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Showing 4 open source projects for "network monitoring tool with python"

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  • Level Up Your Cyber Defense with External Threat Management Icon
    Level Up Your Cyber Defense with External Threat Management

    See every risk before it hits. From exposed data to dark web chatter. All in one unified view.

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  • Most modern and flexible cloud platform for MLM companies Icon
    Most modern and flexible cloud platform for MLM companies

    ERP-class software for multi-level marketing

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    netool toolkit 4.6

    netool toolkit 4.6

    MitM pentesting opensource toolkit

    Operative Systems Suported are: Linux-ubuntu, kali-linux, backtack-linux (un-continued), freeBSD, Mac osx (un-continued) Netool its a toolkit written using 'bash, python, ruby' that allows you to automate frameworks like Nmap, Driftnet, Sslstrip, Metasploit and Ettercap MitM attacks. this toolkit makes it easy tasks such as SNIFFING tcp/udp traffic, Man-In-The-Middle attacks, SSL-sniff, DNS-spoofing, D0S attacks in wan/lan networks, TCP/UDP packet manipulation using etter-filters, and...
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  • 2
    Insidias is a next-generation intrusion detection engine, with a focus on speed, efficiency, advanced pattern matching, parallel-processing, modularity, and expandability.
    Downloads: 0 This Week
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  • 3
    RogueScanner is a network security tool for automatically discovering rogue wireless access points by scanning a wired network. In addition to finding access points, it will classify all discovered network devices
    Downloads: 7 This Week
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  • 4
    Security analysis tools produced by The Ohio State University Network Security Group.
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  • Cloud data warehouse to power your data-driven innovation Icon
    Cloud data warehouse to power your data-driven innovation

    BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

    BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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