Windows Credentials from Password Stores Chrome Login Data Access
The following analytic identifies a non-chrome process accessing Chrome user data "login data" file. This sqlite db file stores various information related to the browser's operation on your computer. Threat actor, adversaries and malware author also abused this file to attempt to extract and decrypt password saved in chrome browser. This anomaly detection can be a good pivot of analysis for suspicious process aside from chrome.exe and explorer.exe executable.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2023-04-27
- Author: Teoderick Contreras, Splunk
- ID: 0d32ba37-80fc-4429-809c-0ba15801aeaf
Kill Chain Phase
- CIS 10
1 2 3 4 5 `wineventlog_security` EventCode=4663 object_file_path="*\\AppData\\Local\\Google\\Chrome\\User Data\\Default\\Login Data" AND NOT (process_path IN ("*:\\Windows\\explorer.exe", "*:\\Windows\\System32\\dllhost.exe", "*\\chrome.exe")) | stats count min(_time) as firstTime max(_time) as lastTime by object_file_name object_file_path process_name process_path process_id EventCode dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_credentials_from_password_stores_chrome_login_data_access_filter`
The SPL above uses the following Macros:
windows_credentials_from_password_stores_chrome_login_data_access_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663. For 4663, enable "Audit Object Access" in Group Policy. Then check the two boxes listed for both "Success" and "Failure."
Known False Positives
Uninstall application may access this registry to remove the entry of the target application. filter is needed.
Associated Analytic Story
|49.0||70||70||A non-chrome process $process_name$ accessing Chrome "Login Data" file on $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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