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# AIL objects
AIL is using different types of objects to classify, correlate and describe extracted information:
- **Cryptocurrency**: Represents extracted cryptocurrency addresses.
- bitcoin
- bitcoin-cash
- dash
- ethereum
- litecoin
- monero
- zcash
- **Cve**: Represents extracted CVE (Common Vulnerabilities and Exposures) IDs.
- **Decoded**: Represents information that has been decoded from an encoded format, such as base64.
- **Domain**: Represents crawled domains and includes metadata related to them.
- **Item**: Represents a piece of text that has been processed by AIL. It can include various types of extracted information.
- **Pgp**: Represents PGP key/block metadata.
- key: PGP key IDs
- mail: email addresses associated with PGP keys
- name: names associated with PGP keys.
- **Screenshot**: Represents screenshots captured from crawled domains.
- **Title**: Represents the HTML title extracted from web pages.
- **Username**:
- telegram: telegram username handles
- twitter: twitter username handles
- jabber: Jabber (XMPP) username handles
# AIL Importers
AIL Importers play a crucial role in the AIL ecosystem,
enabling the import of various types of data into the framework.
These importers are located in the `/bin/importer` directory.
The modular design of importers allows for easy expansion and customization,
ensuring that AIL can adapt to new types of data.
Available Importers:
- [AIL Feeders](#ail-feeders): Extract and feed JSON data from external sources via The API.
- ZMQ
- [pystemon](https://github.com/cvandeplas/pystemon)
- File: Import files and directories.
(Manually Feed File/Dir: [./tool/file_dir_importer.py](./tool/file_dir_importer.py)).
[//]: # (### ZMQ Importer:)
### pystemon:
1. Clone the [pystemon's git repository](https://github.com/cvandeplas/pystemon):
```
git clone https://github.com/cvandeplas/pystemon.git
```
2. Edit configuration file for pystemon ```pystemon/pystemon.yaml```:
- Configure the storage section according to your needs:
```
storage:
archive:
storage-classname: FileStorage
save: yes
save-all: yes
dir: "alerts"
dir-all: "archive"
compress: yes
redis:
storage-classname: RedisStorage
save: yes
save-all: yes
server: "localhost"
port: 6379
database: 10
lookup: no
```
- Adjust the configuration for paste-sites based on your requirements (remember to throttle download and update times).
3. Install python dependencies inside the virtual environment:
```shell
cd ail-framework/
. ./AILENV/bin/activate
cd pystemon/
pip install -U -r requirements.txt
```
4. Edit the configuration file ```ail-framework/configs/core.cfg```:
- Modify the "pystemonpath" path accordingly.
5. Launch ail-framework, pystemon and PystemonImporter.py (all within the virtual environment):
- Option 1 (recommended):
```
./ail-framework/bin/LAUNCH.sh -l #starts ail-framework
./ail-framework/bin/LAUNCH.sh -f #starts pystemon and the PystemonImporter.py
```
- Option 2 (may require two terminal windows):
```
./ail-framework/bin/LAUNCH.sh -l #starts ail-framework
./pystemon/pystemon.py
./ail-framework/bin/importer/PystemonImporter.py
```
### File Importer `importer/FileImporter.py`:
Manually import File and Directory with the [./tool/file_dir_importer.py](./tool/file_dir_importer.py) script:
- Import Files:
```shell
. ./AILENV/bin/activate
cd tools/
./file_dir_importer.py -f MY_FILE_PAT
```
- Import Dirs:
```shell
. ./AILENV/bin/activate
cd tools/
./file_dir_importer.py -d MY_DIR_PATH
```
### Create a New Importer:
```python
from importer.abstract_importer import AbstractImporter
from modules.abstract_module import AbstractModule
class MyNewImporter(AbstractImporter):
def __init__(self):
super().__init__()
# super().__init__(queue=True) # if it's an one-time run importer
self.logger.info(f'Importer {self.name} initialized')
def importer(self, my_var):
# Process my_var and get content to import
content = GET_MY_CONTENT_TO_IMPORT
# if content is not gzipped and/or not b64 encoded,
# set gzipped and/or b64 to False
message = self.create_message(item_id, content, b64=False, gzipped=False)
return message
# if it's an one-time run, otherwise create an AIL Module
# self.add_message_to_queue(message)
class MyNewModuleImporter(AbstractModule):
def __init__(self):
super().__init__()
# init module ...
self.importer = MyNewImporter()
def get_message(self):
return self.importer.importer()
def compute(self, message):
self.add_message_to_queue(message)
if __name__ == '__main__':
module = MyNewModuleImporter()
module.run()
# if it's an one-time run:
# importer = MyImporter()
# importer.importer(my_var)
```
## AIL Feeders
AIL Feeders are a special type of Importer within AIL, specifically designed
to *extract* and *feed* data from external sources into the framework.
- **Extract Data**: AIL Feeders extract data from external sources, such as APK files,
certificate transparency logs, GitHub archives, repositories, ActivityPub sources,
leaked files, Atom/RSS feeds, JSON logs, Discord, and Telegram, ...
- **Run Independently**: Feeders can run on separate systems or infrastructure,
providing flexibility and scalability. They operate independently from the core AIL framework.
- **Internal Logic**: Each feeder can implement its own custom logic and processing
to extract and transform data and metadata from the source into JSON.
- **Push to AIL API**: The generated JSON is then pushed to the AIL API
for ingestion and further analysis within the AIL framework.
[//]: # (- Customize medata parsing)
### AIL Feeders List:
- [ail-feeder-apk](https://github.com/ail-project/ail-feeder-apk): Pushes annotated APK to an AIL instance for yara detection.
- [ail-feeder-ct](https://github.com/ail-project/ail-feeder-ct): AIL feeder for certificate transparency.
- [ail-feeder-github-gharchive](https://github.com/ail-project/ail-feeder-gharchive): extract informations
from GHArchive, collect and feed AIL
- [ail-feeder-github-repo](https://github.com/ail-project/ail-feeder-github-repo): Pushes github repositories to AIL.
- [ail-feeder-activity-pub](https://github.com/ail-project/ail-feeder-activity-pub) ActivityPub feeder.
- [ail-feeder-leak](https://github.com/ail-project/ail-feeder-leak): Automates the process of feeding files to AIL, using data chunking to handle large files.
- [ail-feeder-atom-rss](https://github.com/ail-project/ail-feeder-atom-rss) Atom and RSS feeder for AIL.
- [ail-feeder-jsonlogs](https://github.com/ail-project/ail-feeder-jsonlogs) Aggregate JSON log lines and pushes them to AIL.
### AIL Chats Feeders List:
- [ail-feeder-discord](https://github.com/ail-project/ail-feeder-discord) Discord Feeder.
- [ail-feeder-telegram](https://github.com/ail-project/ail-feeder-telegram) Telegram Channels and User Feeder.
### Chats Message
Overview of the JSON fields used by the Chat feeder.
```
{
"data": "New NFT Scam available,"
"meta": {
"chat": {
"date": {
"datestamp": "2023-01-10 08:19:16",
"timestamp": 1673870217.0,
"timezone": "UTC"
},
"icon": "AAAAAAAA",
"id": 123456,
"info": "",
"name": "NFT legit",
"subchannel": {
"date": {
"datestamp": "2023-08-10 08:19:18",
"timestamp": 1691655558.0,
"timezone": "UTC"
},
"id": 285,
"name": "Market"
},
},
"date": {
"datestamp": "2024-02-01 13:43:46",
"timestamp": 1707139999.0,
"timezone": "UTC"
},
"id": 16,
"reply_to": {
"message_id": 12
},
"sender": {
"first_name": "nftmaster",
"icon": "AAAAAAAA",
"id": 5684,
"info": "best legit NFT vendor",
"username": "nft_best"
},
"type": "message"
},
"source": "ail_feeder_telegram",
"source-uuid": "9cde0855-248b-4439-b964-0495b9b2b8bb"
}
```
#### 1. "data"
- Content of the message.
#### 2. "meta"
- Provides metadata about the message.
##### "type":
- Indicates the type of message. It can be either "message" or "image".
##### "id":
- The unique identifier of the message.
##### "date":
- Represents the timestamp of the message.
- "datestamp": The date in the format "YYYY-MM-DD HH:MM:SS".
- "timestamp": The timestamp representing the date and time.
- "timezone": The timezone in which the date and time are specified (e.g., "UTC").
##### "reply_to":
- The unique identifier of a message to which this message is a reply (optional).
- "message_id": The unique identifier of the replied message.
##### "sender":
- Contains information about the sender of the message.
- "id": The unique identifier for the sender.
- "info": Additional information about the sender (optional).
- "username": The sender's username (optional).
- "firstname": The sender's firstname (optional).
- "lastname": The sender's lastname (optional).
- "phone": The sender's phone (optional).
##### "chat":
- Contains information about the chat where the message was sent.
- "date": The chat creation date.
- "datestamp": The date in the format "YYYY-MM-DD HH:MM:SS".
- "timestamp": The timestamp representing the date and time.
- "timezone": The timezone in which the date and time are specified (e.g., "UTC").
- "icon": The icon associated with the chat (optional).
- "id": The unique identifier of the chat.
- "info": Chat description/info (optional).
- "name": The name of the chat.
- "username": The username of the chat (optional).
- "subchannel": If this message is posted in a subchannel within the chat (optional).
- "date": The subchannel creation date.
- "datestamp": The date in the format "YYYY-MM-DD HH:MM:SS".
- "timestamp": The timestamp representing the date and time.
- "timezone": The timezone in which the date and time are specified (e.g., "UTC").
- "id": The unique identifier of the subchannel.
- "name": The name of the subchannel (optional).
#### 3. "source"
- Indicates the feeder name.
#### 4. "source-uuid"
- The UUID associated with the source.
#### Example: Feeding AIL with Conti leaks
```python
from pyail import PyAIL
pyail = PyAIL(URL, API_KEY, ssl=verifycert)
#. . . imports
#. . . setup code
for elem in sys.stdin:
elm = json.loads(elem)
content = elm['body']
meta = {}
meta['jabber:to'] = elm['to']
meta['jabber:from'] = elm['from']
meta['jabber:ts]' = elm['ts']
pyail.feed_json_item(content , meta, feeder_name, feeder_uuid)
```
# AIL SYNC
The synchronisation mechanism allow the sync from one AIL instance to another AIL using a standard WebSocket
using [AIL JSON protocol](https://github.com/ail-project/ail-exchange-format/blob/main/ail-stream.md).
The synchronisation allows to filter and sync specific collected items including crawled items or
specific tagged items matching defined rules.
This feature can be very useful to limit the scope of analysis in specific fields or resource intensive activity.
This sync can be also used to share filtered streams with other partners.
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