Detection rules › Splunk
Windows High File Deletion Frequency
The following analytic identifies a high frequency of file deletions by monitoring Sysmon EventCodes 23 and 26 for specific file extensions. This detection leverages Sysmon logs to track deleted target filenames, process names, and process IDs. Such activity is significant as it often indicates ransomware behavior, where files are encrypted and the originals are deleted. If confirmed malicious, this activity could lead to extensive data loss and operational disruption, as ransomware can render critical files inaccessible, demanding a ransom for their recovery.
Known false positives
- Users may delete a large number of pictures or files in a folder, which could trigger this detection. Additionally, heavy usage of PowerBI and Outlook may also result in false positives.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Impact |
Telemetry coverage
Rule body
name: Windows High File Deletion Frequency
id: 45b125c4-866f-11eb-a95a-acde48001122
version: 15
creation_date: '2021-03-19'
modification_date: '2026-05-13'
author: Teoderick Contreras, Splunk, Steven Dick
status: production
type: Anomaly
description: The following analytic identifies a high frequency of file deletions by monitoring Sysmon EventCodes 23 and 26 for specific file extensions. This detection leverages Sysmon logs to track deleted target filenames, process names, and process IDs. Such activity is significant as it often indicates ransomware behavior, where files are encrypted and the originals are deleted. If confirmed malicious, this activity could lead to extensive data loss and operational disruption, as ransomware can render critical files inaccessible, demanding a ransom for their recovery.
data_source:
- Sysmon EventID 23
- Sysmon EventID 26
search: '`sysmon` EventCode IN ("23","26") TargetFilename IN ("*.cmd", "*.ini","*.gif", "*.jpg", "*.jpeg", "*.db", "*.ps1", "*.doc", "*.docx", "*.xls", "*.xlsx", "*.ppt", "*.pptx", "*.bmp","*.zip", "*.rar", "*.7z", "*.chm", "*.png", "*.log", "*.vbs", "*.js", "*.vhd", "*.bak", "*.wbcat", "*.bkf" , "*.backup*", "*.dsk", "*.win") NOT TargetFilename IN ("*\\INetCache\\Content.Outlook\\*") | stats count min(_time) as firstTime, max(_time) as lastTime values(file_path) as file_path values(file_hash) as file_hash values(file_name) as file_name values(file_modify_time) as file_modify_time values(process_name) as process_name values(process_path) as process_path values(process_guid) as process_guid values(process_id) as process_id values(process_exec) as process_exec by action dest dvc signature signature_id user user_id vendor_product | where count >=100 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_high_file_deletion_frequency_filter`'
how_to_implement: To successfully implement this search, you need to ingest logs that include the deleted target file name, process name, and process ID from your endpoints. If you are using Sysmon, ensure you have at least version 2.0 of the Sysmon TA installed.
known_false_positives: Users may delete a large number of pictures or files in a folder, which could trigger this detection. Additionally, heavy usage of PowerBI and Outlook may also result in false positives.
references:
- https://www.mandiant.com/resources/fin11-email-campaigns-precursor-for-ransomware-data-theft
- https://blog.virustotal.com/2020/11/keep-your-friends-close-keep-ransomware.html
- https://www.microsoft.com/security/blog/2022/01/15/destructive-malware-targeting-ukrainian-organizations/
intermediate_findings:
entities:
- field: user
type: user
score: 20
message: Elevated file deletion rate observed from process [$process_name$] on machine $dest$
- field: dest
type: system
score: 20
message: Elevated file deletion rate observed from process [$process_name$] on machine $dest$
threat_objects:
- field: process_name
type: process_name
analytic_story:
- Sandworm Tools
- Handala Wiper
- Data Destruction
- WhisperGate
- Swift Slicer
- Medusa Ransomware
- DarkCrystal RAT
- Black Basta Ransomware
- Clop Ransomware
- Interlock Ransomware
- NailaoLocker Ransomware
- APT37 Rustonotto and FadeStealer
- DynoWiper
- ZOVWiper
- Void Manticore
asset_type: Endpoint
mitre_attack_id:
- T1485
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
category: endpoint
security_domain: endpoint
Stages and Predicates
Stage 1: search
`sysmon` EventCode IN ("23","26") TargetFilename IN ("*.cmd", "*.ini","*.gif", "*.jpg", "*.jpeg", "*.db", "*.ps1", "*.doc", "*.docx", "*.xls", "*.xlsx", "*.ppt", "*.pptx", "*.bmp","*.zip", "*.rar", "*.7z", "*.chm", "*.png", "*.log", "*.vbs", "*.js", "*.vhd", "*.bak", "*.wbcat", "*.bkf" , "*.backup*", "*.dsk", "*.win") NOT TargetFilename IN ("*\\INetCache\\Content.Outlook\\*")
Stage 2: stats
| stats count min(_time) as firstTime, max(_time) as lastTime values(file_path) as file_path values(file_hash) as file_hash values(file_name) as file_name values(file_modify_time) as file_modify_time values(process_name) as process_name values(process_path) as process_path values(process_guid) as process_guid values(process_id) as process_id values(process_exec) as process_exec by action dest dvc signature signature_id user user_id vendor_product
Stage 3: where
| where count >=100
Stage 4: search
| `security_content_ctime(firstTime)`
Stage 5: search
| `security_content_ctime(lastTime)`
Stage 6: search
| `windows_high_file_deletion_frequency_filter`
Exclusions
The rule actively suppresses these predicates.
| Field | Kind | Excluded values | Search |
|---|---|---|---|
TargetFilename | eq | "*\\INetCache\\Content.Outlook\\*" | excludes:TargetFilename |
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
EventCode | in |
| field:"EventID" kind:in |
TargetFilename | in |
| field:"TargetFilename" kind:in |
count | ge |
| field:"count" kind:ge value:"100" |