洞,SAX 解析器在自定义 SAX 处理程序尝试通过设置 "checked" 来覆盖实体内容时,仍然会为外部实体生成事件。这使得经典的 XXE(XML 外部实体注入)攻击成为可能。 该漏洞已在后续版本中修复,建议用户尽快升级到最新版本以避免潜在的安全风险。 参考链接: - [GitHub 安全公告](https://github.com/advisories/GHSA-6c2p-rqx3-w4px) - [NVD 漏洞详情](https://nvd.nist.gov/vuln/detail/CVE-2024-40896) - [libxml2 修复提交](https://gitlab.gnome.org/GNOME/libxml2/-/commit/1a8932303969907f6572b1b6aac4081c56adb5c6) - [libxml2 问题报告](https://gitlab.gnome.org/GNOME/libxml2/-/issues/761) #安全漏洞#XXE#libxml2#SAX解析器 #AIGC

djangoproject

@djangoproject · Post #551 · 01/23/2018, 04:28 PM

http://lxml.de/ #lxml is the most feature-rich and easy-to-use library for processing #XML and #HTML in the Python language. The lxml XML toolkit is a Pythonic binding for the #C libraries #libxml2 and #libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python #API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all #CPython versions from 2.6 to 3.6. See the introduction for more information about background and goals of the lxml project. Some common questions are answered in the FAQ.