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Notes
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  • CyberSecurity
    • Penetration Testing
      • ELearnSecurity
        • eJPT
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        • Cross-origin resource sharing (CORS)
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        • Sql Injection
          • Examining the database
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          • Blind SQL injection
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      • TryHackMe
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          • 3. Gaining Access / Exploitation
            • Buffer Overflow
              • 1. Immunity Debugger
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              • OWASP Top 10
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              • Authentication Vulnerability
              • XML External Entity (XXE)
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              • ZTH: Obscure Web Vulns
              • Server Side Request Forgery (SSRF)
              • Insecure Direct Object Reference (IDOR)
              • ZTH : Continued
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                • Local File Inclusion (LFI)
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              • Jenkins
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                • Impacket's secretsdump.py
                • Kerberos
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                  • Enumerating SPN Accounts with Powershell
                  • Get SPN Account Ticket with Invoke-Kerberoast
                  • Kerberoasting with Rubeus & Impacket
                  • AS-REP Roasting with Rubeus/GetNPUsers.py
                  • Pass the Ticket with mimikatz
                  • Golden/Silver Ticket Attacks with mimikatz
                  • Kerberos Backdoors with mimikatz
                  • Harvesting and Brute-Forcing with Rubeus
                  • Conclusion and Resources
          • 4. Post Exploitation
            • Privilege Escalation
              • Linux
                • 1. Introduction
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                • 10. Passwords & Keys
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                • PrivEsc CTF Checklists
              • Windows
                • Token Impersonation
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                • Permission
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            • Tools
              • Meterpreter Modules
              • Impacket's Psexec
              • Impacket's mssqlclient.py
              • Firefox Decryptor
              • Socat - Reverse TCP Tunnel
            • Windows Active Directory
              • Enumeration with Powerview
              • Enumeration with Bloodhound (GUI)
              • Dumping Hashes with mimikatz
              • Golden Ticket Attacks with mimikatz
              • Enumeration with Server Manager
              • Maintaining Access
              • Additional Resources
          • 5. Covering Tracks
          • 6. Reporting
        • Networking Concepts
          • SSH Reverse Tunnels
        • Scripting
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          • Powershell
            • Basic Powershell Commands
            • Enumeration
        • Web Extensions
          • Shodan
          • Wappalyzer
      • Miscellaneous
        • SMTP Enumeration
        • Nmap Advanced Scanning
        • Persistence via Meterpreter
        • DNS Enumeration
        • NetBIOS & SMB
        • DHCP Starvation
        • Packet Manipulation
        • Hash Cracking
        • MITM
        • Msfvenom Payload in APK (Manual Embedding)
    • Blue Teaming
      • Digital Forensics & Incidence Response
        • Memory Acquisition with LIME
        • Disk Analysis with Autopsy
        • Data and Memory Collection with FireEye Redline
        • Memory Forensice with Volatility
      • Intrusion Detection
        • Intrusion Detection Systems (IDS)
        • Threat Monitoring with Security Information & Event Management (SIEM)
        • Security Event Monitoring
        • Host Based Intrusion Detection System (HIDS) - OSSEC
      • Miscellaneous
        • Docker Image Security Analysis with Trivy
  • DevOps
    • Infrastructure as a Code (IaC)
      • Ansible
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      • Terraform
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        • 15. Final Thoughts
    • Orchestration
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        • 1. Main K8s Components
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  • Development
    • Blockchain
      • FreeCodeCamp Course
        • 1. Introduction
        • 2. Solidity Basics
        • 3. Storage Factory
        • 4. Fund Me
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        • 6. Hardhat
        • 7. Hardhat | Fund Me
        • 8. Contract Lottery | Raffle
        • 9. IPFS
        • 10. ERC20s
        • 11. DeFi & Aave
        • 12. NFTs | Encoding
        • 13. Reentrancy Attack
    • Backend
      • NodeJs
        • Introduction
        • Additional Concepts
        • ExpressJs
    • Database
      • SQL
        • Basics
          • 1. Querying Data
          • 2. Filtering Data
          • 3. Joining Multiple Tables
          • 4. Grouping Data
          • 5. Set Operations
          • 6. Grouping Sets, Cube, and Rollup
          • 7. Subquery
          • 8. Common Table Expressions
          • 9. Modifying Data
          • 10. Transactions
          • 11. Import & Export Data
          • 12. Managing Tables
    • Testing
      • Test Driven Development (TDD)
      • Jest js
      • Cypress js
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On this page
  1. CyberSecurity
  2. Penetration Testing
  3. PortSwigger
  4. Sql Injection

Mitigation

Most instances of SQL injection can be prevented by using parameterized queries (also known as prepared statements) instead of string concatenation within the query.

The following code is vulnerable to SQL injection because the user input is concatenated directly into the query:

String query = "SELECT * FROM products WHERE category = '"+ input + "'";
Statement statement = connection.createStatement();
ResultSet resultSet = statement.executeQuery(query);

This code can be easily rewritten in a way that prevents the user input from interfering with the query structure:

PreparedStatement statement = connection.prepareStatement("SELECT * FROM products WHERE category = ?");
statement.setString(1, input);
ResultSet resultSet = statement.executeQuery();

Parameterized queries can be used for any situation where untrusted input appears as data within the query, including the WHERE clause and values in an INSERT or UPDATE statement. They can't be used to handle untrusted input in other parts of the query, such as table or column names, or the ORDER BY clause. Application functionality that places untrusted data into those parts of the query will need to take a different approach, such as white-listing permitted input values, or using different logic to deliver the required behavior.

For a parameterized query to be effective in preventing SQL injection, the string that is used in the query must always be a hard-coded constant, and must never contain any variable data from any origin. Do not be tempted to decide case-by-case whether an item of data is trusted, and continue using string concatenation within the query for cases that are considered safe. It is all too easy to make mistakes about the possible origin of data, or for changes in other code to violate assumptions about what data is tainted.

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Last updated 1 year ago