spamhaus_drop analyzer, closes #2408

api_app/analyzers_manager/migrations/0107_analyzer_config_spamhaus_drop.py

@@ -0,0 +1,126 @@
+from django.db import migrations
+from django.db.models.fields.related_descriptors import (
+    ForwardManyToOneDescriptor,
+    ForwardOneToOneDescriptor,
+    ManyToManyDescriptor,
+)
+
+plugin = {
+    "python_module": {
+        "health_check_schedule": None,
+        "update_schedule": {
+            "minute": "0",
+            "hour": "0",
+            "day_of_week": "*",
+            "day_of_month": "*",
+            "month_of_year": "*",
+        },
+        "module": "spamhaus_drop.SpamhausDropV4",
+        "base_path": "api_app.analyzers_manager.observable_analyzers",
+    },
+    "name": "Spamhaus_DROP",
+    "description": "[Spamhaus_DROP](https://www.spamhaus.org/blocklists/do-not-route-or-peer/) protects from activity directly originating from rogue networks, such as spam campaigns, encryption via ransomware, DNS-hijacking and exploit attempts, authentication attacks to discover working access credentials, harvesting, DDoS attacks.",
+    "disabled": False,
+    "soft_time_limit": 10,
+    "routing_key": "default",
+    "health_check_status": True,
+    "type": "observable",
+    "docker_based": False,
+    "maximum_tlp": "AMBER",
+    "observable_supported": ["ip"],
+    "supported_filetypes": [],
+    "run_hash": False,
+    "run_hash_type": "",
+    "not_supported_filetypes": [],
+    "model": "analyzers_manager.AnalyzerConfig",
+}
+
+params = []
+
+values = []
+
+
+def _get_real_obj(Model, field, value):
+    def _get_obj(Model, other_model, value):
+        if isinstance(value, dict):
+            real_vals = {}
+            for key, real_val in value.items():
+                real_vals[key] = _get_real_obj(other_model, key, real_val)
+            value = other_model.objects.get_or_create(**real_vals)[0]
+        # it is just the primary key serialized
+        else:
+            if isinstance(value, int):
+                if Model.__name__ == "PluginConfig":
+                    value = other_model.objects.get(name=plugin["name"])
+                else:
+                    value = other_model.objects.get(pk=value)
+            else:
+                value = other_model.objects.get(name=value)
+        return value
+
+    if (
+        type(getattr(Model, field))
+        in [ForwardManyToOneDescriptor, ForwardOneToOneDescriptor]
+        and value
+    ):
+        other_model = getattr(Model, field).get_queryset().model
+        value = _get_obj(Model, other_model, value)
+    elif type(getattr(Model, field)) in [ManyToManyDescriptor] and value:
+        other_model = getattr(Model, field).rel.model
+        value = [_get_obj(Model, other_model, val) for val in value]
+    return value
+
+
+def _create_object(Model, data):
+    mtm, no_mtm = {}, {}
+    for field, value in data.items():
+        value = _get_real_obj(Model, field, value)
+        if type(getattr(Model, field)) is ManyToManyDescriptor:
+            mtm[field] = value
+        else:
+            no_mtm[field] = value
+    try:
+        o = Model.objects.get(**no_mtm)
+    except Model.DoesNotExist:
+        o = Model(**no_mtm)
+        o.full_clean()
+        o.save()
+        for field, value in mtm.items():
+            attribute = getattr(o, field)
+            if value is not None:
+                attribute.set(value)
+        return False
+    return True
+
+
+def migrate(apps, schema_editor):
+    Parameter = apps.get_model("api_app", "Parameter")
+    PluginConfig = apps.get_model("api_app", "PluginConfig")
+    python_path = plugin.pop("model")
+    Model = apps.get_model(*python_path.split("."))
+    if not Model.objects.filter(name=plugin["name"]).exists():
+        exists = _create_object(Model, plugin)
+        if not exists:
+            for param in params:
+                _create_object(Parameter, param)
+            for value in values:
+                _create_object(PluginConfig, value)
+
+
+def reverse_migrate(apps, schema_editor):
+    python_path = plugin.pop("model")
+    Model = apps.get_model(*python_path.split("."))
+    Model.objects.get(name=plugin["name"]).delete()
+
+
+class Migration(migrations.Migration):
+    atomic = False
+    dependencies = [
+        ("api_app", "0062_alter_parameter_python_module"),
+        (
+            "analyzers_manager",
+            "0106_analyzer_config_leakix",
+        ),
+    ]
+
+    operations = [migrations.RunPython(migrate, reverse_migrate)]

api_app/analyzers_manager/observable_analyzers/spamhaus_drop.py

@@ -0,0 +1,100 @@
+import bisect
+import ipaddress
+import json
+import logging
+import os
+
+import requests
+from django.conf import settings
+
+from api_app.analyzers_manager import classes
+from api_app.analyzers_manager.exceptions import AnalyzerRunException
+from tests.mock_utils import MockUpResponse, if_mock_connections, patch
+
+logger = logging.getLogger(__name__)
+
+
+class SpamhausDropV4(classes.ObservableAnalyzer):
+    url = "https://www.spamhaus.org/drop/drop_v4.json"
+
+    @classmethod
+    def location(cls) -> str:
+        db_name = "drop_v4.json"
+        return f"{settings.MEDIA_ROOT}/{db_name}"
+
+    def run(self):
+        ip = ipaddress.ip_address(self.observable_name)
+        database_location = self.location()
+        if not os.path.exists(database_location):
+            logger.info(
+                f"Database does not exist in {database_location}, initialising..."
+            )
+            self.update()
+        with open(database_location, "r") as f:
+            db = json.load(f)
+
+        insertion = bisect.bisect_left(
+            db, ip, key=lambda x: ipaddress.ip_network(x["cidr"]).network_address
+        )
+        matches = []
+        # Check entries at and after the insertion point
+        # there maybe one or more subnets contained in the ip
+        for i in range(insertion, len(db)):
+            network = ipaddress.ip_network(db[i]["cidr"])
+            if ip in network:
+                matches.append(db[i])
+            elif network.network_address > ip:
+                break
+        if matches:
+            return {"found": True, "details": matches}
+
+        return {"found": False}
+
+    @classmethod
+    def update(cls):
+        logger.info(f"Updating database from {cls.url}")
+        response = requests.get(url=cls.url)
+        response.raise_for_status()
+        data = cls.convert_to_json(response.text)
+        database_location = cls.location()
+
+        with open(database_location, "w", encoding="utf-8") as f:
+            json.dump(data, f)
+        logger.info(f"Database updated at {database_location}")
+
+    @staticmethod
+    def convert_to_json(input_string) -> dict:
+        lines = input_string.strip().split("\n")
+        json_objects = []
+        for line in lines:
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                json_obj = json.loads(line)
+                json_objects.append(json_obj)
+            except json.JSONDecodeError:
+                raise AnalyzerRunException(
+                    "Invalid JSON format in the response while updating the database"
+                )
+
+        return json_objects
+
+    @classmethod
+    def _monkeypatch(cls):
+        mock_data = (
+            '{"cidr": "1.10.16.0/20", "sblid": "SBL256894", "rir": "apnic"}\n'
+            '{"cidr": "2.56.192.0/22", "sblid": "SBL459831", "rir": "ripencc"}'
+        )
+        patches = [
+            if_mock_connections(
+                patch(
+                    "requests.get",
+                    return_value=MockUpResponse(
+                        mock_data,
+                        200,
+                    ),
+                ),
+            )
+        ]
+        return super()._monkeypatch(patches=patches)

docs/source/Usage.md

@@ -264,9 +264,10 @@ The following is the list of the available analyzers you can run out-of-the-box.
 * `OrklSearch`:[Orkl](https://orkl.eu/) is the Community Driven Cyber Threat Intelligence Library.
 * `Crt_sh`:[Crt_Sh](https://crt.sh/) lets you get certificates info about a domain.
 * `Spamhaus_WQS`:[Spamhaus_WQS](https://docs.spamhaus.com/datasets/docs/source/70-access-methods/web-query-service/000-intro.html) The Spamhaus Web Query Service (WQS) is a method of accessing Spamhaus block lists using the HTTPS protocol. 
-* `Adguard`: [Adguard](https://github.com/AdguardTeam/AdguardSDNSFilter), a filter composed of several other filters (AdGuard Base filter, Social media filter, Tracking Protection filter, Mobile Ads filter, EasyList and EasyPrivacy) and simplified specifically to be better compatible with DNS-level ad blocking.* `Adguard`: [Adguard](https://github.com/AdguardTeam/AdguardSDNSFilter), a filter composed of several other filters (AdGuard Base filter, Social media filter, Tracking Protection filter, Mobile Ads filter, EasyList and EasyPrivacy) and simplified specifically to be better compatible with DNS-level ad blocking.
+* `Adguard`:[Adguard](https://github.com/AdguardTeam/AdguardSDNSFilter), a filter composed of several other filters (AdGuard Base filter, Social media filter, Tracking Protection filter, Mobile Ads filter, EasyList and EasyPrivacy) and simplified specifically to be better compatible with DNS-level ad blocking.
+* `Adguard`: [Adguard](https://github.com/AdguardTeam/AdguardSDNSFilter), a filter composed of several other filters (AdGuard Base filter, Social media filter, Tracking Protection filter, Mobile Ads filter, EasyList and EasyPrivacy) and simplified specifically to be better compatible with DNS-level ad blocking.
 * `JA4_DB`:[JA4_DB](https://ja4db.com/) lets you search a fingerprint in JA4 databse.
-* `LeakIX`:[LeakIX](https://leakix.net/) is a red-team search engine indexing mis-configurations and vulnerabilities online.
+* `LeakIX`:[LeakIX](https://leakix.net/) is a red-team search engine indexing mis-configurations and vulnerabilities online.* `Spamhaus_DROP`:[Spamhaus_DROP](https://www.spamhaus.org/blocklists/do-not-route-or-peer/) protects from activity directly originating from rogue networks, such as spam campaigns, encryption via ransomware, DNS-hijacking and exploit attempts, authentication attacks to discover working access credentials, harvesting, DDoS attacks.
 
 ##### Generic analyzers (email, phone number, etc.; anything really)