A utility program to perform multiple operations for a given subnet/cidr ranges.

Features • Install • Usage • Library • Join Discord

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mapCIDR is developed to ease load distribution for mass scanning operations, it can be used both as a library and as independent CLI tool.

Features

• CIDR expansion support.
• CIDR slicing support.
• CIDR/IP aggregation support.
• CIDR based IP filter support.
• IP/PORT shuffling support.
• STD IN/OUT support.

Installation

go install -v github.com/projectdiscovery/mapcidr/cmd/mapcidr@latest

Usage

mapcidr -h

This will display help for the tool. Here are all the switches it supports.

INPUT:
   -cidr string          CIDR to process
   -l, -list string      File containing list of CIDRs to process
   -il, -ip-list string  File containing list of IPs to process

PROCESS:
   -sbc int                   Slice CIDRs by given CIDR count
   -sbh int                   Slice CIDRs by given HOST count
   -agg, -aggregate           Aggregate IPs/CIDRs into the minimum subnet
   -sip, -shuffle-ip          Shuffle input ip
   -sp, -shuffle-port string  Shuffle input ip:port

OUTPUT:
   -o, -output string  File to write output to
   -silent             Silent mode
   -version            Show version
   -skip-base          Skip base IPs (ending in .0) in output
   -skip-broadcast     Skip broadcast IPs (ending in .255) in output

Running mapCIDR

In order to get list of IPs for a give CIDR, use the following command.

CIDR expansion

mapcidr -cidr 173.0.84.0/24

                   ____________  ___    
  __ _  ___ ____  / ___/  _/ _ \/ _ \
 /  ' \/ _ '/ _ \/ /___/ // // / , _/   
/_/_/_/\_,_/ .__/\___/___/____/_/|_| v0.5
          /_/                                                     	 

		projectdiscovery.io

[WRN] Use with caution. You are responsible for your actions
[WRN] Developers assume no liability and are not responsible for any misuse or damage.

173.0.84.0
173.0.84.1
173.0.84.2
173.0.84.3
173.0.84.4
173.0.84.5
173.0.84.13
173.0.84.14
173.0.84.15
173.0.84.16

CIDR Slicing by CIDR

In order to slice given CIDR or list of CIDR by CIDR count or slice into multiple and equal smaller subnets, use the following command.

mapcidr -cidr 173.0.84.0/24 -sbc 10 -silent

173.0.84.0/27
173.0.84.32/27
173.0.84.64/27
173.0.84.96/27
173.0.84.128/27
173.0.84.160/27
173.0.84.208/28
173.0.84.192/28
173.0.84.240/28
173.0.84.224/28

CIDR slicing by HOST

In order to slice given CIDR for equal number of host count in each CIDR, use the following command.

mapcidr -cidr 173.0.84.0/16 -sbh 20000 -silent

173.0.0.0/18
173.0.64.0/18
173.0.128.0/18
173.0.192.0/18

Note: it's possible to obtain a perfect split only when the desired amount of slices or hosts per subnet is a powers of two. Otherwise, the tool will attempt to automatically find the best split strategy to obtain the desired outcome.

CIDR/IP aggregation

In order to merge multiple CIDR ranges into smaller subnet block, use the following command.

mapcidr -l cidrs.txt -silent -aggregate

In order to list CIDR blocks for given list of IPs, use the following command.

mapcidr -l ips.txt -silent -aggregate

CIDR based IP filtering

In order to filter IPs from the given list of CIDR ranges, use the following command.

mapcidr -ips ip-list.txt -l cirds.txt

Use mapCIDR as a library

It's possible to use the library directly in your go programs. The following code snippets outline how to divide a cidr into subnets, and how to divide the same into subnets containing a certain number of hosts

package main

import (
	"fmt"

	"github.com/projectdiscovery/mapcidr"
)

func main() {
	// Divide the CIDR into two subnets
	subnets1 := mapcidr.SplitN("192.168.1.0/24", 2)
	for _, subnet := range subnets1 {
		fmt.Println(subnet)
	}
	// Divide the CIDR into two subnets containing 128 hosts each
	subnets2 := mapcidr.SplitByNumber("192.168.1.0/24", 128)
	for _, subnet := range subnets2 {
		fmt.Println(subnet)
	}

	// List all ips in the CIDR
	ips, _ := mapcidr.IPAddresses("192.168.1.0/24")
	for _, ip := range ips {
		fmt.Println(ip)
	}
}

mapCDIR is made with 🖤 by the projectdiscovery team.