2 datasets found
  1. Z

    Data from: SLQ Injection Attack for Test (D2)

    • data.niaid.nih.gov
    • portalcientifico.unileon.es
    • +1more
    Updated Jul 27, 2022
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    Adrián Campazas (2022). SLQ Injection Attack for Test (D2) [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_6906910
    Explore at:
    Dataset updated
    Jul 27, 2022
    Dataset provided by
    Adrián Campazas
    Ignacio Crespo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset has SQL injection attacks as malicious Netflow data. The attacks carried out are SQL injection for Union Query and Blind SQL injection. To perform the attacks, the SQLmap tool has been used.

    NetFlow traffic has generated using DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic). NetFlow is a network protocol developed by Cisco for the collection and monitoring of network traffic flow data generated. A flow is defined as a unidirectional sequence of packets with some common properties that pass through a network device.

    The version of NetFlow used to build the datasets is 5.

  2. Z

    SQL Injection Attack Netflow

    • data.niaid.nih.gov
    • zenodo.org
    Updated Sep 28, 2022
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    Adrián Campazas (2022). SQL Injection Attack Netflow [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_6907251
    Explore at:
    Dataset updated
    Sep 28, 2022
    Dataset provided by
    Adrián Campazas
    Ignacio Crespo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Introduction

    This datasets have SQL injection attacks (SLQIA) as malicious Netflow data. The attacks carried out are SQL injection for Union Query and Blind SQL injection. To perform the attacks, the SQLMAP tool has been used.

    NetFlow traffic has generated using DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic). NetFlow is a network protocol developed by Cisco for the collection and monitoring of network traffic flow data generated. A flow is defined as a unidirectional sequence of packets with some common properties that pass through a network device.

    Datasets

    The firts dataset was colleted to train the detection models (D1) and other collected using different attacks than those used in training to test the models and ensure their generalization (D2).

    The datasets contain both benign and malicious traffic. All collected datasets are balanced.

    The version of NetFlow used to build the datasets is 5.

        Dataset
        Aim
        Samples
        Benign-malicious
        traffic ratio
    
    
    
    
        D1
        Training
        400,003
        50%
    
    
        D2
        Test
        57,239
        50%
    

    Infrastructure and implementation

    Two sets of flow data were collected with DOROTHEA. DOROTHEA is a Docker-based framework for NetFlow data collection. It allows you to build interconnected virtual networks to generate and collect flow data using the NetFlow protocol. In DOROTHEA, network traffic packets are sent to a NetFlow generator that has a sensor ipt_netflow installed. The sensor consists of a module for the Linux kernel using Iptables, which processes the packets and converts them to NetFlow flows.

    DOROTHEA is configured to use Netflow V5 and export the flow after it is inactive for 15 seconds or after the flow is active for 1800 seconds (30 minutes)

    Benign traffic generation nodes simulate network traffic generated by real users, performing tasks such as searching in web browsers, sending emails, or establishing Secure Shell (SSH) connections. Such tasks run as Python scripts. Users may customize them or even incorporate their own. The network traffic is managed by a gateway that performs two main tasks. On the one hand, it routes packets to the Internet. On the other hand, it sends it to a NetFlow data generation node (this process is carried out similarly to packets received from the Internet).

    The malicious traffic collected (SQLI attacks) was performed using SQLMAP. SQLMAP is a penetration tool used to automate the process of detecting and exploiting SQL injection vulnerabilities.

    The attacks were executed on 16 nodes and launch SQLMAP with the parameters of the following table.

        Parameters
        Description
    
    
    
    
        '--banner','--current-user','--current-db','--hostname','--is-dba','--users','--passwords','--privileges','--roles','--dbs','--tables','--columns','--schema','--count','--dump','--comments', --schema'
        Enumerate users, password hashes, privileges, roles, databases, tables and columns
    
    
        --level=5
        Increase the probability of a false positive identification
    
    
        --risk=3
        Increase the probability of extracting data
    
    
        --random-agent
        Select the User-Agent randomly
    
    
        --batch
        Never ask for user input, use the default behavior
    
    
        --answers="follow=Y"
        Predefined answers to yes
    

    Every node executed SQLIA on 200 victim nodes. The victim nodes had deployed a web form vulnerable to Union-type injection attacks, which was connected to the MYSQL or SQLServer database engines (50% of the victim nodes deployed MySQL and the other 50% deployed SQLServer).

    The web service was accessible from ports 443 and 80, which are the ports typically used to deploy web services. The IP address space was 182.168.1.1/24 for the benign and malicious traffic-generating nodes. For victim nodes, the address space was 126.52.30.0/24. The malicious traffic in the test sets was collected under different conditions. For D1, SQLIA was performed using Union attacks on the MySQL and SQLServer databases.

    However, for D2, BlindSQL SQLIAs were performed against the web form connected to a PostgreSQL database. The IP address spaces of the networks were also different from those of D1. In D2, the IP address space was 152.148.48.1/24 for benign and malicious traffic generating nodes and 140.30.20.1/24 for victim nodes.

    To run the MySQL server we ran MariaDB version 10.4.12. Microsoft SQL Server 2017 Express and PostgreSQL version 13 were used.

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Share
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Click to copy link
Link copied
Close
Cite
Adrián Campazas (2022). SLQ Injection Attack for Test (D2) [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_6906910

Data from: SLQ Injection Attack for Test (D2)

Related Article
Explore at:
Dataset updated
Jul 27, 2022
Dataset provided by
Adrián Campazas
Ignacio Crespo
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset has SQL injection attacks as malicious Netflow data. The attacks carried out are SQL injection for Union Query and Blind SQL injection. To perform the attacks, the SQLmap tool has been used.

NetFlow traffic has generated using DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic). NetFlow is a network protocol developed by Cisco for the collection and monitoring of network traffic flow data generated. A flow is defined as a unidirectional sequence of packets with some common properties that pass through a network device.

The version of NetFlow used to build the datasets is 5.

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