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.
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 /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/
| Parameter | Return data | Description | Nmap Command |
|---|
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 |
GET /register/<int:user_id>/<string:password>
| Parameter | Type | Description |
|---|
ID | Int | user ID |
Passwd | String | User Passwd |
Added GPT functionality with chunking module.The methodology is based on howLangchain 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:
defAI(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 }returnai_outputDefault_Key:e43d4newer updates are still in progress