Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,235 detections
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Detects anomalous remote interactive or network logons where the specific account and remote host/IP combination has not been observed in the previous 14 days. The rule correlates these new login events with subsequent process execution on the destination host within a short window (5 minutes) to identify potential lateral movement where an adversary uses valid credentials to log in and immediately execute commands.
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.
Detects a suspicious sequence of events where a user's password is changed or reset by an administrator (or help-desk role) followed within a short time window by that same user registering a new MFA device, potentially indicating a vishing-based account takeover attack (e.g., PREY-0058/UNC6671).
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
Detects instances where the Grafana MCP (Model Context Protocol) server's service account identity executes administrative tools (such as 'grafana_api_request') within a session that lacks a verified, prior authentication event (bearer token). This pattern suggests an adversary may be spoofing or hijacking a privileged service account session to perform unauthorized administrative actions.
Detects instances where the Grafana MCP (Model Context Protocol) server's service account identity executes administrative tools (such as 'grafana_api_request') within a session that lacks a verified, prior authentication event (bearer token). This pattern suggests an adversary may be spoofing or hijacking a privileged service account session to perform unauthorized administrative actions.
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
Detects anomalous remote interactive or network logons where the specific account and remote host/IP combination has not been observed in the previous 14 days. The rule correlates these new login events with subsequent process execution on the destination host within a short window (5 minutes) to identify potential lateral movement where an adversary uses valid credentials to log in and immediately execute commands.
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.
Detects anomalous authentication attempts where a single source IP validates a high volume of distinct Service Principal or App Client IDs within a short timeframe with a high failure rate. This pattern is indicative of attackers performing bulk validation of stolen API keys or OAuth credentials, likely harvested through mobile application decompilation (APK/IPA analysis).
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects sessions using shared Grafana service account tokens that perform both read-only and action-capable tool operations without confirmed prior authentication. This behavior is indicative of an unauthenticated or spoofed session leveraging a service account's excessive permissions, bypassing standard authentication flows.
Detects instances where the Grafana MCP (Model Context Protocol) server's service account identity executes administrative tools (such as 'grafana_api_request') within a session that lacks a verified, prior authentication event (bearer token). This pattern suggests an adversary may be spoofing or hijacking a privileged service account session to perform unauthorized administrative actions.
Detects anomalous authentication attempts where a single source IP validates a high volume of distinct Service Principal or App Client IDs within a short timeframe with a high failure rate. This pattern is indicative of attackers performing bulk validation of stolen API keys or OAuth credentials, likely harvested through mobile application decompilation (APK/IPA analysis).
Detects anomalous remote interactive or network logons where the specific account and remote host/IP combination has not been observed in the previous 14 days. The rule correlates these new login events with subsequent process execution on the destination host within a short window (5 minutes) to identify potential lateral movement where an adversary uses valid credentials to log in and immediately execute commands.
Detects anomalous remote interactive or network logons where the specific account and remote host/IP combination has not been observed in the previous 14 days. The rule correlates these new login events with subsequent process execution on the destination host within a short window (5 minutes) to identify potential lateral movement where an adversary uses valid credentials to log in and immediately execute commands.
Detects an Owner-role GitLab account or token modifying merge-request approval rules, protected-branch settings, or project membership -- controls that, if weakened, defeat code-review safeguards.
Detects an Owner-role GitLab account or token modifying merge-request approval rules, protected-branch settings, or project membership -- controls that, if weakened, defeat code-review safeguards.
Detects an Owner-role GitLab account or token modifying merge-request approval rules, protected-branch settings, or project membership -- controls that, if weakened, defeat code-review safeguards.
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.
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
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