Nmap API

Uses python3.10, Debian, python-Nmap, and flask framework to create an Nmap API that can do scans with a good speed online and is easy to deploy.

This is an implementation for our college PCL project which is still under development and constantly updating.

API Reference

Get all items

  GET /api/p1/{auth_key}/{target}
  GET /api/p2/{auth_key}/{target}
  GET /api/p3/{auth_key}/{target}
  GET /api/p4/{auth_key}/{target}
  GET /api/p5/{auth_key}/{target}

Parameter	Type	Description
`auth_key`	`string`	Required. The API auth key gebe
`target`	`string`	Required. The target Hostname and IP

Get item

  GET /api/p1/
  GET /api/p2/
  GET /api/p3/
  GET /api/p4/
  GET /api/p5/
  GET /api/p6/
  GET /api/p7/
  GET /api/p8/
  GET /api/p9/
  GET /api/p10/
  GET /api/p11/
  GET /api/p12/
  GET /api/p13/

Auth and User management

  GET /register/<int:user_id>/<string:password>

Parameter	Type	Description
`ID`	`Int`	user ID
`Passwd`	`String`	User Passwd

Improvements

Added GPT functionality with chunking module. The methodology is based on how Langchain GPT embeddings operate. Basically the operation goes like this:

Data -> Chunks_generator ─┐            ┌─> AI_Loop -> Data_Extraction -> Return_Data
                          ├─> Chunk1  ─┤
                          ├─> Chunk2  ─┤
                          ├─> Chunk3  ─┤
                          └─> Chunk N ─┘

AI code:

def AI(analize: str) -> dict[str, any]:
    prompt = f"""
        Do a NMAP scan analysis on the provided NMAP scan information
        The NMAP output must return in a JSON format accorging to the provided
        output format. The data must be accurate in regards towards a pentest report.
        The data must follow the following rules:
        1) The NMAP scans must be done from a pentester point of view
        2) The final output must be minimal according to the format given.
        3) The final output must be kept to a minimal.
        4) If a value not found in the scan just mention an empty string.
        5) Analyze everything even the smallest of data.
        6) Completely analyze the data provided and give a confirm answer using the output format.

        The output format:
        {{
            "critical score": [""],
            "os information": [""],
            "open ports": [""],
            "open services": [""],
            "vulnerable service": [""],
            "found cve": [""]
        }}

        NMAP Data to be analyzed: {analize}
    """
    messages = [{"content": prompt, "role": "assistant"}]
    response = openai.ChatCompletion.create(
        model=model_engine,
        messages=messages,
        max_tokens=2500,
        n=1,
        stop=None,
    )
    response = response['choices'][0]['message']['content']
    ai_output = {
        "markdown": response
    }

    return ai_output

Default_Key: e43d4 newer updates are still in progress

`p1`	`json`	Effective Scan	`-Pn -sV -T4 -O -F`
`p2`	`json`	Simple Scan	`-Pn -T4 -A -v`
`p3`	`json`	Low Power Scan	`-Pn -sS -sU -T4 -A -v`
`p4`	`json`	Partial Intense Scan	`-Pn -p- -T4 -A -v`
`p5`	`json`	Complete Intense Scan	`-Pn -sS -sU -T4 -A -PE -PP -PY -g 53 --script=vuln`
`p6`	`json`	Comprehensive Service Version Detection	`-Pn -sV -p- -A`
`p7`	`json`	Aggressive Scan with OS Detection	`-Pn -sS -sV -O -T4 -A`
`p8`	`json`	Script Scan for Common Vulnerabilities	`-Pn -sC`
`p9`	`json`	Intense Scan, All TCP Ports	`-Pn -p 1-65535 -T4 -A -v`
`p10`	`json`	UDP Scan	`-Pn -sU -T4`
`p11`	`json`	Service and Version Detection for Top Ports	`-Pn -sV --top-ports 100`
`p12`	`json`	Aggressive Scan with NSE Scripts for Vulnerabilities	`-Pn -sS -sV -T4 --script=default,discovery,vuln`
`p13`	`json`	Fast Scan for Common Ports	`-Pn -F`

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