Detections

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

2,831 detections

Detects anomalous non-interactive sign-ins that bypass multi-factor authentication (MFA) requirements from a geographical location not previously seen in the user's historical sign-in baseline. This pattern is indicative of attackers using stolen OAuth access or refresh tokens to maintain persistence and bypass standard authentication controls.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
000
Detects anomalous non-interactive sign-ins that bypass multi-factor authentication (MFA) requirements from a geographical location not previously seen in the user's historical sign-in baseline. This pattern is indicative of attackers using stolen OAuth access or refresh tokens to maintain persistence and bypass standard authentication controls.
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Arnold Chan@slaz
Defender - KQL
1 month ago
000
Detects anomalous administrative activity within Microsoft Exchange by identifying accounts performing multiple suspicious operations within a short timeframe. This rule flags activities like modifying transport rules, virtual directories, or management role assignments, which are often indicative of malicious persistence or configuration tampering, while excluding known authorized service accounts.
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Arnold Chan@slaz
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Hunters
1 month ago
000
Detects anomalous administrative activity within Microsoft Exchange by identifying accounts performing multiple suspicious operations within a short timeframe. This rule flags activities like modifying transport rules, virtual directories, or management role assignments, which are often indicative of malicious persistence or configuration tampering, while excluding known authorized service accounts.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
000
Detects anomalous, high-frequency access to sensitive Microsoft Graph API endpoints by a single service principal or user identity. The rule flags identities that interact with five or more distinct categories of sensitive resources (e.g., users, groups, applications, sites) within a 30-minute window, suggesting automated reconnaissance or environment discovery.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
102
This rule detects when a user account updates their MFA information in Azure AD or Microsoft 365, resulting in an increase in the number of associated MFA devices. This is a common indicator of an attacker registering a new MFA device (such as a hardware token or phone app) to a compromised account to establish persistence or bypass existing MFA requirements.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
000
Detects high-frequency requests to various Microsoft Graph API endpoints, such as users, groups, applications, and mailboxes, within a short timeframe. This behavior is indicative of an adversary attempting to map out a target's cloud identity infrastructure and environment, often as a precursor to more focused attacks like phishing, data exfiltration, or lateral movement within M365.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
000
Detects a single identity, application, or IP address performing Graph API requests across multiple disparate categories (e.g., tenant, directory, privilege, application, repository, mailbox) within a short window. This pattern is indicative of automated reconnaissance or tenant enumeration, commonly performed during the post-compromise phase to map the environment prior to exfiltration.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
000
Detects high-volume access to Exchange Online mailboxes by a single user from a single IP address using the 'One Outlook Web' application ID, potentially indicating unauthorized automated mailbox data exfiltration.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
000
This rule detects OAuth authorization requests (targeting Microsoft or Google identity providers) that use 'prompt=none' (silent authentication) and redirect the user to an unexpected or untrusted domain. This pattern is commonly used in OAuth consent phishing or token theft attacks, where an attacker attempts to silently acquire an authorization code by redirecting it to a malicious application server instead of the legitimate service provider's domain.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
506
Detects anomalous GitLab project enumeration where an account performs an excessive number of requests to the Projects API using the 'membership=true' parameter within a one-hour window. This behavior is indicative of an attacker attempting to discover all accessible repositories associated with a compromised or over-privileged GitLab token.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
002
Detects anomalous GitLab project enumeration where an account performs an excessive number of requests to the Projects API using the 'membership=true' parameter within a one-hour window. This behavior is indicative of an attacker attempting to discover all accessible repositories associated with a compromised or over-privileged GitLab token.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
002
Detects anomalous GitLab project enumeration where an account performs an excessive number of requests to the Projects API using the 'membership=true' parameter within a one-hour window. This behavior is indicative of an attacker attempting to discover all accessible repositories associated with a compromised or over-privileged GitLab token.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
002
Detects unreviewed commits to .gitlab-ci.yml that alter how the gitlab-triage tool invokes the sensitive API_TOKEN variable, with no associated merge request.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
002
Detects a GitLab personal access token/response indicating Owner-level (access_level 50) group access combined with the broad 'api' scope on the sensitive gnutls/gnutls project -- the excessive standing-privilege pattern that turned one leaked token into a 55-project exposure.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
002
Detects a GitLab personal access token/response indicating Owner-level (access_level 50) group access combined with the broad 'api' scope on the sensitive gnutls/gnutls project -- the excessive standing-privilege pattern that turned one leaked token into a 55-project exposure.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
002
Detects a GitLab personal access token/response indicating Owner-level (access_level 50) group access combined with the broad 'api' scope on the sensitive gnutls/gnutls project -- the excessive standing-privilege pattern that turned one leaked token into a 55-project exposure.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
002
Detects instances where a specific user creates or deletes a Microsoft Power Automate flow that has active sharing permissions configured, potentially indicating unauthorized workflow manipulation or persistence attempts.
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Shadows VMB@Vemorian_Mort
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Detections.ai Community
2 months ago
2052
Detects a single GitLab token/account holding Owner-level access across an unusually large number of projects (50+), the standing-privilege condition that turned one leaked token into a 55-project supply-chain exposure.
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Arnold Chan@slaz
Defender - KQL
2 months ago
002
This rule monitors for Exchange administration operations where mailbox permissions ('FullAccess', 'SendAs', or 'SendOnBehalf') are granted to a user. It specifically flags instances where the account performing the action is neither the owner of the target mailbox nor the grantee, identifying suspicious, potentially unauthorized delegation patterns.
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Ali AlEnezi@site
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Detections.ai Community
1 month ago
000
This rule monitors for successful sign-ins to sensitive cloud resources (such as Microsoft Authentication Broker, Office 365 Exchange Online, or Graph API) that originate from IP addresses not observed in the user's recent history (14-day baseline) or from known datacenter/hosting network ranges. The rule also filters for common scripted User-Agent strings (e.g., Python requests, curl) or empty User-Agent strings to increase the likelihood of detecting programmatic or malicious automated access rather than standard browser-based user activity.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
11016
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