Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,431 detections
Filters
Last updated
All Time
Detection languages
2,428
3
Contributors
747
554
405
315
183
Categories
1,914
1,291
689
671
449
Platforms
2,202
183
149
62
49
Products / Services
2,366
1,378
38
37
25
MITRE Techniques
537
454
342
308
301
CVEs
17
10
9
9
9
IDS Classtypes
1,098
452
204
154
102
IDS Protocols
2,431
868
408
324
97
Detects CI/CD package manager traffic (e.g., pip, npm) attempting to connect to domains that mimic legitimate PyPI or npm registry domains. This behavior is indicative of a dependency confusion or supply chain attack where an adversary uses typosquatted or phantom-squatted domains to intercept or redirect package requests.
Detects HTTP requests where the referrer is a major LLM service (e.g., ChatGPT, Claude) but the destination host uses keywords indicative of phantom squatting (e.g., parcel, delivery, login) suggesting an attempt to use LLM-generated content or platforms to facilitate malicious redirects or phishing.
Detects HTTP POST requests to known phishing kit endpoints 'panel_track.php' or 'verify_api.php', which are associated with the Montana Empire credential harvesting campaign.
This rule detects outbound HTTP traffic generated by the WinHTTP library, specifically when the User-Agent identifies as WinHttp.WinHttpRequest. This pattern is indicative of potential post-exploitation activity, such as command-and-control communication or data exfiltration, originating from a process associated with an exploited Excel document (CVE-2025-60727).
Detects inbound HTTP requests containing JNDI lookup strings commonly used to exploit the Log4Shell vulnerability (CVE-2021-44228). The rule specifically monitors for JNDI lookups over ldap, rmi, or dns protocols within HTTP traffic, which can lead to remote code execution.
Detects attempts to exploit the Log4Shell vulnerability (CVE-2021-44228) by monitoring HTTP headers for JNDI lookup strings. The rule inspects traffic for malicious patterns like '${jndi:ldap://', '${jndi:rmi://', or '${jndi:dns://', which are used to trigger remote code execution in vulnerable Java applications.
Detects attempts to exploit Microsoft Exchange vulnerabilities (CVE-2021-34473, CVE-2021-34523, CVE-2021-31207), collectively known as ProxyShell. The rule monitors inbound HTTP requests targeting the /autodiscover/ endpoint with specific path traversal patterns and malicious components used to stage web shells or execute arbitrary commands.
This rule detects potentially malicious activity leveraging the Windows Remote Management (WinRM) protocol over HTTP (ports 5985/5986). It specifically monitors for POST requests to the '/wsman' URI that contain the string 'powershell' in the request body, which is indicative of remote command execution via WinRM using PowerShell.
This rule detects HTTP requests attempting to perform Local File Inclusion (LFI) or path traversal attacks by searching for patterns such as '/../' sequences and common sensitive file paths like /etc/passwd, /etc/shadow, or /proc/self/environ in the URI.
Detects outbound HTTP POST requests to suspicious URIs and subsequent inbound responses containing executable binary (PE) signatures, characteristic of Emotet malware command-and-control (C2) activity.
Detects HTTP traffic patterns characteristic of Emotet malware command and control (C2) beaconing, specifically looking for POST requests with random alphanumeric URIs (4-16 characters) and a specific Accept-Encoding header (gzip, deflate).
This rule detects potential Cobalt Strike Beacon check-in activity over HTTP. It identifies incoming GET requests where the URI is abnormally short and the HTTP Referer header is missing, which are common indicators of default Cobalt Strike malleable C2 profiles.
This rule detects HTTP responses that return an Android Package (APK) file (application/vnd.android.package-archive) to a client. This is indicative of potential mobile malware delivery or unauthorized application distribution.
This rule detects outgoing HTTP POST requests containing patterns commonly associated with Emotet command-and-control (C2) communication, specifically identifying the use of an application/octet-stream content type combined with a specific, randomized URI path structure consisting of alphanumeric segments.
Detects outbound network traffic from internal hosts exhibiting characteristics of PowerShell-based download cradles, such as specific User-Agent strings or URL patterns associated with IEX DownloadString or Invoke-WebRequest.
Detects HTTP traffic patterns consistent with data exfiltration to major cloud storage providers (AWS S3, Azure Blob Storage, Google Cloud Storage) using common command-line interface tools like rclone, aws-cli, and AzCopy.
This rule detects attempts to extract credentials from FortiGate devices by targeting specific management API endpoints. It looks for HTTP GET requests to '/api/v2/cmdb/' followed by paths like 'system/admin', 'vpn.ssl.settings', or 'user/local', which are known to contain sensitive configuration or user data. This activity is associated with the 'FortiBleed' campaign and CVE-2026-24858.
Detects network activity initiated by the TukTuk malware to communicate with Arweave public gateways (arweave.net and g8way.io), which are utilized as dead-drop resolvers for C2 infrastructure resolution.
This rule detects the use of the 'msiexec.exe' utility to fetch and potentially execute an '.msi' installer package directly from a remote source via HTTP. This behavior is a known technique for bypassing application control by abusing a signed system binary to download and install malicious packages.
Detects HTTP traffic containing a specific session cookie pattern characteristic of PowerShell Empire C2 agent communication, utilizing regex to identify base64-encoded session identifiers.
Detects outbound HTTP POST requests to external networks that match a known Emotet C2 traffic pattern. The rule specifically looks for HTTP POST requests using an 'application/x-www-form-urlencoded' Content-Type and a URI structure consisting of randomized alphanumeric segments (4-20 characters long). This structure is characteristic of Emotet's communication with its command-and-control infrastructure.
Page 62 of 116