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Network Activity Detected via catedit

This rule monitors for the execution of the cat command, followed by a connection attempt by the same process. Cat is capable of transfering data via tcp/udp channels by redirecting its read output to a /dev/tcp or /dev/udp channel. This activity is highly suspicious, and should be investigated. Attackers may leverage this capability to transfer tools or files to another host in the network or exfiltrate data while attempting to evade detection in the process.

Rule type: eql

Rule indices:

  • logs-endpoint.events.*

Severity: medium

Risk score: 47

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: Linux
  • Use Case: Threat Detection
  • Tactic: Command and Control
  • Data Source: Elastic Defend

Version: 6

Rule authors:

  • Elastic

Rule license: Elastic License v2

Investigation guideedit

Triage and analysis

Investigating Network Activity Detected via cat

Attackers may leverage the cat utility in conjunction with a listener to read all bytes of a file, and output the content to a /dev/tcp or /dev/udp channel to transfer/exfiltrate file contents to a remote system.

This rule looks for a sequence of a cat execution event followed by a network connection attempt by the same cat process.

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. This investigation guide uses placeholder fields to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you’re using Elastic Stack version 8.6.0 or earlier, you’ll need to manually adjust this investigation guide’s queries to ensure they properly run.

Possible investigation steps

  • Identify any signs of suspicious network activity or anomalies that may indicate command and control activity or data exfiltration. This could include unexpected traffic patterns or unusual network behavior.
  • Investigate listening ports and open sockets to look for potential protocol tunneling, reverse shells, or data exfiltration.
  • !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
  • !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
  • Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
  • !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
  • Investigate whether the user is currently logged in and active.
  • !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
  • Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
  • !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
  • !{osquery{"label":"Osquery - Retrieve Process Info","query":"SELECT name, cmdline, parent, path, uid FROM processes"}}
  • Investigate other alerts associated with the user/host during the past 48 hours.
  • If scripts or executables were dropped, retrieve the files and determine if they are malicious:
  • Use a private sandboxed malware analysis system to perform analysis.
  • Observe and collect information about the following activities:
  • Attempts to contact external domains and addresses.
  • Check if the domain is newly registered or unexpected.
  • Check the reputation of the domain or IP address.
  • File access, modification, and creation activities.

Related rules

  • Suspicious Network Activity to the Internet by Previously Unknown Executable - 53617418-17b4-4e9c-8a2c-8deb8086ca4b

False positive analysis

  • If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
  • Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.

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, such as reverse shells, reverse proxies, or droppers, that attackers could use to reinfect the system.
  • Remove and block malicious artifacts identified during triage.
  • 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.
  • Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
  • Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
  • Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).

Setupedit

Setup

This rule requires data coming in from Elastic Defend.

Elastic Defend Integration Setup

Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.

Prerequisite Requirements:

  • Fleet is required for Elastic Defend.
  • To configure Fleet Server refer to the documentation.

The following steps should be executed in order to add the Elastic Defend integration on a Linux System:

  • Go to the Kibana home page and click "Add integrations".
  • In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
  • Click "Add Elastic Defend".
  • Configure the integration name and optionally add a description.
  • Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
  • Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. Helper guide.
  • We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
  • Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead. For more details on Elastic Agent configuration settings, refer to the helper guide.
  • Click "Save and Continue".
  • To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts. For more details on Elastic Defend refer to the helper guide.

Rule queryedit

sequence by host.id, process.entity_id with maxspan=1s
  [process where host.os.type == "linux" and event.type == "start" and event.action == "exec" and
   process.name == "cat" and process.parent.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish")]
  [network where host.os.type == "linux" and event.action in ("connection_attempted", "disconnect_received") and
   process.name == "cat" and not (destination.ip == null or destination.ip == "0.0.0.0" or cidrmatch(
     destination.ip, "10.0.0.0/8", "127.0.0.0/8", "169.254.0.0/16", "172.16.0.0/12", "192.0.0.0/24", "192.0.0.0/29",
     "192.0.0.8/32", "192.0.0.9/32", "192.0.0.10/32", "192.0.0.170/32", "192.0.0.171/32", "192.0.2.0/24",
     "192.31.196.0/24", "192.52.193.0/24", "192.168.0.0/16", "192.88.99.0/24", "224.0.0.0/4", "100.64.0.0/10",
     "192.175.48.0/24","198.18.0.0/15", "198.51.100.0/24", "203.0.113.0/24", "240.0.0.0/4", "::1", "FE80::/10",
     "FF00::/8"
     )
   )]

Framework: MITRE ATT&CKTM

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