Detection: SSL Certificates with Punycode

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 SSL certificates with Punycode domains in the SSL issuer email domain, identified by the prefix "xn--". It leverages the Certificates Datamodel to flag these domains and uses CyberChef for decoding. This activity is significant as Punycode can be used for domain spoofing and phishing attacks. If confirmed malicious, attackers could deceive users and systems, potentially leading to unauthorized access and data breaches.

1
2| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Certificates.All_Certificates by All_Certificates.SSL.ssl_issuer_email_domain All_Certificates.SSL.ssl_issuer All_Certificates.SSL.ssl_subject_email All_Certificates.SSL.dest All_Certificates.SSL.src All_Certificates.SSL.sourcetype All_Certificates.SSL.ssl_subject_email_domain 
3| `drop_dm_object_name("All_Certificates.SSL")` 
4| eval punycode=if(like(ssl_issuer_email_domain,"%xn--%"),1,0) 
5| where punycode=1 
6| cyberchef infield="ssl_issuer_email_domain" outfield="convertedPuny" jsonrecipe="[{"op":"From Punycode","args":[true]}]" 
7| table ssl_issuer_email_domain convertedPuny ssl_issuer ssl_subject_email dest src sourcetype ssl_subject_email_domain 
8| `ssl_certificates_with_punycode_filter`

Data Source

No data sources specified for this detection.

Macros Used

Name Value
security_content_summariesonly summariesonly=summariesonly_config allow_old_summaries=oldsummaries_config fillnull_value=fillnull_config``
ssl_certificates_with_punycode_filter search *
ssl_certificates_with_punycode_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
T1573 Encrypted Channel Command And Control
KillChainPhase.COMMAND_AND_CONTROL
NistCategory.DE_AE
Cis18Value.CIS_13
APT29
BITTER
Magic Hound
Tropic Trooper

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 Risk Event False
This configuration file applies to all detections of type hunting.

Implementation

Ensure data is properly being ingested into the Certificates datamodel. If decoding the of interest, the CyberChef app is needed https://splunkbase.splunk.com/app/5348. If decoding is not needed, remove the cyberchef lines.

Known False Positives

False positives may be present if the organization works with international businesses. Filter as needed.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
A x509 certificate has been identified to have punycode in the SSL issuer email domain on $dest$. 15 50 30
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

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