Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
228 detections
Filters
Last updated
All Time
Detection languages
192
13
9
6
5
Contributors
70
39
34
22
15
Categories
20,427
11,813
5,871
5,145
4,864
Platforms
191
50
12
11
10
Products / Services
196
33
25
24
7
MITRE Techniques
141
127
107
70
56
CVEs
2
IDS Classtypes
6
2
1
IDS Protocols
9
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
This rule monitors for network communication with a specific known malicious IP address and URL path, as well as the execution or presence of associated malicious file hashes. Additionally, it flags emails involving specific indicators identified as potentially associated with malicious activity.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule monitors for network communication with a specific known malicious IP address and URL path, as well as the execution or presence of associated malicious file hashes. Additionally, it flags emails involving specific indicators identified as potentially associated with malicious activity.
This rule monitors for network communication with a specific known malicious IP address and URL path, as well as the execution or presence of associated malicious file hashes. Additionally, it flags emails involving specific indicators identified as potentially associated with malicious activity.
This rule monitors for network communication with a specific known malicious IP address and URL path, as well as the execution or presence of associated malicious file hashes. Additionally, it flags emails involving specific indicators identified as potentially associated with malicious activity.
This rule detects incoming phishing emails that use specific financial or payment-related lures (e.g., 'eft wire transfer', 'invoice receipt') in the subject line or body to entice users into clicking a link that points directly to an executable file, often disguised as a document.
This rule detects incoming phishing emails that use specific financial or payment-related lures (e.g., 'eft wire transfer', 'invoice receipt') in the subject line or body to entice users into clicking a link that points directly to an executable file, often disguised as a document.
This rule detects incoming phishing emails that use specific financial or payment-related lures (e.g., 'eft wire transfer', 'invoice receipt') in the subject line or body to entice users into clicking a link that points directly to an executable file, often disguised as a document.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects potential phishing or HTML smuggling attempts by identifying a burst of anomalously large SVG file attachments delivered via email to multiple recipients, followed by a correlation with web browser process network activity from the same recipients shortly after the email delivery.
Detects incoming spearphishing emails that contain a ZIP archive attachment. The rule alerts if the archive contains an LNK file with a double extension (e.g., .pdf.lnk) or if the email subject contains specific social engineering lures related to food pricing or peace negotiations.
Detects a multi-stage phishing pattern attributed to Star Blizzard (also known as Callisto Group or COLDRIVER). The attack involves an initial email containing no attachments to establish trust or initiate a thread, followed by a subsequent reply-thread email containing both an archive file (ZIP/RAR) and an image file. This technique is designed to bypass email security scanners by hiding the archive password within the image attachment or obscuring the malicious payload context.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects potentially malicious emails that impersonate Microsoft account security notifications or security advisories. It looks for emails with specific social engineering themes in the sender name, sender address, or subject line, accompanied by .zip attachments that contain suspicious file names related to cybersecurity warnings or OTP abuse, which are common lures for malware delivery.
This rule correlates email attachment delivery events with subsequent process creation events on the recipient's endpoint. It identifies scenarios where a known document reader or mail client (Outlook, Word, Excel, PowerPoint, Adobe Acrobat/Reader) spawns a suspicious child process (PowerShell, CMD, WScript, CScript, MSHTA, Rundll32, or Regsvr32) shortly after a file is delivered via email to the same user. This detects the immediate execution phase of a phishing attack.
This rule detects incoming email messages containing .zip attachments with filenames that mimic financial documents (e.g., NFe, DANFE, invoice-related keywords) combined with numerical strings. This naming pattern is commonly associated with phishing campaigns attempting to deliver malicious archives.
Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
Page 2 of 11


