Lab: Blind SQL injection with conditional responses PRACTITIONER 带条件响应的SQL盲注靶场复盘

本文详细介绍了如何利用盲注SQL漏洞来找出靶场应用中管理员账户的密码。通过发送特定的SQL查询,确认了数据表的存在、用户'administrator'的存在以及密码长度为20。然后使用Intruder模式进行暴力破解,最终成功获取密码并登录。这个过程展示了盲注在无错误反馈情况下的应用。

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靶场完成目标:

This lab contains a blind SQL injection vulnerability. The application uses a tracking cookie for analytics, and performs an SQL query containing the value of the submitted cookie.

The results of the SQL query are not returned, and no error messages are displayed.But the application includes a “Welcome back” message in the page if the query returns any rows.

The database contains a different table called users, with columns called username and password. You need to exploit the blind SQL injection vulnerability to find out the password of the administrator user.

To solve the lab, log in as the administrator user.
综上所述,没有报错,但是如果合法就会出现welcome back的字样
靶场目标是使用administrator账户登录

开启演练

打开靶场并用burp抓包,发送到repeater

### DVWA SQL Blind Injection Medium Level Attack Method Tutorial In the context of DVWA (Damn Vulnerable Web Application), exploiting a SQL blind injection vulnerability at the medium difficulty level involves understanding how to interact with the application and craft specific payloads that can infer database structure or content based on true/false responses. The command provided serves as an example payload used within such attacks, specifically designed to retrieve table names from the current database schema by leveraging conditional logic in queries: ```sql select table_name from information_schema.tables where table_schema=database()[^1] ``` For executing this type of attack against DVWA's SQLi Blind challenge set to 'Medium', one approach is using automated tools like SqlMap which simplifies the process significantly. An invocation might look similar to what has been shared previously: ```bash py3 sqlmap.py -u "http://192.168.123.20/vulnerabilities/sqli_blind/?id=1&Submit=Submit#" --cookie="PHPSESSID=248dmjg65dksvfvf8kk0k7vqj0; security=low" --current-db[^2] ``` This tool automates much of the work involved in detecting vulnerabilities, extracting data through time-based boolean conditions without direct output feedback, and even taking over databases under certain circumstances—all while adhering to user-defined constraints regarding legality and ethics. When performing manual exploitation for educational purposes only, consider crafting custom scripts or modifying existing ones according to your environment setup. The key lies in constructing queries that cause different behaviors depending on whether they evaluate to true or false, allowing inference about underlying structures indirectly via side-channel observations. --related questions-- 1. How does changing the security level affect the effectiveness of SQL injection techniques? 2. What are some common defenses implemented against SQL injections? 3. Can you explain more about Information Schema Tables and their role in discovering database objects during penetration testing? 4. Are there any particular challenges associated with exploiting blind SQL injections compared to error-based methods?
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