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Go
The Go library is a simple abstraction to the LimaCharlie.io REST API. The REST API currently supports many more functions. If it's missing a function available in the REST API that you would like to use, let us know at support@limacharlie.io.
Getting Started
Authentication
You can use Client Options to declare your client/org, or you can use environment variables.
Using Environment Variables:
LC_OID
: Organization IDLC_API_KEY
: your LC API KEYLC_UID
: optional, your user ID
package main
import (
"fmt"
"github.com/refractionPOINT/go-limacharlie/limacharlie"
)
func main() {
client, err := limacharlie.NewClientFromLoader(limacharlie.ClientOptions{}, nil, &limacharlie.EnvironmentClientOptionLoader{})
if err != nil {
fmt.Println(err)
}
org, _ := limacharlie.NewOrganization(client)
fmt.Printf("Hello, this is %s", org.GetOID())
}
Using Client Options:
package main
import (
"fmt"
"github.com/refractionPOINT/go-limacharlie/limacharlie"
)
func main() {
clientOptions = limacharlie.ClientOptions{
OID: "MY_OID",
APIKey: "MY_API_KEY",
UID: "MY_UID",
}
org, _ := limacharlie.NewOrganizationFromClientOptions(clientOptions, nil)
fmt.Printf("Hello, this is %s", org.GetOID())
}
SDK
Examples
package main
import (
"fmt"
"github.com/refractionPOINT/go-limacharlie/limacharlie"
)
func main() {
client, err := limacharlie.NewClientFromLoader(limacharlie.ClientOptions{}, nil, &limacharlie.EnvironmentClientOptionLoader{})
if err != nil {
fmt.Println(err)
}
org, _ := limacharlie.NewOrganization(client)
// List all sensors
sensors, err := org.ListSensors()
if err != nil {
fmt.Println(err)
}
for sid, sensor := range sensors {
fmt.Printf("%s - %s", sid, sensor.Hostname)
}
// List D&R rules from Hive
hiveClient := limacharlie.NewHiveClient(org)
rules, _ := hiveClient.List(limacharlie.HiveArgs{
HiveName: "dr-general",
PartitionKey: org.GetOID(),
})
for rule_name, _ := range rules {
fmt.Println(rule_name)
}
// Add D&R rule to Hive
enabled := true
case_sensitive := false
if _, err := hiveClient.Add(limacharlie.HiveArgs{
HiveName: "dr-general",
PartitionKey: org.GetOID(),
Key: "test_rule_name",
Enabled: &enabled,
Data: limacharlie.Dict{
"detect": limacharlie.Dict{
"event": "NEW_PROCESS",
"op": "is",
"path": "event/COMMAND_LINE",
"value": "whoami",
"case sensitive": &case_sensitive,
},
"respond": []limacharlie.Dict{{
"action": "report",
"name": "whoami detection",
}},
},
}); err != nil {
fmt.Println(err)
}
// List extensions
extensions, _ := org.Extensions()
for _, extension_name := range extensions {
fmt.Println(extension_name)
}
// Subscribe to extension
subscription_request := org.SubscribeToExtension("binlib")
if subscription_request != nil {
fmt.Println(subscription_request)
}
// List payloads
payloads, _ := org.Payloads()
for payload, _ := range payloads {
fmt.Println(payload)
}
// List installation keys
installation_keys, _ := org.InstallationKeys()
for _, key := range installation_keys {
fmt.Println(key.Description)
}
// Create installation key
key_request, _ := org.AddInstallationKey(InstallationKey{
Description: "my-test-key",
Tags: []string{"tag", "another-tag"},
})
}
Python
The Python library is a simple abstraction to the LimaCharlie.io REST API. The REST API currently supports many more functions. If it's missing a function available in the REST API that you would like to use, let us know at support@limacharlie.io.
Getting Started
Installing
pip install limacharlie
Credentials
Authenticating to use the SDK / CLI can be done in a few ways.
Option 1 - Logging In
The simplest is to login to an Organization using an API key.
Use limacharlie login
to store credentials locally. You will need an OID
(Organization ID) and an API key, and (optionally) a UID
(User ID), all of which you can get from the Access Management --> REST API section of the web interface.
The login interface supports named environments, or a default one used when no environment is selected.
To list available environments:
limacharlie use
Setting a given environment in the current shell session can be done like this:
limacharlie use my-dev-org
You can also specify a UID
(User ID) during login to use a user API key representing
the total set of permissions that user has (see User Profile in the web interface).
Option 2 - Environment Variables
You can use the LC_OID
and LC_API_KEY
and LC_UID
environment variables to replace the values used logging in. The environment variables will be used if no other credentials are specified.
SDK
The root of the functionality in the SDK is from the Manager
object. It holds the credentials and is tied to a specific LimaCharlie Organization.
You can authenticate the Manager
using an oid
(and optionally a uid
), along with either a secret_api_key
or jwt
directly. Alternatively you can just use an environment name (as specified in limacharlie login
). If no creds are provided, the Manager
will try to use the default environment and credentials.
Importing
import limacharlie
YARA_SIG = 'https://raw.githubusercontent.com/Yara-Rules/rules/master/Malicious_Documents/Maldoc_PDF.yar'
# Create an instance of the SDK.
mgr = limacharlie.Manager()
# Get a list of all the sensors in the current Organization.
all_sensors = mgr.sensors()
# Select the first sensor in the list.
sensor = all_sensors[0]
# Tag this sensor with a tag for 10 minutes.
sensor.tag( 'suspicious', ttl = 60 * 10 )
# Send a task to the sensor (unidirectionally, not expecting a response).
sensor.task( 'os_processes' )
# Send a yara scan to that sensor for processes "evil.exe".
sensor.task( 'yara_scan -e *evil.exe ' + YARA_SIG )
Use of gevent
Note that the SDK uses the gevent
package which sometimes has issues with other
packages that operate at a low level in python. For example, Jupyter notebooks
may see freezing on importing limacharlie
and require a tweak to load:
{
"display_name": "IPython 2 w/gevent",
"language": "python",
"argv": [
"python",
"-c", "from gevent.monkey import patch_all; patch_all(thread=False); from ipykernel.kernelapp import main; main()",
"-f",
"{connection_file}"
]
}
Components
Manager
This is a the general component that provides access to the managing functions of the API like querying sensors online, creating and removing Outputs etc.
Firehose
The Firehose
is a simple object that listens on a port for LimaCharlie.io data. Under the hood it creates a Syslog Output on limacharlie.io pointing to itself and removes it on shutdown. Data from limacharlie.io is added to firehose.queue
(a gevent Queue
) as it is received.
It is a basic building block of automation for limacharlie.io.
Spout
Much like the Firehose
, the Spout receives data from LimaCharlie.io, the difference
is that the Spout
does not require opening a local port to listen actively on. Instead
it leverages stream.limacharlie.io
to receive the data stream over HTTPS.
A Spout
is automatically created when you instantiate a Manager
with theis_interactive = True
and inv_id = XXXX
arguments in order to provide real-time
feedback from tasking sensors.
Sensor
This is the object returned by manager.sensor( sensor_id )
.
It supports a task
, hostname
, tag
, untag
, getTags
and more functions. This
is the main way to interact with a specific sensor.
The task
function sends a task to the sensor unidirectionally, meaning it does not
receive the response from the sensor (if any). If you want to interact with a sensor
in real-time, use the interactive mode (as mentioned in the Spout
) and use either
the request
function to receive replies through a FutureResults
object or thesimpleRequest
to wait for the response and receive it as a return value.
Artifacts
The Artifacts
is a helpful class to upload artifacts to LimaCharlie without going through a sensor.
Extensions
The Extensions
can be used to subscribe to and manage extensions within your org.
import limacharlie
from limacharlie import Extension
mgr = limacharlie.Manager()
ext = Extension(mgr)
ext.subscribe('binlib')
Payloads
The Payloads
can be used to manage various executable payloads accessible to sensors.
Replay
The Replay
object allows you to interact with Replay jobs managed by LimaCharlie. These allow you to re-run D&R Rules on historical data.
Sample command line to query one sensor:
limacharlie-replay --sid 9cbed57a-6d6a-4af0-b881-803a99b177d9 --start 1556568500 --end 1556568600 --rule-content ./test_rule.txt
Sample command line to query an entire organization:
limacharlie-replay --entire-org --start 1555359000 --end 1556568600 --rule-name my-rule-name
Search
The Search
object allows you to perform an IOC search across multiple organizations.
SpotCheck
The SpotCheck
object (sometimes called Fleet Check) allows you to manage an active (query sensors directly as opposed to searching on indexed historical data) search for various IOCs on an organization's sensors.
Configs
The Configs
is used to retrieve an organization's configuration as a config file, or apply
an existing config file to an organization. This is the concept of Infrastructure as Code.
Webhook
The Webhook
object demonstrates handling webhooks emitted by the LimaCharlie cloud, including verifying the shared-secret signing of the webhooks.
Examples:
Command Line Interface
Many of the objects available as part of the LimaCharlie Python SDK also support various command line interfaces.
Query
LimaCharlie Query Language (LCQL) provides a flexible, intuitive and interactive way to explore your data in LimaCharlie.
limacharlie query --help
ARLs
Authenticated Resource Locators (ARLs) describe a way to specify access to a remote resource, supporting many methods, including authentication data, and all that within a single string.
ARLs can be used in the YARA manager to import rules from GitHub repositories and other locations.
Testing an ARL before applying it somewhere can be helpful to shake out access or authentication errors beforehand. You can test an ARL and see what files are fetched, and their contents, by running the following command:
limacharlie get-arl -a [github,Yara-Rules/rules/email]
Firehose
Listens on interface 1.2.3.4
, port 9424
for incoming connections from LimaCharlie.io.
Receives only events from hosts tagged with fh_test
.
python -m limacharlie.Firehose 1.2.3.4:9424 event -n firehose_test -t fh_test --oid c82e5c17-d519-4ef5-a4ac-caa4a95d31ca
Spout
Behaves similarly to the Firehose, but instead of listening from an internet accessible port, it connects to the stream.limacharlie.io
service to stream the output over HTTPS. This means the Spout allows you to get ad-hoc output like the Firehose, but it also works through NATs and proxies.
It is MUCH more convenient for short term ad-hoc outputs, but it is less reliable than a Firehose for very large amounts of data.
python -m limacharlie.Spout event --oid c82e5c17-d519-4ef5-a4ac-caa4a95d31ca
Configs
The fetch
command will get a list of the Detection & Response rules in your
organization and will write them to the config file specified or the default
config file lc_conf.yaml
in YAML format.
limacharlie configs fetch --oid c82e5c17-d519-4ef5-a4ac-c454a95d31ca`
Then push
can upload the rules specified in the config file (or the default one)
to your organization. The optional --force
argument will remove active rules not
found in the config file. The --dry-run
simulates the sync and displays the changes
that would occur.
The --config
allows you to specify an alternate config file and the --api-key
allows
you to specify a file on disk where the API should be read from (otherwise, of if -
is
specified as a file, the API Key is read from STDIN).
limacharlie configs push --dry-run --oid c82e5c17-d519-4ef5-a4ac-c454a95d31ca --config /path/to/template.yaml --all --ignore-inaccessible
All these capabilities are also supported directly by the limacharlie.Configs
object.
The Sync functionality currently supports all common useful configurations. The --no-rules
and --no-outputs
flags can be used to ignore one or the other in config files and sync. Additional flags are also supported, see limacharlie configs --help
.
To understand better the config format, do a fetch
from your organization. Notice the use of the include
statement. Using this statement you can combine multiple config files together, making
it ideal for the management of complex rule sets and their versioning.
Spot Checks
Used to perform Organization-wide checks for specific indicators of compromise. Available as a custom API SpotCheck
object or as a module from the command line. Supports many types of IoCs like file names, directories, registry keys, file hashes and YARA signatures.
python -m limacharlie.SpotCheck --no-macos --no-linux --tags vip --file c:\\evil.exe`
For detailed usage:
python -m limacharlie.SpotCheck --help
Search
Shortcut utility to perform IOC searches across all locally configured organizations.
limacharlie search --help
Extensions
Shortcut utility to manage extensions.
limacharlie extension --help
Artifact Upload
Shortcut utility to upload and retrieve Artifacts within LimaCharlie with just the CLI (no agent).
limacharlie artifacts --help
Artifact Download
Shortcut utility to download Artifact Collection in LimaCharlie locally.
limacharlie artifacts get_original --help
Replay
Shortcut utility to perform Replay jobs from the CLI.
limacharlie replay --help
Detection & Response
Shortcut utility to manage Detection and Response rules over the CLI.
limacharlie dr --help
Events & Detections
Print out to STDOUT events or detections matching the parameter.
limacharlie events --help
limacharlie detections --help
List Sensors
Print out all basic sensor information for all sensors matching the selector.
limacharlie sensors --selector 'plat == windows'