Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
330 detections
Filters
Last updated
All Time
Detection languages
158
115
22
15
10
Contributors
147
71
32
32
7
Categories
167
156
109
109
96
Platforms
199
104
22
21
17
Products / Services
161
150
64
56
37
MITRE Techniques
18,108
15,613
12,573
8,384
6,203
CVEs
2
IDS Classtypes
107
17
10
10
8
IDS Protocols
86
35
28
3
1
Detects potential Unicode-based homograph attacks by scanning for non-ASCII characters in both DeviceNetworkEvents.RemoteUrl and EmailUrlInfo.Url. These attacks leverage visually deceptive domain names—using characters from non-Latin scripts (e.g., Cyrillic "а" instead of Latin "a")—to mimic legitimate sites and deceive users.
The detection covers both network activity and email delivery paths, helping uncover phishing attempts, credential harvesting links, or other malicious redirects.
Recommendation: If available, include telemetry from DNS logs (e.g., DnsEvents) and firewall/proxy logs to improve detection coverage and correlate threats across multiple layers of the kill chain.
The detection covers both network activity and email delivery paths, helping uncover phishing attempts, credential harvesting links, or other malicious redirects.
Recommendation: If available, include telemetry from DNS logs (e.g., DnsEvents) and firewall/proxy logs to improve detection coverage and correlate threats across multiple layers of the kill chain.
📌 Description
Threat actors frequently register lookalike domains to support malicious activities such as phishing attacks, drive-by compromises, and command-and-control (C2) operations. This KQL hunting query is designed to help identify potential phishing and typosquatting domains that may be targeting your organization or its third-party vendors.
🔍 Threat Intelligence Feed
The hunting query utilizes data from the SANS Internet Storm Center (ISC) API, which provides access to newly registered domains.
API Endpoint:
https://isc.sans.edu/api/recentdomains/today?json
Use Cases:
Threat intelligence enrichment
Detection of suspicious or malicious domains
Security log correlation
Returned Data Fields:
Domain name
Registration date
IP address
Type
Additional metadata (if available)
Query by Date (Optional):
Example: https://isc.sans.edu/api/recentdomains/2025-07-08?json
🎯 ATT&CK Framework Mapping
Technique: Acquire Infrastructure: Domains
ID: T1583.001
Reference: MITRE ATT&CK
Threat actors frequently register lookalike domains to support malicious activities such as phishing attacks, drive-by compromises, and command-and-control (C2) operations. This KQL hunting query is designed to help identify potential phishing and typosquatting domains that may be targeting your organization or its third-party vendors.
🔍 Threat Intelligence Feed
The hunting query utilizes data from the SANS Internet Storm Center (ISC) API, which provides access to newly registered domains.
API Endpoint:
https://isc.sans.edu/api/recentdomains/today?json
Use Cases:
Threat intelligence enrichment
Detection of suspicious or malicious domains
Security log correlation
Returned Data Fields:
Domain name
Registration date
IP address
Type
Additional metadata (if available)
Query by Date (Optional):
Example: https://isc.sans.edu/api/recentdomains/2025-07-08?json
🎯 ATT&CK Framework Mapping
Technique: Acquire Infrastructure: Domains
ID: T1583.001
Reference: MITRE ATT&CK
This detection identifies network traffic to domains known to be used as command and control (C2) infrastructure in recent SharePoint exploitation campaigns. Communication with these domains is a strong indicator of compromise.
KQL Query from file: MDO - Enhancing Email Security with NRD Filtering
KQL Query from file: Exposure Management - Slim's Metric (MaxCVSS-DAW)
This rule detects attempts to access domains that have been registered within the last 30 days. It correlates network HTTP or generic network connection events with WHOIS data to identify recently created domains. The rule leverages WHOIS enrichment to determine the creation time of the accessed domain and flags any access to domains created within the specified 30-day window.
This rule detects when a network connection is made to a domain that has expired. It leverages WHOIS data to identify domains whose expiration time is before the event timestamp. The rule specifically looks for HTTP network events and joins them with WHOIS information to identify access to recently expired domains. This could indicate access to potentially malicious infrastructure, as expired domains can be re-registered by threat actors for nefarious purposes.
Example usage of WHOIS data, detecting an executable file download from a domain that's recently expired
This 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.
The following analytic detects the presence of punycode within x509 certificates using Zeek x509 logs. It identifies punycode in the subject alternative name email and other fields by searching for the "xn--" prefix. This activity is significant as punycode can be used in phishing attacks or to bypass domain filters, posing a security risk. If confirmed malicious, attackers could use these certificates to impersonate legitimate domains, potentially leading to unauthorized access or data breaches.
The following analytic identifies web requests to domains that closely resemble your monitored brand's domain, indicating potential brand abuse. It leverages data from web traffic sources, such as web proxies or network traffic analysis tools, and cross-references these with known domain permutations generated by the "ESCU - DNSTwist Domain Names" search. This activity is significant as it can indicate phishing attempts or other malicious activities targeting your brand. If confirmed malicious, attackers could deceive users, steal credentials, or distribute malware, leading to significant reputational and financial damage.
This rule detects DNS queries to domains that have been created within the last 30 days. This behavior can be indicative of newly registered malicious domains used for command and control, phishing, or other adversarial activities. The rule correlates DNS query events with WHOIS data to identify the domain creation time.
This rule detects DNS queries for domains that contain a specific string (e.g., a company name) and are not registered with an approved domain registrar. It leverages WHOIS data to identify potentially malicious typosquatting domains that have been recently registered or observed. The rule specifically looks for DNS queries where the domain name matches a defined pattern (e.g., 'threatpunter') and the WHOIS information indicates a registrar other than the approved one ('MarkMonitor Inc.'). Additionally, it checks if the domain was first seen in the environment within the last 30 days, indicating a new or suspicious registration.
This rule detects DNS queries for domains that have a very low rolling maximum prevalence (3 or less over a 10-day period). This can indicate newly registered domains, domains used for command and control, or other suspicious activity that has not yet gained widespread legitimate use. The rule correlates DNS events with derived prevalence data to identify these low-prevalence domains.
Provides example usage of WHOIS data, detecting a DNS query for a domain that contains a specific string and is not registered with the defined domain registrar.
Page 16 of 16



