Detection: Download Files Using Telegram

Description

The following analytic detects suspicious file downloads by the Telegram application on a Windows system. It leverages Sysmon EventCode 15 to identify instances where Telegram.exe creates files with a Zone.Identifier, indicating a download. This activity is significant as it may indicate an adversary using Telegram to download malicious tools, such as network scanners, for further exploitation. If confirmed malicious, this behavior could lead to network mapping, lateral movement, and potential compromise of additional systems within the network.

1`sysmon` EventCode= 15 process_name = "telegram.exe" TargetFilename = "*:Zone.Identifier" 
2|stats count min(_time) as firstTime max(_time) as lastTime by dest EventCode process_name process_id TargetFilename Hash 
3| `security_content_ctime(firstTime)` 
4| `security_content_ctime(lastTime)` 
5| `download_files_using_telegram_filter`

Data Source

Name Platform Sourcetype Source
Sysmon EventID 15 Windows icon Windows 'xmlwineventlog' 'XmlWinEventLog:Microsoft-Windows-Sysmon/Operational'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
download_files_using_telegram_filter search *
download_files_using_telegram_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1105 Ingress Tool Transfer Command And Control
KillChainPhase.COMMAND_AND_CONTROL
NistCategory.DE_CM
Cis18Value.CIS_10
APT-C-36
APT18
APT28
APT29
APT3
APT32
APT33
APT37
APT38
APT39
APT41
Ajax Security Team
Andariel
Aquatic Panda
BITTER
BRONZE BUTLER
BackdoorDiplomacy
Chimera
Cinnamon Tempest
Cobalt Group
Confucius
Daggerfly
Darkhotel
Dragonfly
Elderwood
Evilnum
FIN13
FIN7
FIN8
Fox Kitten
GALLIUM
Gamaredon Group
Gorgon Group
HAFNIUM
HEXANE
INC Ransom
IndigoZebra
Indrik Spider
Ke3chang
Kimsuky
Lazarus Group
LazyScripter
Leviathan
LuminousMoth
Magic Hound
Metador
Molerats
Moonstone Sleet
Moses Staff
MuddyWater
Mustang Panda
Mustard Tempest
Nomadic Octopus
OilRig
PLATINUM
Patchwork
Play
Rancor
Rocke
Sandworm Team
SideCopy
Sidewinder
Silence
TA2541
TA505
TA551
TeamTNT
Threat Group-3390
Tonto Team
Tropic Trooper
Turla
Volatile Cedar
Volt Typhoon
WIRTE
Whitefly
Windshift
Winnti Group
Winter Vivern
Wizard Spider
ZIRCONIUM
menuPass

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

To successfully implement this search, you need to be ingesting logs with the process name and TargetFilename from your endpoints or Events that monitor filestream events which is happened when process download something. (EventCode 15) If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.

Known False Positives

normal download of file in telegram app. (if it was a common app in network)

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Suspicious files were downloaded with the Telegram application on $dest$ 49 70 70
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational XmlWinEventLog
Integration ✅ Passing Dataset XmlWinEventLog:Microsoft-Windows-Sysmon/Operational XmlWinEventLog

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range


Source: GitHub | Version: 3