Name:Detect Remote Access Software Usage File id:3bf5541a-6a45-4fdc-b01d-59b899fff961 version:4 date:2024-09-30 author:Steven Dick status:production type:Anomaly Description:The following analytic detects the writing of files from known remote access software to disk within the environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on file path, file name, and user information. This activity is significant as adversaries often use remote access tools like AnyDesk, GoToMyPC, LogMeIn, and TeamViewer to maintain unauthorized access. If confirmed malicious, this could allow attackers to persist in the environment, potentially leading to data exfiltration, further compromise, or complete control over affected systems. Data_source:
-Sysmon EventID 11
search:| tstats `security_content_summariesonly` count, min(_time) as firstTime, max(_time) as lastTime, values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.dest, Filesystem.user, Filesystem.file_name | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Filesystem)` | lookup remote_access_software remote_utility AS file_name OUTPUT isutility, description as signature, comment_reference as desc, category | search isutility = TRUE | `remote_access_software_usage_exceptions` | `detect_remote_access_software_usage_file_filter`
how_to_implement:The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the file path, file name, and the user that created the file. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the `Filesystem` node of the `Endpoint` data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process. The "exceptions" macro leverages both an Assets and Identities lookup, as well as a KVStore collection called "remote_software_exceptions" that lets you track and maintain device-based exceptions for this set of detections. known_false_positives:Known or approved applications used by the organization or usage of built-in functions. Known false positives can be added to the remote_access_software_usage_exception.csv lookup to globally suppress these situations across all remote access content References: -https://attack.mitre.org/techniques/T1219/ -https://thedfirreport.com/2022/08/08/bumblebee-roasts-its-way-to-domain-admin/ -https://thedfirreport.com/2022/11/28/emotet-strikes-again-lnk-file-leads-to-domain-wide-ransomware/ drilldown_searches: name:'View the detection results for - "$dest$" and "$user$"' search:'%original_detection_search% | search dest = "$dest$" user = "$user$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$" and "$user$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$", "$user$") 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: - 'Insider Threat' - 'Command And Control' - 'Ransomware' - 'Gozi Malware' - 'CISA AA24-241A' asset_type:Endpoint confidence:50 impact:50 message:A file for known a remote access software [$file_name$] was created on $dest$ by $user$. mitre_attack_id: - 'T1219' observable: name:'dest' type:'Hostname' - role: - 'Victim' name:'user' type:'User' - role: - 'Victim' name:'file_name' type:'File Name' - role: - 'Attacker' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' required_fields: - '_time' - 'Filesystem.dest' - 'Filesystem.user' - 'Filesystem.file_name' risk_score:25 security_domain:endpoint manual_test:This detection uses A&I lookups from Enterprise Security.
