Feat/attack map improvement (#57)
* feat: enhance IP reputation management with city data and geolocation integration * feat: enhance dashboard with city coordinates and improved marker handling * feat: update chart version to 0.2.1 in Chart.yaml, README.md, and values.yaml * feat: update logo format and size in README.md * feat: improve location display logic in dashboard for attackers and IPs
This commit is contained in:
Lorenzo Venerandi
committed by
GitHub
GitHub
parent
8c76f6c847
commit
5aca684df9
@@ -1,10 +1,10 @@
|
||||
<h1 align="center">🕷️ Krawl</h1>
|
||||
<h1 align="center">Krawl</h1>
|
||||
|
||||
<h3 align="center">
|
||||
<a name="readme-top"></a>
|
||||
<img
|
||||
src="img/krawl-logo.jpg"
|
||||
height="200"
|
||||
src="img/krawl-svg.svg"
|
||||
height="250"
|
||||
>
|
||||
</h3>
|
||||
<div align="center">
|
||||
|
||||
@@ -2,8 +2,8 @@ apiVersion: v2
|
||||
name: krawl-chart
|
||||
description: A Helm chart for Krawl honeypot server
|
||||
type: application
|
||||
version: 0.2.0
|
||||
appVersion: 0.2.0
|
||||
version: 0.2.1
|
||||
appVersion: 0.2.1
|
||||
keywords:
|
||||
- honeypot
|
||||
- security
|
||||
|
||||
@@ -20,13 +20,13 @@ helm repo update
|
||||
### Install from OCI Registry
|
||||
|
||||
```bash
|
||||
helm install krawl oci://ghcr.io/blessedrebus/krawl-chart --version 0.1.5-dev
|
||||
helm install krawl oci://ghcr.io/blessedrebus/krawl-chart --version 0.2.1
|
||||
```
|
||||
|
||||
Or with a specific namespace:
|
||||
|
||||
```bash
|
||||
helm install krawl oci://ghcr.io/blessedrebus/krawl-chart --version 0.1.5-dev -n krawl --create-namespace
|
||||
helm install krawl oci://ghcr.io/blessedrebus/krawl-chart --version 0.2.1 -n krawl --create-namespace
|
||||
```
|
||||
|
||||
### Install the chart locally
|
||||
|
||||
@@ -3,7 +3,7 @@ replicaCount: 1
|
||||
image:
|
||||
repository: ghcr.io/blessedrebus/krawl
|
||||
pullPolicy: Always
|
||||
tag: "latest"
|
||||
tag: "0.2.1"
|
||||
|
||||
imagePullSecrets: []
|
||||
nameOverride: "krawl"
|
||||
|
||||
@@ -398,6 +398,7 @@ class DatabaseManager:
|
||||
asn: str,
|
||||
asn_org: str,
|
||||
list_on: Dict[str, str],
|
||||
city: Optional[str] = None,
|
||||
) -> None:
|
||||
"""
|
||||
Update IP rep stats
|
||||
@@ -408,6 +409,7 @@ class DatabaseManager:
|
||||
asn: IP address ASN
|
||||
asn_org: IP address ASN ORG
|
||||
list_on: public lists containing the IP address
|
||||
city: City name (optional)
|
||||
|
||||
"""
|
||||
session = self.session
|
||||
@@ -419,6 +421,8 @@ class DatabaseManager:
|
||||
ip_stats.asn = asn
|
||||
ip_stats.asn_org = asn_org
|
||||
ip_stats.list_on = list_on
|
||||
if city:
|
||||
ip_stats.city = city
|
||||
session.commit()
|
||||
except Exception as e:
|
||||
session.rollback()
|
||||
|
||||
@@ -34,14 +34,17 @@ def main():
|
||||
|
||||
if payload.get("results"):
|
||||
data = payload["results"][0]
|
||||
country_iso_code = data["geoip_data"]["country_iso_code"]
|
||||
asn = data["geoip_data"]["asn_autonomous_system_number"]
|
||||
asn_org = data["geoip_data"]["asn_autonomous_system_organization"]
|
||||
geoip_data = data["geoip_data"]
|
||||
country_iso_code = geoip_data.get("country_iso_code")
|
||||
asn = geoip_data.get("asn_autonomous_system_number")
|
||||
asn_org = geoip_data.get("asn_autonomous_system_organization")
|
||||
city = geoip_data.get("city_name") # Extract city name from API
|
||||
list_on = data["list_on"]
|
||||
|
||||
sanitized_country_iso_code = sanitize_for_storage(country_iso_code, 3)
|
||||
sanitized_asn = sanitize_for_storage(asn, 100)
|
||||
sanitized_asn_org = sanitize_for_storage(asn_org, 100)
|
||||
sanitized_city = sanitize_for_storage(city, 100) if city else None
|
||||
sanitized_list_on = sanitize_dict(list_on, 100000)
|
||||
|
||||
db_manager.update_ip_rep_infos(
|
||||
@@ -50,6 +53,7 @@ def main():
|
||||
sanitized_asn,
|
||||
sanitized_asn_org,
|
||||
sanitized_list_on,
|
||||
sanitized_city, # Pass city to database
|
||||
)
|
||||
except requests.RequestException as e:
|
||||
app_logger.warning(f"Failed to fetch IP rep for {ip}: {e}")
|
||||
|
||||
@@ -548,6 +548,11 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
background: #161b22;
|
||||
border-top: 6px solid #30363d;
|
||||
}}
|
||||
/* Remove the default leaflet icon background */
|
||||
.ip-custom-marker {{
|
||||
background: none !important;
|
||||
border: none !important;
|
||||
}}
|
||||
.ip-marker {{
|
||||
border: 2px solid #fff;
|
||||
border-radius: 50%;
|
||||
@@ -558,27 +563,46 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
font-weight: bold;
|
||||
color: white;
|
||||
cursor: pointer;
|
||||
transition: transform 0.2s, box-shadow 0.2s;
|
||||
}}
|
||||
.ip-marker:hover {{
|
||||
transform: scale(1.15);
|
||||
}}
|
||||
.marker-attacker {{
|
||||
background: #f85149;
|
||||
box-shadow: 0 0 8px rgba(248, 81, 73, 0.8), inset 0 0 4px rgba(248, 81, 73, 0.5);
|
||||
}}
|
||||
.marker-attacker:hover {{
|
||||
box-shadow: 0 0 15px rgba(248, 81, 73, 1), inset 0 0 6px rgba(248, 81, 73, 0.7);
|
||||
}}
|
||||
.marker-bad_crawler {{
|
||||
background: #f0883e;
|
||||
box-shadow: 0 0 8px rgba(240, 136, 62, 0.8), inset 0 0 4px rgba(240, 136, 62, 0.5);
|
||||
}}
|
||||
.marker-bad_crawler:hover {{
|
||||
box-shadow: 0 0 15px rgba(240, 136, 62, 1), inset 0 0 6px rgba(240, 136, 62, 0.7);
|
||||
}}
|
||||
.marker-good_crawler {{
|
||||
background: #3fb950;
|
||||
box-shadow: 0 0 8px rgba(63, 185, 80, 0.8), inset 0 0 4px rgba(63, 185, 80, 0.5);
|
||||
}}
|
||||
.marker-good_crawler:hover {{
|
||||
box-shadow: 0 0 15px rgba(63, 185, 80, 1), inset 0 0 6px rgba(63, 185, 80, 0.7);
|
||||
}}
|
||||
.marker-regular_user {{
|
||||
background: #58a6ff;
|
||||
box-shadow: 0 0 8px rgba(88, 166, 255, 0.8), inset 0 0 4px rgba(88, 166, 255, 0.5);
|
||||
}}
|
||||
.marker-regular_user:hover {{
|
||||
box-shadow: 0 0 15px rgba(88, 166, 255, 1), inset 0 0 6px rgba(88, 166, 255, 0.7);
|
||||
}}
|
||||
.marker-unknown {{
|
||||
background: #8b949e;
|
||||
box-shadow: 0 0 8px rgba(139, 148, 158, 0.8), inset 0 0 4px rgba(139, 148, 158, 0.5);
|
||||
}}
|
||||
.marker-unknown:hover {{
|
||||
box-shadow: 0 0 15px rgba(139, 148, 158, 1), inset 0 0 6px rgba(139, 148, 158, 0.7);
|
||||
}}
|
||||
.leaflet-bottom.leaflet-right {{
|
||||
display: none !important;
|
||||
}}
|
||||
@@ -1011,7 +1035,7 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
if (stats.country_code || stats.city) {{
|
||||
html += '<div class="stat-row">';
|
||||
html += '<span class="stat-label-sm">Location:</span>';
|
||||
html += `<span class="stat-value-sm">${{stats.city || ''}}${{stats.city && stats.country_code ? ', ' : ''}}${{stats.country_code || 'Unknown'}}</span>`;
|
||||
html += `<span class="stat-value-sm">${{stats.city ? (stats.country_code ? `${{stats.city}}, ${{stats.country_code}}` : stats.city) : (stats.country_code || 'Unknown')}}</span>`;
|
||||
html += '</div>';
|
||||
}}
|
||||
|
||||
@@ -1345,7 +1369,7 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
<td>${{attacker.total_requests}}</td>
|
||||
<td>${{formatTimestamp(attacker.first_seen)}}</td>
|
||||
<td>${{formatTimestamp(attacker.last_seen)}}</td>
|
||||
<td>${{attacker.city || 'Unknown'}}${{attacker.city && attacker.country_code ? ', ' : ''}}${{attacker.country_code || ''}}</td>
|
||||
<td>${{attacker.city ? (attacker.country_code ? `${{attacker.city}}, ${{attacker.country_code}}` : attacker.city) : (attacker.country_code || 'Unknown')}}</td>
|
||||
</tr>
|
||||
<tr class="ip-stats-row" id="stats-row-${{attacker.ip.replace('.', '-')}}" style="display: none;">
|
||||
<td colspan="6" class="ip-stats-cell">
|
||||
@@ -1895,7 +1919,6 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
let allIps = [];
|
||||
let mapMarkers = [];
|
||||
let markerLayers = {{}};
|
||||
let circleLayers = {{}};
|
||||
|
||||
const categoryColors = {{
|
||||
attacker: '#f85149',
|
||||
@@ -1945,7 +1968,60 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
// Get max request count for scaling
|
||||
const maxRequests = Math.max(...allIps.map(ip => ip.total_requests || 0));
|
||||
|
||||
// Create a map of country locations (approximate country centers)
|
||||
// City coordinates database (major cities worldwide)
|
||||
const cityCoordinates = {{
|
||||
// United States
|
||||
'New York': [40.7128, -74.0060], 'Los Angeles': [34.0522, -118.2437],
|
||||
'San Francisco': [37.7749, -122.4194], 'Chicago': [41.8781, -87.6298],
|
||||
'Seattle': [47.6062, -122.3321], 'Miami': [25.7617, -80.1918],
|
||||
'Boston': [42.3601, -71.0589], 'Atlanta': [33.7490, -84.3880],
|
||||
'Dallas': [32.7767, -96.7970], 'Houston': [29.7604, -95.3698],
|
||||
'Denver': [39.7392, -104.9903], 'Phoenix': [33.4484, -112.0740],
|
||||
// Europe
|
||||
'London': [51.5074, -0.1278], 'Paris': [48.8566, 2.3522],
|
||||
'Berlin': [52.5200, 13.4050], 'Amsterdam': [52.3676, 4.9041],
|
||||
'Moscow': [55.7558, 37.6173], 'Rome': [41.9028, 12.4964],
|
||||
'Madrid': [40.4168, -3.7038], 'Barcelona': [41.3874, 2.1686],
|
||||
'Milan': [45.4642, 9.1900], 'Vienna': [48.2082, 16.3738],
|
||||
'Stockholm': [59.3293, 18.0686], 'Oslo': [59.9139, 10.7522],
|
||||
'Copenhagen': [55.6761, 12.5683], 'Warsaw': [52.2297, 21.0122],
|
||||
'Prague': [50.0755, 14.4378], 'Budapest': [47.4979, 19.0402],
|
||||
'Athens': [37.9838, 23.7275], 'Lisbon': [38.7223, -9.1393],
|
||||
'Brussels': [50.8503, 4.3517], 'Dublin': [53.3498, -6.2603],
|
||||
'Zurich': [47.3769, 8.5417], 'Geneva': [46.2044, 6.1432],
|
||||
'Helsinki': [60.1699, 24.9384], 'Bucharest': [44.4268, 26.1025],
|
||||
'Saint Petersburg': [59.9343, 30.3351], 'Manchester': [53.4808, -2.2426],
|
||||
'Roubaix': [50.6942, 3.1746], 'Frankfurt': [50.1109, 8.6821],
|
||||
'Munich': [48.1351, 11.5820], 'Hamburg': [53.5511, 9.9937],
|
||||
// Asia
|
||||
'Tokyo': [35.6762, 139.6503], 'Beijing': [39.9042, 116.4074],
|
||||
'Shanghai': [31.2304, 121.4737], 'Singapore': [1.3521, 103.8198],
|
||||
'Mumbai': [19.0760, 72.8777], 'Delhi': [28.7041, 77.1025],
|
||||
'Bangalore': [12.9716, 77.5946], 'Seoul': [37.5665, 126.9780],
|
||||
'Hong Kong': [22.3193, 114.1694], 'Bangkok': [13.7563, 100.5018],
|
||||
'Jakarta': [6.2088, 106.8456], 'Manila': [14.5995, 120.9842],
|
||||
'Hanoi': [21.0285, 105.8542], 'Ho Chi Minh City': [10.8231, 106.6297],
|
||||
'Taipei': [25.0330, 121.5654], 'Kuala Lumpur': [3.1390, 101.6869],
|
||||
'Karachi': [24.8607, 67.0011], 'Islamabad': [33.6844, 73.0479],
|
||||
'Dhaka': [23.8103, 90.4125], 'Colombo': [6.9271, 79.8612],
|
||||
// South America
|
||||
'São Paulo': [-23.5505, -46.6333], 'Rio de Janeiro': [-22.9068, -43.1729],
|
||||
'Buenos Aires': [-34.6037, -58.3816], 'Bogotá': [4.7110, -74.0721],
|
||||
'Lima': [-12.0464, -77.0428], 'Santiago': [-33.4489, -70.6693],
|
||||
// Middle East & Africa
|
||||
'Cairo': [30.0444, 31.2357], 'Dubai': [25.2048, 55.2708],
|
||||
'Istanbul': [41.0082, 28.9784], 'Tel Aviv': [32.0853, 34.7818],
|
||||
'Johannesburg': [26.2041, 28.0473], 'Lagos': [6.5244, 3.3792],
|
||||
'Nairobi': [-1.2921, 36.8219], 'Cape Town': [-33.9249, 18.4241],
|
||||
// Australia & Oceania
|
||||
'Sydney': [-33.8688, 151.2093], 'Melbourne': [-37.8136, 144.9631],
|
||||
'Brisbane': [-27.4698, 153.0251], 'Perth': [-31.9505, 115.8605],
|
||||
'Auckland': [-36.8485, 174.7633],
|
||||
// Additional cities
|
||||
'Unknown': null
|
||||
}};
|
||||
|
||||
// Country center coordinates (fallback when city not found)
|
||||
const countryCoordinates = {{
|
||||
'US': [37.1, -95.7], 'GB': [55.4, -3.4], 'CN': [35.9, 104.1], 'RU': [61.5, 105.3],
|
||||
'JP': [36.2, 138.3], 'DE': [51.2, 10.5], 'FR': [46.6, 2.2], 'IN': [20.6, 78.96],
|
||||
@@ -1958,9 +2034,51 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
'TR': [38.9, 35.2], 'IR': [32.4, 53.7], 'AE': [23.4, 53.8], 'KZ': [48.0, 66.9],
|
||||
'UA': [48.4, 31.2], 'BG': [42.7, 25.5], 'RO': [45.9, 24.97], 'CZ': [49.8, 15.5],
|
||||
'HU': [47.2, 19.5], 'AT': [47.5, 14.6], 'BE': [50.5, 4.5], 'DK': [56.3, 9.5],
|
||||
'FI': [61.9, 25.8], 'NO': [60.5, 8.5], 'GR': [39.1, 21.8], 'PT': [39.4, -8.2]
|
||||
'FI': [61.9, 25.8], 'NO': [60.5, 8.5], 'GR': [39.1, 21.8], 'PT': [39.4, -8.2],
|
||||
'AR': [-38.4161, -63.6167], 'CO': [4.5709, -74.2973], 'CL': [-35.6751, -71.5430],
|
||||
'PE': [-9.1900, -75.0152], 'VE': [6.4238, -66.5897], 'LS': [40.0, -100.0]
|
||||
}};
|
||||
|
||||
// Helper function to get coordinates for an IP
|
||||
function getIPCoordinates(ip) {{
|
||||
// Try city first
|
||||
if (ip.city && cityCoordinates[ip.city]) {{
|
||||
return cityCoordinates[ip.city];
|
||||
}}
|
||||
// Fall back to country
|
||||
if (ip.country_code && countryCoordinates[ip.country_code]) {{
|
||||
return countryCoordinates[ip.country_code];
|
||||
}}
|
||||
return null;
|
||||
}}
|
||||
|
||||
// Track used coordinates to add small offsets for overlapping markers
|
||||
const usedCoordinates = {{}};
|
||||
function getUniqueCoordinates(baseCoords) {{
|
||||
const key = `${{baseCoords[0].toFixed(4)}},${{baseCoords[1].toFixed(4)}}`;
|
||||
if (!usedCoordinates[key]) {{
|
||||
usedCoordinates[key] = 0;
|
||||
}}
|
||||
usedCoordinates[key]++;
|
||||
|
||||
// If this is the first marker at this location, use exact coordinates
|
||||
if (usedCoordinates[key] === 1) {{
|
||||
return baseCoords;
|
||||
}}
|
||||
|
||||
// Add small random offset for subsequent markers
|
||||
// Offset increases with each marker to create a spread pattern
|
||||
const angle = (usedCoordinates[key] * 137.5) % 360; // Golden angle for even distribution
|
||||
const distance = 0.05 * Math.sqrt(usedCoordinates[key]); // Increase distance with more markers
|
||||
const latOffset = distance * Math.cos(angle * Math.PI / 180);
|
||||
const lngOffset = distance * Math.sin(angle * Math.PI / 180);
|
||||
|
||||
return [
|
||||
baseCoords[0] + latOffset,
|
||||
baseCoords[1] + lngOffset
|
||||
];
|
||||
}}
|
||||
|
||||
// Create layer groups for each category
|
||||
markerLayers = {{
|
||||
attacker: L.featureGroup(),
|
||||
@@ -1970,20 +2088,16 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
unknown: L.featureGroup()
|
||||
}};
|
||||
|
||||
circleLayers = {{
|
||||
attacker: L.featureGroup(),
|
||||
bad_crawler: L.featureGroup(),
|
||||
good_crawler: L.featureGroup(),
|
||||
regular_user: L.featureGroup(),
|
||||
unknown: L.featureGroup()
|
||||
}};
|
||||
|
||||
// Add markers for each IP
|
||||
allIps.slice(0, 100).forEach(ip => {{
|
||||
if (!ip.country_code || !ip.category) return;
|
||||
|
||||
const coords = countryCoordinates[ip.country_code];
|
||||
if (!coords) return;
|
||||
// Get coordinates (city first, then country)
|
||||
const baseCoords = getIPCoordinates(ip);
|
||||
if (!baseCoords) return;
|
||||
|
||||
// Get unique coordinates with offset to prevent overlap
|
||||
const coords = getUniqueCoordinates(baseCoords);
|
||||
|
||||
const category = ip.category.toLowerCase();
|
||||
if (!markerLayers[category]) return;
|
||||
@@ -2002,7 +2116,7 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
|
||||
const marker = L.marker(coords, {{
|
||||
icon: L.divIcon({{
|
||||
html: markerElement,
|
||||
html: markerElement.outerHTML,
|
||||
iconSize: [markerSize, markerSize],
|
||||
className: `ip-custom-marker category-${{category}}`
|
||||
}})
|
||||
@@ -2027,7 +2141,7 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
</span>
|
||||
</div>
|
||||
<span style="color: #8b949e; font-size: 12px;">
|
||||
${{ip.city || ''}}${{ip.city && ip.country_code ? ', ' : ''}}${{ip.country_code || 'Unknown'}}
|
||||
${{ip.city ? (ip.country_code ? `${{ip.city}}, ${{ip.country_code}}` : ip.city) : (ip.country_code || 'Unknown')}}
|
||||
</span><br/>
|
||||
<div style="margin-top: 8px; border-top: 1px solid #30363d; padding-top: 8px;">
|
||||
<div><span style="color: #8b949e;">Requests:</span> <span style="color: ${{categoryColor}}; font-weight: bold;">${{ip.total_requests}}</span></div>
|
||||
@@ -2041,41 +2155,7 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
markerLayers[category].addLayer(marker);
|
||||
}});
|
||||
|
||||
// Add cluster circles for each category
|
||||
const categoryCountryCounts = {{}};
|
||||
|
||||
allIps.forEach(ip => {{
|
||||
if (ip.country_code && ip.category) {{
|
||||
const category = ip.category.toLowerCase();
|
||||
if (!categoryCountryCounts[category]) {{
|
||||
categoryCountryCounts[category] = {{}};
|
||||
}}
|
||||
categoryCountryCounts[category][ip.country_code] =
|
||||
(categoryCountryCounts[category][ip.country_code] || 0) + 1;
|
||||
}}
|
||||
}});
|
||||
|
||||
Object.entries(categoryCountryCounts).forEach(([category, countryCounts]) => {{
|
||||
Object.entries(countryCounts).forEach(([country, count]) => {{
|
||||
const coords = countryCoordinates[country];
|
||||
if (coords && circleLayers[category]) {{
|
||||
const color = categoryColors[category] || '#8b949e';
|
||||
const circle = L.circle(coords, {{
|
||||
radius: 100000 + (count * 150000),
|
||||
color: color,
|
||||
fillColor: color,
|
||||
fillOpacity: 0.15,
|
||||
weight: 1,
|
||||
opacity: 0.4,
|
||||
dashArray: '3'
|
||||
}});
|
||||
circleLayers[category].addLayer(circle);
|
||||
}}
|
||||
}});
|
||||
}});
|
||||
|
||||
// Add all layers to map initially
|
||||
Object.values(circleLayers).forEach(layer => attackerMap.addLayer(layer));
|
||||
// Add all marker layers to map initially
|
||||
Object.values(markerLayers).forEach(layer => attackerMap.addLayer(layer));
|
||||
|
||||
// Fit map to all markers
|
||||
@@ -2120,18 +2200,6 @@ def generate_dashboard(stats: dict, dashboard_path: str = "") -> str:
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
|
||||
if (circleLayers[category]) {{
|
||||
if (show) {{
|
||||
if (!attackerMap.hasLayer(circleLayers[category])) {{
|
||||
attackerMap.addLayer(circleLayers[category]);
|
||||
}}
|
||||
}} else {{
|
||||
if (attackerMap.hasLayer(circleLayers[category])) {{
|
||||
attackerMap.removeLayer(circleLayers[category]);
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
}});
|
||||
}}
|
||||
|
||||
|
||||
@@ -2,8 +2,21 @@
|
||||
|
||||
"""
|
||||
Test script to insert fake external IPs into the database for testing the dashboard.
|
||||
This generates realistic-looking test data including access logs, credential attempts, and attack detections.
|
||||
Also triggers category behavior changes to demonstrate the timeline feature.
|
||||
This generates realistic-looking test data including:
|
||||
- Access logs with various suspicious activities
|
||||
- Credential attempts
|
||||
- Attack detections (SQL injection, XSS, etc.)
|
||||
- Category behavior changes for timeline demonstration
|
||||
- Real good crawler IPs (Googlebot, Bingbot, etc.) with API-fetched geolocation
|
||||
|
||||
Usage:
|
||||
python test_insert_fake_ips.py [num_ips] [logs_per_ip] [credentials_per_ip] [--no-cleanup]
|
||||
|
||||
Examples:
|
||||
python test_insert_fake_ips.py # Generate 20 IPs with defaults, cleanup DB first
|
||||
python test_insert_fake_ips.py 30 # Generate 30 IPs with defaults
|
||||
python test_insert_fake_ips.py 30 20 5 # Generate 30 IPs, 20 logs each, 5 credentials each
|
||||
python test_insert_fake_ips.py --no-cleanup # Generate data without cleaning DB first
|
||||
"""
|
||||
|
||||
import random
|
||||
@@ -12,6 +25,7 @@ import sys
|
||||
from datetime import datetime, timedelta
|
||||
from zoneinfo import ZoneInfo
|
||||
from pathlib import Path
|
||||
import requests
|
||||
|
||||
# Add parent src directory to path so we can import database and logger
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
|
||||
@@ -23,14 +37,81 @@ from logger import get_app_logger
|
||||
# TEST DATA GENERATORS
|
||||
# ----------------------
|
||||
|
||||
FAKE_IPS = [
|
||||
"203.0.113.45", # Regular attacker IP
|
||||
"198.51.100.89", # Credential harvester IP
|
||||
"192.0.2.120", # Bot IP
|
||||
"205.32.180.65", # Another attacker
|
||||
"210.45.67.89", # Suspicious IP
|
||||
"175.23.45.67", # International IP
|
||||
"182.91.102.45", # Another suspicious IP
|
||||
# Fake IPs with geolocation data (country_code, city, ASN org)
|
||||
# These will appear on the map based on their country_code
|
||||
FAKE_IPS_WITH_GEO = [
|
||||
# United States
|
||||
("45.142.120.10", "US", "New York", "AS14061 DigitalOcean"),
|
||||
("107.189.10.143", "US", "Los Angeles", "AS20473 Vultr"),
|
||||
("162.243.175.23", "US", "San Francisco", "AS14061 DigitalOcean"),
|
||||
("198.51.100.89", "US", "Chicago", "AS16509 Amazon"),
|
||||
|
||||
# Europe
|
||||
("185.220.101.45", "DE", "Berlin", "AS24940 Hetzner"),
|
||||
("195.154.133.20", "FR", "Paris", "AS12876 Scaleway"),
|
||||
("178.128.83.165", "GB", "London", "AS14061 DigitalOcean"),
|
||||
("87.251.67.90", "NL", "Amsterdam", "AS49453 GlobalConnect"),
|
||||
("91.203.5.165", "RU", "Moscow", "AS51115 HLL LLC"),
|
||||
("46.105.57.169", "FR", "Roubaix", "AS16276 OVH"),
|
||||
("217.182.143.207", "RU", "Saint Petersburg", "AS51570 JSC ER-Telecom"),
|
||||
("188.166.123.45", "GB", "Manchester", "AS14061 DigitalOcean"),
|
||||
|
||||
# Asia
|
||||
("103.253.145.36", "CN", "Beijing", "AS4134 Chinanet"),
|
||||
("42.112.28.216", "CN", "Shanghai", "AS4134 Chinanet"),
|
||||
("118.163.74.160", "JP", "Tokyo", "AS2516 KDDI"),
|
||||
("43.229.53.35", "SG", "Singapore", "AS23969 TOT"),
|
||||
("115.78.208.140", "IN", "Mumbai", "AS9829 BSNL"),
|
||||
("14.139.56.18", "IN", "Bangalore", "AS4755 TATA"),
|
||||
("61.19.25.207", "TW", "Taipei", "AS3462 HiNet"),
|
||||
("121.126.219.198", "KR", "Seoul", "AS4766 Korea Telecom"),
|
||||
("202.134.4.212", "ID", "Jakarta", "AS7597 TELKOMNET"),
|
||||
("171.244.140.134", "VN", "Hanoi", "AS7552 Viettel"),
|
||||
|
||||
# South America
|
||||
("177.87.169.20", "BR", "São Paulo", "AS28573 Claro"),
|
||||
("200.21.19.58", "BR", "Rio de Janeiro", "AS7738 Telemar"),
|
||||
("181.13.140.98", "AR", "Buenos Aires", "AS7303 Telecom Argentina"),
|
||||
("190.150.24.34", "CO", "Bogotá", "AS3816 Colombia Telecomunicaciones"),
|
||||
|
||||
# Middle East & Africa
|
||||
("41.223.53.141", "EG", "Cairo", "AS8452 TE-Data"),
|
||||
("196.207.35.152", "ZA", "Johannesburg", "AS37271 Workonline"),
|
||||
("5.188.62.214", "TR", "Istanbul", "AS51115 HLL LLC"),
|
||||
("37.48.93.125", "AE", "Dubai", "AS5384 Emirates Telecom"),
|
||||
("102.66.137.29", "NG", "Lagos", "AS29465 MTN Nigeria"),
|
||||
|
||||
# Australia & Oceania
|
||||
("103.28.248.110", "AU", "Sydney", "AS4739 Internode"),
|
||||
("202.168.45.33", "AU", "Melbourne", "AS1221 Telstra"),
|
||||
|
||||
# Additional European IPs
|
||||
("94.102.49.190", "PL", "Warsaw", "AS12912 T-Mobile"),
|
||||
("213.32.93.140", "ES", "Madrid", "AS3352 Telefónica"),
|
||||
("79.137.79.167", "IT", "Rome", "AS3269 Telecom Italia"),
|
||||
("37.9.169.146", "SE", "Stockholm", "AS3301 Telia"),
|
||||
("188.92.80.123", "RO", "Bucharest", "AS8708 RCS & RDS"),
|
||||
("80.240.25.198", "CZ", "Prague", "AS6830 UPC"),
|
||||
]
|
||||
|
||||
# Extract just IPs for backward compatibility
|
||||
FAKE_IPS = [ip_data[0] for ip_data in FAKE_IPS_WITH_GEO]
|
||||
|
||||
# Create geo data dictionary
|
||||
FAKE_GEO_DATA = {
|
||||
ip_data[0]: (ip_data[1], ip_data[2], ip_data[3])
|
||||
for ip_data in FAKE_IPS_WITH_GEO
|
||||
}
|
||||
|
||||
# Real good crawler IPs (Googlebot, Bingbot, etc.) - geolocation will be fetched from API
|
||||
GOOD_CRAWLER_IPS = [
|
||||
"66.249.66.1", # Googlebot
|
||||
"66.249.79.23", # Googlebot
|
||||
"40.77.167.52", # Bingbot
|
||||
"157.55.39.145", # Bingbot
|
||||
"17.58.98.100", # Applebot
|
||||
"199.59.150.39", # Twitterbot
|
||||
"54.236.1.15", # Amazon Bot
|
||||
]
|
||||
|
||||
FAKE_PATHS = [
|
||||
@@ -79,11 +160,11 @@ ATTACK_TYPES = [
|
||||
]
|
||||
|
||||
CATEGORIES = [
|
||||
"ATTACKER",
|
||||
"BAD_CRAWLER",
|
||||
"GOOD_CRAWLER",
|
||||
"REGULAR_USER",
|
||||
"UNKNOWN",
|
||||
"attacker",
|
||||
"bad_crawler",
|
||||
"good_crawler",
|
||||
"regular_user",
|
||||
"unknown",
|
||||
]
|
||||
|
||||
|
||||
@@ -109,14 +190,92 @@ def generate_analyzed_metrics():
|
||||
}
|
||||
|
||||
|
||||
def generate_fake_data(num_ips: int = 45, logs_per_ip: int = 15, credentials_per_ip: int = 3):
|
||||
def cleanup_database(db_manager, app_logger):
|
||||
"""
|
||||
Clean up all existing test data from the database.
|
||||
|
||||
Args:
|
||||
db_manager: Database manager instance
|
||||
app_logger: Logger instance
|
||||
"""
|
||||
from models import AccessLog, CredentialAttempt, AttackDetection, IpStats, CategoryHistory
|
||||
|
||||
app_logger.info("=" * 60)
|
||||
app_logger.info("Cleaning up existing database data")
|
||||
app_logger.info("=" * 60)
|
||||
|
||||
session = db_manager.session
|
||||
try:
|
||||
# Delete all records from each table
|
||||
deleted_attack_detections = session.query(AttackDetection).delete()
|
||||
deleted_access_logs = session.query(AccessLog).delete()
|
||||
deleted_credentials = session.query(CredentialAttempt).delete()
|
||||
deleted_category_history = session.query(CategoryHistory).delete()
|
||||
deleted_ip_stats = session.query(IpStats).delete()
|
||||
|
||||
session.commit()
|
||||
|
||||
app_logger.info(f"Deleted {deleted_access_logs} access logs")
|
||||
app_logger.info(f"Deleted {deleted_attack_detections} attack detections")
|
||||
app_logger.info(f"Deleted {deleted_credentials} credential attempts")
|
||||
app_logger.info(f"Deleted {deleted_category_history} category history records")
|
||||
app_logger.info(f"Deleted {deleted_ip_stats} IP statistics")
|
||||
app_logger.info("✓ Database cleanup complete")
|
||||
except Exception as e:
|
||||
session.rollback()
|
||||
app_logger.error(f"Error during database cleanup: {e}")
|
||||
raise
|
||||
finally:
|
||||
db_manager.close_session()
|
||||
|
||||
|
||||
def fetch_geolocation_from_api(ip: str, app_logger) -> tuple:
|
||||
"""
|
||||
Fetch geolocation data from the IP reputation API.
|
||||
|
||||
Args:
|
||||
ip: IP address to lookup
|
||||
app_logger: Logger instance
|
||||
|
||||
Returns:
|
||||
Tuple of (country_code, city, asn, asn_org) or None if failed
|
||||
"""
|
||||
try:
|
||||
api_url = "https://iprep.lcrawl.com/api/iprep/"
|
||||
params = {"cidr": ip}
|
||||
headers = {"Content-Type": "application/json"}
|
||||
response = requests.get(api_url, headers=headers, params=params, timeout=10)
|
||||
|
||||
if response.status_code == 200:
|
||||
payload = response.json()
|
||||
if payload.get("results"):
|
||||
data = payload["results"][0]
|
||||
geoip_data = data.get("geoip_data", {})
|
||||
|
||||
country_code = geoip_data.get("country_iso_code", "Unknown")
|
||||
city = geoip_data.get("city_name", "Unknown")
|
||||
asn = geoip_data.get("asn_autonomous_system_number")
|
||||
asn_org = geoip_data.get("asn_autonomous_system_organization", "Unknown")
|
||||
|
||||
return (country_code, city, asn, asn_org)
|
||||
except requests.RequestException as e:
|
||||
app_logger.warning(f"Failed to fetch geolocation for {ip}: {e}")
|
||||
except Exception as e:
|
||||
app_logger.error(f"Error processing geolocation for {ip}: {e}")
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def generate_fake_data(num_ips: int = 20, logs_per_ip: int = 15, credentials_per_ip: int = 3, include_good_crawlers: bool = True, cleanup: bool = True):
|
||||
"""
|
||||
Generate and insert fake test data into the database.
|
||||
|
||||
Args:
|
||||
num_ips: Number of unique fake IPs to generate (default: 5)
|
||||
num_ips: Number of unique fake IPs to generate (default: 20)
|
||||
logs_per_ip: Number of access logs per IP (default: 15)
|
||||
credentials_per_ip: Number of credential attempts per IP (default: 3)
|
||||
include_good_crawlers: Whether to add real good crawler IPs with API-fetched geolocation (default: True)
|
||||
cleanup: Whether to clean up existing database data before generating new data (default: True)
|
||||
"""
|
||||
db_manager = get_database()
|
||||
app_logger = get_app_logger()
|
||||
@@ -125,6 +284,11 @@ def generate_fake_data(num_ips: int = 45, logs_per_ip: int = 15, credentials_per
|
||||
if not db_manager._initialized:
|
||||
db_manager.initialize()
|
||||
|
||||
# Clean up existing data if requested
|
||||
if cleanup:
|
||||
cleanup_database(db_manager, app_logger)
|
||||
print() # Add blank line for readability
|
||||
|
||||
app_logger.info("=" * 60)
|
||||
app_logger.info("Starting fake IP data generation for testing")
|
||||
app_logger.info("=" * 60)
|
||||
@@ -186,6 +350,28 @@ def generate_fake_data(num_ips: int = 45, logs_per_ip: int = 15, credentials_per
|
||||
app_logger.info(f" ✓ Generated {logs_per_ip} access logs")
|
||||
app_logger.info(f" ✓ Generated {credentials_per_ip} credential attempts")
|
||||
|
||||
# Add geolocation data if available for this IP
|
||||
if ip in FAKE_GEO_DATA:
|
||||
country_code, city, asn_org = FAKE_GEO_DATA[ip]
|
||||
# Extract ASN number from ASN string (e.g., "AS12345 Name" -> 12345)
|
||||
asn_number = None
|
||||
if asn_org and asn_org.startswith("AS"):
|
||||
try:
|
||||
asn_number = int(asn_org.split()[0][2:]) # Remove "AS" prefix and get number
|
||||
except (ValueError, IndexError):
|
||||
asn_number = 12345 # Fallback
|
||||
|
||||
# Update IP reputation info including geolocation and city
|
||||
db_manager.update_ip_rep_infos(
|
||||
ip=ip,
|
||||
country_code=country_code,
|
||||
asn=asn_number or 12345,
|
||||
asn_org=asn_org,
|
||||
list_on={},
|
||||
city=city # Now passing city to the function
|
||||
)
|
||||
app_logger.info(f" 📍 Added geolocation: {city}, {country_code} ({asn_org})")
|
||||
|
||||
# Trigger behavior/category changes to demonstrate timeline feature
|
||||
# First analysis
|
||||
initial_category = random.choice(CATEGORIES)
|
||||
@@ -232,11 +418,79 @@ def generate_fake_data(num_ips: int = 45, logs_per_ip: int = 15, credentials_per
|
||||
)
|
||||
total_category_changes += 1
|
||||
|
||||
# Add good crawler IPs with real geolocation from API
|
||||
total_good_crawlers = 0
|
||||
if include_good_crawlers:
|
||||
app_logger.info("\n" + "=" * 60)
|
||||
app_logger.info("Adding Good Crawler IPs with API-fetched geolocation")
|
||||
app_logger.info("=" * 60)
|
||||
|
||||
for crawler_ip in GOOD_CRAWLER_IPS:
|
||||
app_logger.info(f"\nProcessing Good Crawler: {crawler_ip}")
|
||||
|
||||
# Fetch real geolocation from API
|
||||
geo_data = fetch_geolocation_from_api(crawler_ip, app_logger)
|
||||
|
||||
# Don't generate access logs for good crawlers to prevent re-categorization
|
||||
# We'll just create the IP stats entry with the category set
|
||||
app_logger.info(f" ✓ Adding as good crawler (no logs to prevent re-categorization)")
|
||||
|
||||
# First, we need to create the IP in the database via persist_access
|
||||
# (but we'll only create one minimal log entry)
|
||||
db_manager.persist_access(
|
||||
ip=crawler_ip,
|
||||
path="/robots.txt", # Minimal, normal crawler behavior
|
||||
user_agent="Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)",
|
||||
method="GET",
|
||||
is_suspicious=False,
|
||||
is_honeypot_trigger=False,
|
||||
attack_types=None,
|
||||
)
|
||||
|
||||
# Add geolocation if API fetch was successful
|
||||
if geo_data:
|
||||
country_code, city, asn, asn_org = geo_data
|
||||
db_manager.update_ip_rep_infos(
|
||||
ip=crawler_ip,
|
||||
country_code=country_code,
|
||||
asn=asn if asn else 12345,
|
||||
asn_org=asn_org,
|
||||
list_on={},
|
||||
city=city
|
||||
)
|
||||
app_logger.info(f" 📍 API-fetched geolocation: {city}, {country_code} ({asn_org})")
|
||||
else:
|
||||
app_logger.warning(f" ⚠ Could not fetch geolocation for {crawler_ip}")
|
||||
|
||||
# Set category to good_crawler - this sets manual_category=True to prevent re-analysis
|
||||
db_manager.update_ip_stats_analysis(
|
||||
ip=crawler_ip,
|
||||
analyzed_metrics={
|
||||
"request_frequency": 0.1, # Very low frequency
|
||||
"suspicious_patterns": 0,
|
||||
"credential_attempts": 0,
|
||||
"attack_diversity": 0.0,
|
||||
},
|
||||
category="good_crawler",
|
||||
category_scores={
|
||||
"attacker": 0,
|
||||
"good_crawler": 100,
|
||||
"bad_crawler": 0,
|
||||
"regular_user": 0,
|
||||
"unknown": 0,
|
||||
},
|
||||
last_analysis=datetime.now(tz=ZoneInfo('UTC'))
|
||||
)
|
||||
total_good_crawlers += 1
|
||||
time.sleep(0.5) # Small delay between API calls
|
||||
|
||||
# Print summary
|
||||
app_logger.info("\n" + "=" * 60)
|
||||
app_logger.info("Test Data Generation Complete!")
|
||||
app_logger.info("=" * 60)
|
||||
app_logger.info(f"Total IPs created: {len(selected_ips)}")
|
||||
app_logger.info(f"Total IPs created: {len(selected_ips) + total_good_crawlers}")
|
||||
app_logger.info(f" - Attackers/Mixed: {len(selected_ips)}")
|
||||
app_logger.info(f" - Good Crawlers: {total_good_crawlers}")
|
||||
app_logger.info(f"Total access logs: {total_logs}")
|
||||
app_logger.info(f"Total attack detections: {total_attacks}")
|
||||
app_logger.info(f"Total credential attempts: {total_credentials}")
|
||||
@@ -244,6 +498,7 @@ def generate_fake_data(num_ips: int = 45, logs_per_ip: int = 15, credentials_per
|
||||
app_logger.info("=" * 60)
|
||||
app_logger.info("\nYou can now view the dashboard with this test data.")
|
||||
app_logger.info("The 'Behavior Timeline' will show category transitions for each IP.")
|
||||
app_logger.info("The map will show good crawlers with real geolocation from API.")
|
||||
app_logger.info("Run: python server.py")
|
||||
app_logger.info("=" * 60)
|
||||
|
||||
@@ -252,8 +507,10 @@ if __name__ == "__main__":
|
||||
import sys
|
||||
|
||||
# Allow command-line arguments for customization
|
||||
num_ips = int(sys.argv[1]) if len(sys.argv) > 1 else 5
|
||||
num_ips = int(sys.argv[1]) if len(sys.argv) > 1 else 20
|
||||
logs_per_ip = int(sys.argv[2]) if len(sys.argv) > 2 else 15
|
||||
credentials_per_ip = int(sys.argv[3]) if len(sys.argv) > 3 else 3
|
||||
# Add --no-cleanup flag to skip database cleanup
|
||||
cleanup = "--no-cleanup" not in sys.argv
|
||||
|
||||
generate_fake_data(num_ips, logs_per_ip, credentials_per_ip)
|
||||
generate_fake_data(num_ips, logs_per_ip, credentials_per_ip, include_good_crawlers=True, cleanup=cleanup)
|
||||
|
||||
Reference in New Issue
Block a user