name: Sqlite Module In Temp Folder
id: 0f216a38-f45f-11eb-b09c-acde48001122
version: 3
date: '2024-09-30'
author: Teoderick Contreras, Splunk
status: production
type: TTP
description: The following analytic detects the creation of sqlite3.dll files in the %temp% folder. It leverages Sysmon EventCode 11 to identify when these files are written to the temporary directory. This activity is significant because it is associated with IcedID malware, which uses the sqlite3 module to parse browser databases and steal sensitive information such as banking details, credit card information, and credentials. If confirmed malicious, this behavior could lead to significant data theft and compromise of user accounts.
data_source:
- Sysmon EventID 11
search: '`sysmon` EventCode=11 (TargetFilename = "*\\sqlite32.dll" OR TargetFilename = "*\\sqlite64.dll") (TargetFilename = "*\\temp\\*") | stats count min(_time) as firstTime max(_time) as lastTime by dest signature signature_id process_name file_name file_path action process_guid| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `sqlite_module_in_temp_folder_filter`'
how_to_implement: To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.
known_false_positives: unknown
references:
- https://www.cisecurity.org/insights/white-papers/security-primer-icedid
drilldown_searches:
- name: View the detection results for - "$dest$"
  search: '%original_detection_search% | search  dest = "$dest$"'
  earliest_offset: $info_min_time$
  latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$dest$"
  search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") starthoursago=168  | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
  earliest_offset: $info_min_time$
  latest_offset: $info_max_time$
tags:
  analytic_story:
  - IcedID
  asset_type: Endpoint
  confidence: 30
  impact: 30
  message: Process $process_name$ create a file $file_name$ in host $dest$
  mitre_attack_id:
  - T1005
  observable:
  - name: dest
    type: Hostname
    role:
    - Victim
  - name: process_name
    type: Process
    role:
    - Attacker
  product:
  - Splunk Enterprise
  - Splunk Enterprise Security
  - Splunk Cloud
  required_fields:
  - _time
  - process_name
  - TargetFilename
  - EventCode
  - ProcessId
  - Image
  risk_score: 9
  security_domain: endpoint
tests:
- name: True Positive Test
  attack_data:
  - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/malware/icedid/simulated_icedid/windows-sysmon.log
    source: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational
    sourcetype: XmlWinEventLog:Microsoft-Windows-Sysmon/Operational