IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.
« AdFind Command Activity AdminSDHolder Backdoor »
Elastic Docs ›Elastic Security Solution [8.14] ›Detections and alerts ›Prebuilt rule reference

Adding Hidden File Attribute via Attrib

edit

Adding Hidden File Attribute via Attrib

edit

Adversaries can add the hidden attribute to files to hide them from the user in an attempt to evade detection.

Rule type: eql

Rule indices:

  • winlogbeat-*
  • logs-endpoint.events.process-*
  • logs-windows.forwarded*
  • logs-windows.sysmon_operational-*
  • endgame-*
  • logs-system.security*
  • logs-m365_defender.event-*
  • logs-sentinel_one_cloud_funnel.*
  • logs-crowdstrike.fdr*

Severity: low

Risk score: 21

Runs every: 5m

Searches indices from: now-9m (Date Math format, see also Additional look-back time)

Maximum alerts per execution: 100

References: None

Tags:

  • Domain: Endpoint
  • OS: Windows
  • Use Case: Threat Detection
  • Tactic: Defense Evasion
  • Tactic: Persistence
  • Data Source: Elastic Endgame
  • Resources: Investigation Guide
  • Data Source: Elastic Defend
  • Data Source: System
  • Data Source: Microsoft Defender for Endpoint
  • Data Source: Sysmon
  • Data Source: SentinelOne
  • Data Source: Crowdstrike

Version: 314

Rule authors:

  • Elastic

Rule license: Elastic License v2

Investigation guide

edit

Triage and analysis

Investigating Adding Hidden File Attribute via Attrib

The Hidden attribute is a file or folder attribute that makes the file or folder invisible to regular directory listings when the attribute is set.

Attackers can use this attribute to conceal tooling and malware to prevent administrators and users from finding it, even if they are looking specifically for it.

This rule looks for the execution of the attrib.exe utility with a command line that indicates the modification of the Hidden attribute.

Note: This investigation guide uses the Osquery Markdown Plugin introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.

Possible investigation steps

  • Identify the user account that performed the action and whether it should perform this kind of action.
  • Contact the account owner and confirm whether they are aware of this activity.
  • Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
  • Investigate other alerts associated with the user/host during the past 48 hours.
  • Examine the command line to identify the target file or folder.
  • Examine the file, which process created it, header, etc.
  • If suspicious, retrieve the files' SHA-256 hash values using the PowerShell Get-FileHash cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
  • Examine the host for derived artifacts that indicate suspicious activities:
  • Observe and collect information about the following activities in the alert subject host:
  • Attempts to contact external domains and addresses.
  • Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' process.entity_id.
  • Examine the DNS cache for suspicious or anomalous entries.
  • !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
  • Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
  • Examine the host services for suspicious or anomalous entries.
  • !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
  • !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE %LocalSystem OR user_account LIKE %LocalService OR user_account LIKE %NetworkService OR\nuser_account == null)\n"}}
  • !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat(https://www.virustotal.com/gui/file/, sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != trusted\n"}}

False positive analysis

  • This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.

Response and remediation

  • Initiate the incident response process based on the outcome of the triage.
  • Isolate the involved host to prevent further post-compromise behavior.
  • If the triage identified malware, search the environment for additional compromised hosts.
  • Implement temporary network rules, procedures, and segmentation to contain the malware.
  • Stop suspicious processes.
  • Immediately block the identified indicators of compromise (IoCs).
  • Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
  • Remove and block malicious artifacts identified during triage.
  • Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
  • Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
  • Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
  • Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).

Rule query

edit
process where host.os.type == "windows" and event.type == "start" and
  (process.name : "attrib.exe" or ?process.pe.original_file_name == "ATTRIB.EXE") and process.args : "+h" and
  not (process.parent.name: "cmd.exe" and process.command_line: "attrib  +R +H +S +A *.cui")

Framework: MITRE ATT&CKTM

« AdFind Command Activity AdminSDHolder Backdoor »