Detections

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

361 detections

Detects anomalous activity by newly added guest users in Microsoft Teams, specifically identifying when a guest user account is added and subsequently performs multiple file-related operations (upload, download, access) or message-sending activities within a short timeframe. This behavior can be indicative of external threat actors or compromised guest accounts exfiltrating or accessing sensitive information within a Teams workspace.
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Ali AlEnezi@site
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Detections.ai Community
1 month ago
000
This rule monitors Office 365 SharePoint file operations and search queries for patterns indicative of automated discovery and exfiltration of sensitive content. It specifically identifies high-frequency search queries involving wildcard parameters used in SharePoint content indexing, which may suggest an adversary is systematically crawling or enumerating organizational documents.
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Ankit Mehta@Secvyn
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SlimKQL
2 months ago
102
Detects anomalous data access or collection activity across multiple M365 workloads (SharePoint, OneDrive, Exchange). The rule identifies users exhibiting high volumes of file or mail access across at least two distinct workloads within a one-hour window, which may indicate account compromise, bulk data exfiltration, or unauthorized persistence via mailbox rules.
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Arnold Chan@slaz
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Hunters
2 months ago
101
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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Arnold Chan@slaz
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Hunters
2 months ago
001
Detects anomalous access to Microsoft 365 services (OneDrive, SharePoint, Mail) where the user activity is characterized by a high volume of operations (more than 30) across a diverse set of objects (more than 15) within a one-hour window. The detection focuses on activity originating from specific common automation/scripting User-Agents (Microsoft Graph, Python httpx/requests) that deviate from typical, focused service account behavior.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
104
This rule detects suspicious, high-volume file access or download operations in SharePoint and OneDrive. It filters for activities performed by specific user agents commonly associated with automated scripting tools (e.g., python-requests, Microsoft.Graph.Client), which indicates potential automated exfiltration or unauthorized bulk data collection.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
004
Detects automated directory fuzzing attempts against Azure Storage blobs targeting sensitive files like .env, .pem, or configuration files. The rule identifies suspicious activity by aggregating requests from Anonymous or SAS-authenticated sources that exhibit high request volumes and access to multiple distinct sensitive paths, while excluding known legitimate bulk-transfer and synchronization tools.
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Arnold Chan@slaz
Defender - KQL
2 months ago
001
Detects anomalous, large-scale cloning or mirroring of code repositories combined with targeted access to infrastructure-as-code configuration files (e.g., .tfvars, .tfstate) or automated exfiltration of CI/CD build artifacts. This behavior is indicative of an adversary attempting to exfiltrate proprietary source code or sensitive secrets stored within repositories.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
001
Detects anomalous, large-scale cloning or mirroring of code repositories combined with targeted access to infrastructure-as-code configuration files (e.g., .tfvars, .tfstate) or automated exfiltration of CI/CD build artifacts. This behavior is indicative of an adversary attempting to exfiltrate proprietary source code or sensitive secrets stored within repositories.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
001
This rule monitors Office 365 SharePoint file operations and search queries for patterns indicative of automated discovery and exfiltration of sensitive content. It specifically identifies high-frequency search queries involving wildcard parameters used in SharePoint content indexing, which may suggest an adversary is systematically crawling or enumerating organizational documents.
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Ankit Mehta@Secvyn
Defender - KQL
2 months ago
001
Detects a user performing a high volume of SharePoint site discovery queries within a one-hour window. This behavior often indicates an adversary attempting to map site structures and discover content across an organization's SharePoint environment.
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Ankit Mehta@Secvyn
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SlimKQL
2 months ago
001
Detects anomalous user behavior where a file search query is followed by a high volume of file downloads within a short period (30 minutes) from the same IP address. This behavior is indicative of an attacker searching for sensitive documents and performing bulk extraction or exfiltration.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
001
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
002
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
002
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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Arnold Chan@slaz
Defender - KQL
2 months ago
002
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
102
This rule monitors Office 365 activity for anomalous search behavior, specifically targeting high volumes of distinct search queries involving site collections, web structures, or index ID patterns. Such patterns are indicative of automated data discovery or enumeration activities performed against SharePoint or OneDrive environments.
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Arnold Chan@slaz
Defender - KQL
2 months ago
002
This rule monitors Office 365 activity for anomalous search behavior, specifically targeting high volumes of distinct search queries involving site collections, web structures, or index ID patterns. Such patterns are indicative of automated data discovery or enumeration activities performed against SharePoint or OneDrive environments.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
002
This rule monitors Office 365 activity for anomalous search behavior, specifically targeting high volumes of distinct search queries involving site collections, web structures, or index ID patterns. Such patterns are indicative of automated data discovery or enumeration activities performed against SharePoint or OneDrive environments.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
002
Detects anomalous access to Microsoft 365 services (OneDrive, SharePoint, Mail) where the user activity is characterized by a high volume of operations (more than 30) across a diverse set of objects (more than 15) within a one-hour window. The detection focuses on activity originating from specific common automation/scripting User-Agents (Microsoft Graph, Python httpx/requests) that deviate from typical, focused service account behavior.
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Arnold Chan@slaz
Defender - KQL
2 months ago
002
Detects anomalous access to Microsoft 365 services (OneDrive, SharePoint, Mail) where the user activity is characterized by a high volume of operations (more than 30) across a diverse set of objects (more than 15) within a one-hour window. The detection focuses on activity originating from specific common automation/scripting User-Agents (Microsoft Graph, Python httpx/requests) that deviate from typical, focused service account behavior.
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Arnold Chan@slaz
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Hunters
2 months ago
000
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