Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
40,063 detections
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Detects the Comet browser process, typically associated with AI-agent operations, accessing sensitive browser profile files (e.g., History, Bookmarks, Login Data, Cookies) followed by outbound network communication within a 15-minute window, excluding known legitimate paths.
Detects the Comet browser process, typically associated with AI-agent operations, accessing sensitive browser profile files (e.g., History, Bookmarks, Login Data, Cookies) followed by outbound network communication within a 15-minute window, excluding known legitimate paths.
This rule detects potential exploitation attempts targeting VLC media player, specifically focusing on the CVE-2026-56711 integer overflow vulnerability. The rule identifies instances where VLC processes a PNG file originating from untrusted locations (such as Downloads, Temp, or removable media) shortly after that file was created or modified on the host.
Detects the execution of Microsoft Teams client processes on endpoints associated with user accounts that have already been flagged as compromised via authentication anomalies. This rule acts as a pivot and investigation tool for tracking potentially malicious activity within Teams on impacted hosts.
This rule monitors network traffic and internal logs for connections to known malicious IP addresses or domain names associated with 'ClickFix' social engineering campaigns (often impersonating services like HBO Max). The logic explicitly filters out known threat intelligence scanners and security researcher probes. It performs correlation by requiring domain/message matches for generic IP-based alerts to reduce noise, and aggregates events per host over 15-minute windows to produce consolidated alerts.
Detects network communication with domains and IP addresses known to be associated with 'ClickFix' social engineering campaigns (specifically those masquerading as legitimate HBO Max or macOS related updates). The rule applies a strict correlation between observed malicious IP traffic and specific DNS requests to reduce noise from IP address reuse or threat intelligence feed probes, while also excluding known security-related processes.
Detects the use of PowerShell's 'WriteAllBytes' method to write a file to the user's Local AppData Temp directory, immediately followed by the creation of a known or suspicious executable file in that same location. This pattern is commonly indicative of a stage in a fileless-style malware attack or automated payload delivery.
This rule detects potentially malicious child processes spawned by processes associated with Microsoft Semantic Kernel agents. These agents may be exploited to execute administrative tools, living-off-the-land binaries (LOLBins), or networking utilities commonly used in post-exploitation activities, such as credential dumping, discovery, or command execution.
Detects outbound network connections from internal devices to public IP addresses over standard MQTT (1883) or MQTT over TLS (8883) ports. MQTT is frequently used for IoT communication but can be abused for command and control (C2) or unauthorized data exfiltration.
Detects the creation of a scheduled task containing the string 'Google Chrome Update' in the command line, where the task is not the legitimate 'GoogleUpdateTaskMachine' task. The rule specifically targets tasks that execute PowerShell or arbitrary executables, which is a common persistence technique used by adversaries to mask malicious tasks as legitimate software updates.
Detects suspicious PE files that masquerade as Mozilla Firefox by using Firefox-related product names and metadata, but lack valid Mozilla Corporation code-signing signatures and are located within the ProgramData directory.
Detects the execution of PowerShell commands initiated from a .lnk file that query system information related to virtualization technologies (e.g., VMware, VirtualBox, Hyper-V) or hardware details (e.g., BIOS, VideoController). This pattern is often used for environmental awareness or anti-sandbox/anti-analysis techniques by malware.
This rule detects non-browser processes attempting to access sensitive web browser credential files, such as 'Login Data', 'logins.json', and 'key4.db'. Such activity is highly characteristic of credential-stealing malware (including BabylonRAT) attempting to exfiltrate stored passwords or session data from Google Chrome or Mozilla Firefox profiles.
This rule monitors for indicators of compromise (IOCs) associated with the Rapuncel/Cruciferra 'Bring Your Own Vulnerable Driver' (BYOVD) malware-as-a-service (MaaS) campaign. It detects malicious file hashes (associated with dropped binaries or drivers), connections to known malicious command-and-control (C2) IP addresses, and network requests to domains used by the infrastructure.
This rule monitors for indicators of compromise (IOCs) associated with the Rapuncel/Cruciferra 'Bring Your Own Vulnerable Driver' (BYOVD) malware-as-a-service (MaaS) campaign. It detects malicious file hashes (associated with dropped binaries or drivers), connections to known malicious command-and-control (C2) IP addresses, and network requests to domains used by the infrastructure.
This rule monitors for indicators of compromise (IOCs) associated with the Rapuncel/Cruciferra 'Bring Your Own Vulnerable Driver' (BYOVD) malware-as-a-service (MaaS) campaign. It detects malicious file hashes (associated with dropped binaries or drivers), connections to known malicious command-and-control (C2) IP addresses, and network requests to domains used by the infrastructure.
Detects the execution of PowerShell with common obfuscation or stealth-related flags (e.g., -enc, -nop, -w hidden) when initiated by CMD or from a LNK file, particularly when originating from Windows Explorer. This is a common pattern for malicious file execution and dropper activity.
CloudSEK researchers uncovered BigBear 2.0, a global Microsoft 365 phishing-as-a-service operation targeting hundreds of organizations across 40+ countries. The investigation exposed the attacker’s admin panel, affiliate network, phishing infrastructure, and thousands of stolen credentials and session cookies, revealing how modern AiTM attacks can hijack authenticated sessions even after MFA.
Detects the creation of a Volume Shadow Copy followed by an attempt to access or copy the Active Directory database file (ntds.dit) from the shadow copy. This pattern is commonly used by adversaries to perform offline credential dumping.
This rule detects modifications to the security descriptors (ACLs) of sensitive Active Directory objects, specifically targeting additions of powerful rights like GenericAll, GenericWrite, WriteDacl, or ForceChangePassword. Monitoring these changes on privileged objects such as Domain Admins, Enterprise Admins, and Domain Controllers is critical for detecting potential privilege escalation or persistence efforts.
Detects instances where PowerShell.exe acts as a parent process or initiator for potentially suspicious process injections into common host processes including csc.exe, chrome.exe, msedge.exe, or SearchIndexer.exe. This activity is often associated with code execution or persistence mechanisms where PowerShell injects malicious logic into other processes.
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