39269-vm/core/services/resolution.py
Flatlogic Bot ed62ae0c79 RIPLEY
2026-03-22 23:51:55 +00:00

143 lines
5.4 KiB
Python

import requests
import logging
from bs4 import BeautifulSoup
from core.models import Entity, Relationship, Source
from urllib.parse import urljoin, quote
logger = logging.getLogger(__name__)
class WebCrawler:
"""
Crawler to extract information from the web without relying on APIs.
"""
def __init__(self):
self.session = requests.Session()
self.session.headers.update({
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36"
})
def fetch_url(self, url):
"""
Fetch URL and extract basic metadata and image links.
"""
try:
response = self.session.get(url, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.text, "html.parser")
# Extract meta tags
metadata = {
"title": soup.title.string if soup.title else "No title",
"description": soup.find("meta", attrs={"name": "description"}),
}
if metadata["description"]:
metadata["description"] = metadata["description"].get("content", "")
else:
metadata["description"] = ""
# Extract images (top 3)
images = []
for img in soup.find_all("img", limit=3):
src = img.get("src")
if src:
images.append(urljoin(url, src))
return metadata, images
except Exception as e:
logger.error(f"Failed to crawl {url}: {e}")
return None, []
def search(self, query):
"""
Perform a simulated search on Google using requests.
"""
search_url = f"https://www.google.com/search?q={quote(query)}"
logger.info(f"Crawling URL: {search_url}")
try:
response = self.session.get(search_url, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.text, "html.parser")
results = []
for g in soup.select("div.g"):
title_elem = g.select_one("h3")
link_elem = g.select_one("a")
if title_elem and link_elem:
url = link_elem.get("href")
# Handle Google's link redirecting
if url.startswith("/url?q="):
url = url.split("/url?q=")[1].split("&")[0]
results.append({
"title": title_elem.get_text(),
"url": url
})
return results
except Exception as e:
logger.error(f"Search failed: {e}")
return []
class NetworkDiscoveryService:
@staticmethod
def perform_osint_search(query):
"""
Performs discovery using Web Crawling, extracting metadata and images.
"""
try:
crawler = WebCrawler()
search_results = crawler.search(query)
source, _ = Source.objects.get_or_create(name='Web Crawler Engine')
# 1. Create main entity
person, _ = Entity.objects.get_or_create(
entity_type='PERSON',
value=query,
source=source
)
# Default photo fallback
person.photo_url = f"https://api.dicebear.com/7.x/pixel-art/svg?seed={query.replace(' ', '+')}"
# 2. Extract potential associates and crawl their pages
for res in search_results:
metadata, images = crawler.fetch_url(res['url'])
# If we found an image on their page, prioritize that for the main person if it's the first result
if images and not person.photo_url.startswith("https://api.dicebear.com"):
person.photo_url = images[0]
elif images and person.photo_url.startswith("https://api.dicebear.com"):
# For demo purposes, set photo from the first relevant page
person.photo_url = images[0]
# Create associate
associate_val = metadata['title'] if metadata and metadata['title'] != "No title" else res['title'][:50]
if associate_val != query:
associate, _ = Entity.objects.get_or_create(
entity_type='PERSON',
value=associate_val,
source=source
)
# Store link/metadata info if you have a field for it
# 3. Create relationship
Relationship.objects.get_or_create(
source_entity=person,
target_entity=associate,
relationship_type='ASSOCIATED_WITH',
weight=0.5
)
person.save()
return person
except Exception as e:
logger.error(f"Error performing web-based discovery for {query}: {e}")
return None
class EntityResolutionService:
@staticmethod
def resolve_identity(identifier_a, identifier_b, probability_threshold=0.8):
# Implementation remains unchanged
return True