Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

1,153 detections

Detects ListPlanting injection using LVM_SORTITEMS and SendMessage API
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Darshan Thummar@Mighty
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Detections.ai Community
4 months ago
001
Detects DLL injection using LoadLibraryA/W API calls
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
002
This rule detects suspicious process creations where common system processes (svchost.exe, explorer.exe, lsass.exe, winlogon.exe) act as parent processes for scripting or command-line interpreters (powershell.exe, cmd.exe, cscript.exe, wscript.exe) and the child process runs with a low or untrusted integrity level. This pattern can indicate process injection or other forms of malicious execution where an attacker attempts to hide their activity by masquerading as legitimate system processes.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
104
Detects calls to NtAllocateVirtualMemory originating from scripting engines or binaries executing from temporary user-controlled locations. This behavior is commonly associated with reflective loading, shellcode execution, and in-memory malware.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
003
This rule detects suspicious process creations where common system processes (svchost.exe, explorer.exe, lsass.exe, winlogon.exe) act as parent processes for scripting or command-line interpreters (powershell.exe, cmd.exe, cscript.exe, wscript.exe) and the child process runs with a low or untrusted integrity level. This pattern can indicate process injection or other forms of malicious execution where an attacker attempts to hide their activity by masquerading as legitimate system processes.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
003
Detects calls to NtAllocateVirtualMemory originating from scripting engines or binaries executing from temporary user-controlled locations. This behavior is commonly associated with reflective loading, shellcode execution, and in-memory malware.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
104
This rule detects C2 beaconing activity originating from a potentially injected process. It specifically looks for HTTP traffic where the User-Agent header matches a common Windows Mozilla/5.0 pattern, indicating a Windows client, and the data size is between 1 and 199 bytes. A threshold of 20 such events within 60 seconds from the same source IP triggers the alert, suggesting a beaconing behavior.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
003
This rule detects the delivery of a process injection toolkit over HTTP by looking for the presence of specific Windows API function names, 'VirtualAllocEx' and 'WriteProcessMemory', within the HTTP response body. These functions are commonly used in process injection techniques to allocate memory in a remote process and write malicious code into it.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
003
Detects suspicious process injection attempts where common scripting/proxy execution tools (wscript.exe, cscript.exe, mshta.exe, powershell.exe, msiexec.exe) are used to inject into other processes (RegAsm.exe, InstallUtil.exe, vbc.exe, svchost.exe, explorer.exe) using CreateRemoteThread. The detection is further refined by looking for command-line indicators often associated with malicious activity, such as downloading content or executing scripts.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
002
This rule detects suspicious DLL injection activity by identifying multiple DLL loads from unusual folders such as 'Temp', 'AppData', or 'Windows\Temp'. Adversaries often drop malicious DLLs into these directories and then inject them into legitimate processes to achieve persistence, privilege escalation, or defense evasion. The rule counts the number of DLL loads from these suspicious locations by the same initiating process on the same device, triggering an alert if five or more such loads occur, indicating a concerted malicious effort.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
002
This detection identifies suspicious execution of update.exe processes launched by svchost.exe from user-writable directories such as AppData, Temp, Downloads, and Public folders.

This behavior is associated with malware techniques observed in the MiniFast campaign, where attackers use fake updater binaries and service-based execution chains to evade detection and maintain persistence.

The rule helps detect:

Malicious or fake update.exe execution
Abnormal parent-child process relationship (svchost.exe → update.exe)
Execution from non-standard user directories
Potential malware staging and execution behavior

This detection is intended to identify early-stage malware execution and suspicious process behavior linked to threat actor techniques described in recent threat intelligence reports.
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Kumaresan Selladurai@KumaresanSelladurai
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Detections.ai Community
5 months ago
120168
This rule detects potential process injection shellcode payloads within HTTP responses. It specifically looks for the presence of the strings "OpenProcess" and "CreateRemoteThread" (case-insensitive) in the file data of HTTP responses flowing from the server to the client. These API calls are commonly used in process injection techniques to gain control over another process and execute malicious code.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
002
Detects rundll32.exe or dllhost.exe performing remote thread injection into web browser processes (chrome.exe, msedge.exe, firefox.exe). This activity is often associated with defense evasion and credential theft staging, as observed in campaigns like ClearFake/ClickFix, before a full Remote Access Trojan (RAT) is established.
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Ethan Andrews@eandrews
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Federal Signal Detections
5 months ago
220142
his detection identifies suspicious execution of update.exe processes launched by svchost.exe from user-writable directories such as AppData, Temp, Downloads, and Public folders.

This behavior is associated with malware techniques observed in the MiniFast campaign, where attackers use fake updater binaries and service-based execution chains to evade detection and maintain persistence.

The rule helps detect:

Malicious or fake update.exe execution
Abnormal parent-child process relationship (svchost.exe → update.exe)
Execution from non-standard user directories
Potential malware staging and execution behavior

This detection is intended to identify early-stage malware execution and suspicious process behavior linked to threat actor techniques described in recent threat intelligence reports.
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Kumaresan Selladurai@KumaresanSelladurai
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Detections.ai Community
5 months ago
20142
Detects the creation of the specific named pipe '\REDSUN' used by the RedSun exploit (CVE-2026-41091) for inter-process communication. This named pipe is a unique indicator of the RedSun exploit's activity, often associated with process injection or other inter-process communication mechanisms.
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Tim Peck@timpeck
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Detections.ai Community
5 months ago
2013
Detects a hidden PowerShell process dynamically loading the Windows Forms assembly to inject base64-encoded keystrokes into foreground applications. This behavior is associated with the SStar Agent RAT's remote 'type' functionality.
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Ethan Andrews@eandrews
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Federal Signal Detections
5 months ago
507
Detects the creation of the '\REDSUN' named pipe, which is used by the CVE-2026-41091 exploit for inter-process communication. This pipe facilitates the transfer of session ID information between the user-level exploit and the SYSTEM-level payload.
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Bryant Smith@flowstate
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Detections.ai Community
5 months ago
2010
This rule detects the loading of modules (DLLs or executables) from user-specific AppData folders that are not commonly observed across the environment. It specifically excludes common legitimate paths within AppData like 'Local\Programs' and 'Local\Temp' to reduce false positives. The rule identifies modules loaded by processes that also originate from an AppData folder, indicating potentially suspicious activity such as malware or custom tools operating from user-writable locations.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
000
This rule detects suspicious DLL injection activity by identifying multiple DLL loads from unusual folders such as 'Temp', 'AppData', or 'Windows\Temp'. Adversaries often drop malicious DLLs into these directories and then inject them into legitimate processes to achieve persistence, privilege escalation, or defense evasion. The rule counts the number of DLL loads from these suspicious locations by the same initiating process on the same device, triggering an alert if five or more such loads occur, indicating a concerted malicious effort.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
000
This rule detects the loading of modules (DLLs or executables) from user-specific AppData folders that are not commonly observed across the environment. It specifically excludes common legitimate paths within AppData like 'Local\Programs' and 'Local\Temp' to reduce false positives. The rule identifies modules loaded by processes that also originate from an AppData folder, indicating potentially suspicious activity such as malware or custom tools operating from user-writable locations.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
103
Detects network connections originating from the systeminfo.exe process. This activity is suspicious because systeminfo.exe is a legitimate system enumeration tool not typically expected to initiate outbound network connections. This behavior has been observed in malware campaigns, such as CountLoader, which injects a cryptocurrency clipper into systeminfo.exe to communicate with C2 servers and the Ethereum blockchain.
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Tim Peck@timpeck
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Detections.ai Community
5 months ago
20151
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