Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
2,982 detections
Filters
Last updated
All Time
Detection languages
1,486
513
403
239
167
Contributors
986
658
304
198
109
Categories
916
822
673
590
452
Platforms
39,936
7,266
6,537
3,866
3,647
2,982
Products / Services
1,229
703
443
309
200
MITRE Techniques
1,053
824
459
384
348
CVEs
17
16
16
10
10
IDS Classtypes
24
7
7
4
3
IDS Protocols
49
1
Detects inbound emails impersonating IT support or helpdesk staff that utilize urgent pretexts related to passkey, MFA, or SSO updates. These lures are commonly used in phishing campaigns to direct users toward malicious authentication flows, such as AiTM or device-code phishing setups.
Detects high-volume, automated file download or access activity originating from SharePoint Online, OneDrive, or Exchange Online within a 2-hour window. The rule identifies suspicious patterns involving a large number of distinct file events, potentially indicating automated scripts or tools (like python-httpx) performing mass data collection or exfiltration.
Detects high-volume, automated file download or access activity originating from SharePoint Online, OneDrive, or Exchange Online within a 2-hour window. The rule identifies suspicious patterns involving a large number of distinct file events, potentially indicating automated scripts or tools (like python-httpx) performing mass data collection or exfiltration.
Detects a single user account sending an unusually high volume of Microsoft Teams messages containing themes related to passkey, SSO enrollment, or security updates. This behavior is indicative of a compromised internal account being leveraged to propagate social engineering lures to other employees.
Detects a suspicious sign-in sequence indicative of an Adversary-in-the-Middle (AiTM) phishing attack. The rule identifies a user attempting to sign in from an unmanaged device (triggered by Azure AD error 50074, requiring secondary authentication) followed shortly by an interruption in session persistence (triggered by error 50140) while using a browser user agent, suggesting the session is being relayed through a malicious proxy.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
Detects anomalous, high-frequency access to multiple distinct Microsoft Graph API endpoints (e.g., users, groups, applications) by a single user within a short timeframe, which is indicative of tenant-wide reconnaissance following identity compromise.
Detects a suspicious pattern where a user registers a new PhoneAppOTP MFA method and subsequently logs in using this method after a significant time delay (exceeding 3 days). This behavior is indicative of an attacker who has gained temporary access, registered their own MFA device to ensure persistent future access, and returned later to utilize it.
Detects a suspicious pattern where a user registers a new PhoneAppOTP MFA method and subsequently logs in using this method after a significant time delay (exceeding 3 days). This behavior is indicative of an attacker who has gained temporary access, registered their own MFA device to ensure persistent future access, and returned later to utilize it.
This rule detects successful sign-in activity to the 'My Sign-Ins' application where the device is not marked as trusted or the sign-in carries a non-zero risk level. This behavior may indicate an adversary attempting to gain access to account security settings or sensitive portal information using compromised or unmanaged devices.
Detects anomalous sign-in behavior following a successful device code authentication. The rule identifies instances where a successful device code login is immediately followed by a sign-in session using a different IP address or device name for the same account, indicating potential session theft or adversary-in-the-middle phishing activity.
Detects anomalous, high-volume file access or download activity in Microsoft SharePoint Online or OneDrive for Business originating from a 'python-httpx' user agent. This pattern often indicates automated data collection or exfiltration attempts using programmatic tools.
Detects anomalous, low-volume data access behavior within cloud applications (such as file downloads, previews, or mail access) that is sustained over an extended period. This pattern often indicates slow, deliberate data exfiltration designed to evade volume-based detection thresholds.
Detects incoming HTTP requests attempting to exploit a path traversal vulnerability in the GitLab Commits API (CVE-2026-85706). The rule looks for URI patterns containing directory traversal sequences (e.g., ../) targeting the repository commits endpoint.
Detects unauthenticated path traversal attempts targeting the GitLab repository commits API, specifically checking for URL-encoded and plain path traversal patterns (e.g., '../') in requests to the commits endpoint. This behavior is indicative of attempts to exploit vulnerabilities like CVE-2026-85706 to read arbitrary files outside the repository scope.
Detects a suspicious sequence of events where a user initiates a device code authorization flow, immediately followed by a Microsoft Authentication Broker sign-in using the 'sso_reload=true' parameter. This pattern is indicative of an attacker hijacking the device code authorization process to gain unauthorized access to a user's session.
This rule performs a wide aggregation of logs across proxy, cloud, GitHub, and network destination data sources. Because it lacks specific filtering logic or behavioral indicators, it does not detect any specific attack technique and serves only as a broad data collection query.
This rule detects instances where a user account performs a password update without any preceding or associated account verification events (such as email verification, reset requests, or action execution) within a short timeframe. This behavior can be indicative of account compromise where an adversary modifies credentials for a compromised user account.
Detects instances where unauthenticated users or sessions execute privileged 'tools/call' operations within the Grafana MCP dispatcher. This behavior is indicative of potential session spoofing attacks, specifically targeting vulnerabilities similar to CVE-2026-19516, where lack of an Authorization header allows unauthorized access to privileged tool functions.
Detects instances where a single proxy service API key or account is used from an abnormally high number of distinct IP addresses within a short timeframe. This behavior is indicative of credential theft and unauthorized sharing or exploitation of proxy credentials by third-party actors.
Detects instances where a single proxy service API key or account is used from an abnormally high number of distinct IP addresses within a short timeframe. This behavior is indicative of credential theft and unauthorized sharing or exploitation of proxy credentials by third-party actors.
Page 62 of 142