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    Home»Security»Common Vulnerabilities and Exposures (CVEs)»CVE-2025-39458 – Mikado-Themes Foton PHP Remote File Inclusion Vulnerability

    CVE-2025-39458 – Mikado-Themes Foton PHP Remote File Inclusion Vulnerability

    May 19, 2025

    CVE ID : CVE-2025-39458

    Published : May 19, 2025, 7:15 p.m. | 22 minutes ago

    Description : Improper Control of Filename for Include/Require Statement in PHP Program (‘PHP Remote File Inclusion’) vulnerability in Mikado-Themes Foton allows PHP Local File Inclusion.This issue affects Foton: from n/a through 2.5.2.

    Severity: 8.1 | HIGH

    Visit the link for more details, such as CVSS details, affected products, timeline, and more…

    Hostinger

    Source: Read More

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    北汽车联网云平台基于阿里云数据库MongoDB版打造稳固底层核心,盘活车端数据以提升用戶体验

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    在数字化时代,车联网数据应用正在对汽车行业产生革命性的影响,成为商业模式变革的关键一环。车联网数据应用通过将车辆与互联网连接起来,为企业和消费者提供全新的商业价值和服务体验。车联网是新一代网络通信技术与汽车、电子、道路交通运输等领域深度融合的产业形态。 北汽集团旗下的北京汽车研究总院,负责支撑极狐和北京两大自主品牌乘用车及旗下车型的研发,涵盖整车研发全过程业务。智能网联是该研究总院的核心业务板块之一,主要承担车联网云平台、整车EE架构、智能车控、智能座舱、智能驾驶等业务,其中北汽车联网云平台通过集成云计算、物联网、大数据等先进技术,通过收集、处理和分析车辆数据,为车主、车企和交通管理部门提供智能化、个性化的服务。 据北汽车联网专业副总师左春刚介绍,北汽车联网云平台已经支持了北汽集团百万辆汽车的数据接入、数十万辆汽车同时在线业务,全平台数据量已超过亿级别。 大数据的应用已成为车联网发展的关键因素 随着车辆快速增长及业务需求的不断迭代,平台的数据量急剧增长,数据管理挑战重重,例如数据量大、更新频率快、格式复杂、数据并发高、查询效率低、数据安全等等。 对于汽车制造商而言,车联网数据的处理和利用技术一直处于快速革新进化过程。其中最重要的一点就是如何集中存储和管理大量不同的事务数据并对其使用,以及利用基于人工智能的解决方案和分析功能,充分挖掘所有这些数据的强大功能和业务潜力。 面对车联网平台上车辆数高速增长,采用传统数据库存储车辆信息已无法满足业务需求。北汽车联网云平台选用阿里云数据库MongoDB版支撑底层数据,打造了一个稳固的底层核心,实现了数据效力的层层向上传导,从业务层到应用层都明显有所受益。 文档模型更加直观,支撑数据复杂的格式 相比较于传统关系模型,MongoDB的JSON数据结构更加直观、更加灵活,非常适合车端数据的复杂格式、适合车联网场景中车辆相关基础信息的联合查询。将车辆基础信息迁移到MongoDB中进行存储管理,大大提升了数据应用效率。采用传统数据库存储时,车辆信息涉及多张表单,每张表单近百个字段,字段冗余复杂;采用MongoDB优化后,只需将所有车辆信息存储于一个集合中,更加易于读取、维护。 GeoJSON实现对位置数据计算、查询和展现 车辆位置计算是MongoDB在车联网云平台应用场景之一。针对在一定范围内对车辆停放情况进行筛查的场景,采用MongoDB GeoJSON (地理空间索引) 技术即可满足筛查要求,方便又高效。左春刚具体介绍道:在数据清洗阶段,输入车端原始数据,格式化数据为MongoDB存储格式,输出清洗后的规范数据;在数据计算阶段,使用地理空间索引技术筛选出特定范围内车辆,继而应用算法对位置进行聚类分析,输出车辆停放信息数据;在数据展示阶段,从MongoDB上实时获取数据,在地图上分类渲染车辆停放情况,实现通过界面直接查看。 支持Sharding、海量数据存储、高并发和频繁更新…

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