Detection: Detect ARP Poisoning

EXPERIMENTAL DETECTION

This detection status is set to experimental. The Splunk Threat Research team has not yet fully tested, simulated, or built comprehensive datasets for this detection. As such, this analytic is not officially supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Description

The following analytic detects ARP Poisoning attacks by monitoring for Dynamic ARP Inspection (DAI) errors on Cisco network devices. It leverages logs from Cisco devices, specifically looking for events where the ARP inspection feature has disabled an interface due to suspicious activity. This activity is significant because ARP Poisoning can allow attackers to intercept, modify, or disrupt network traffic, leading to potential data breaches or denial of service. If confirmed malicious, this could enable attackers to perform man-in-the-middle attacks, compromising the integrity and confidentiality of network communications.

1`cisco_networks` facility="PM" mnemonic="ERR_DISABLE" disable_cause="arp-inspection" 
2| eval src_interface=src_int_prefix_long+src_int_suffix 
3| stats min(_time) AS firstTime max(_time) AS lastTime count BY host src_interface 
4| `security_content_ctime(firstTime)`
5|`security_content_ctime(lastTime)`
6| `detect_arp_poisoning_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
cisco_networks eventtype=cisco_ios
detect_arp_poisoning_filter search *
detect_arp_poisoning_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1200 Hardware Additions Initial Access
T1498 Network Denial of Service Impact
T1557 Adversary-in-the-Middle Collection
T1557.002 ARP Cache Poisoning Credential Access
KillChainPhase.ACTIONS_ON_OBJECTIVES
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
NistCategory.DE_CM
Cis18Value.CIS_13
DarkVishnya
APT28
Kimsuky
Cleaver
LuminousMoth

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

This search uses a standard SPL query on logs from Cisco Network devices. The network devices must be configured with DHCP Snooping (see https://www.cisco.com/c/en/us/td/docs/switches/lan/catalyst2960x/software/15-0_2_EX/security/configuration_guide/b_sec_152ex_2960-x_cg/b_sec_152ex_2960-x_cg_chapter_01101.html) and Dynamic ARP Inspection (see https://www.cisco.com/c/en/us/td/docs/switches/lan/catalyst2960x/software/15-2_2_e/security/configuration_guide/b_sec_1522e_2960x_cg/b_sec_1522e_2960x_cg_chapter_01111.html) and log with a severity level of minimum "5 - notification". The search also requires that the Cisco Networks Add-on for Splunk (https://splunkbase.splunk.com/app/1467) is used to parse the logs from the Cisco network devices.

Known False Positives

This search might be prone to high false positives if DHCP Snooping or ARP inspection has been incorrectly configured, or if a device normally sends many ARP packets (unlikely).

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
tbd 25 50 50
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Not Applicable N/A N/A N/A
Unit ❌ Failing N/A N/A N/A
Integration ❌ Failing N/A N/A N/A

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range


Source: GitHub | Version: 3