有时候网站sqlserver数据库被挂马了,网上的很多软件与方法都是针对text小于8000的,这里的方法貌似可行,需要的朋友可以参考下。
首先备份数据库,以防不必要的损失。而后对所有被挂马的小于8000字符的varchar字段执行
代码如下:
update 表名 set 字段名=replace(字段名,'','')
其中为挂马字段。执行后挂马字段被清除。但是有部分字段,比如内容字段等大于8000字符的varchar字段则需要执行
代码如下:
update 表名 set 表项=replace(cast(表项 as varchar(8000)),' ','')
来更新被挂马字段,而房产网由于内容比较多,执行以上语句的时候会发生假死现象,于是加个区间分两次进行,一次处理15000条得以解决。
代码如下:
update 表名 set 表项=replace(cast(表项 as varchar(8000)),' ','') where id>1 and id
以上被挂马问题一般都是sql数据库,这是sql数据库特有的注入漏洞。换数据库不现实,只能针对以上情况进行防范。思路就是在所有数据库链接请求那里做相应的过滤。
代码如下:
Response.Buffer = True '缓存页面
'防范get注入
If Request.QueryString "" Then StopInjection(Request.QueryString)
'防范post注入
If Request.Form "" Then StopInjection(Request.Form)
'防范cookies注入
If Request.Cookies "" Then StopInjection(Request.Cookies)
'正则子函数
Function StopInjection(Values)
Dim regEx
Set regEx = New RegExp
regEx.IgnoreCase = True
regEx.Global = True
regEx.Pattern = "'|;|#|([\s\b+()]+([email=select%7Cupdate%7Cinsert%7Cdelete%7Cdeclare%7C@%7Cexec%7Cdbcc%7Calter%7Cdrop%7Ccreate%7Cbackup%7Cif%7Celse%7Cend%7Cand%7Cor%7Cadd%7Cset%7Copen%7Cclose%7Cuse%7Cbegin%7Cretun%7Cas%7Cgo%7Cexists)[/s/b]select|update|insert|delete|declare|@|exec|dbcc|alter|drop|create|backup|if|else|end|and|or|add|set|open|close|use|begin|retun|as|go|exists)[\s\b[/email]+]*)"
Dim sItem, sValue
For Each sItem In Values
sValue = Values(sItem)
If regEx.Test(sValue) Then
Response.Write ""
Response.End
End If
Next
Set regEx = Nothing
End function
%>
做一个通用的sql防注入页面,把它包含在conn.asp数据库连接语句里边,这样就实现了全站的防范 sql 注入的攻击了。但是前台的类似?id=这样的语句还是存在注入漏洞,需要我们严格过滤 request.form 和 request.querystring 获取的内容。坚决不用 request("name") 这样的方式获取值,凡是采用 cookies 保存的内容,尽量不要用在sql语句里进行查询数据库操作。
如果不熟悉sqlserver的朋友可以用软件来实现

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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