Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects high-volume file download or data access events across SharePoint, OneDrive, and Exchange Online. This rule monitors for requests from Python-based HTTP libraries (httpx, requests, urllib) targeting Microsoft Graph API endpoints, which is a pattern indicative of automated bulk data collection or exfiltration, often observed in campaigns like Storm-3121 or Storm-3032.
Detects user authentication events that exhibit patterns consistent with Adversary-in-the-Middle (AiTM) phishing campaigns, specifically those leveraging passkey or SSO-themed lures and device-code authentication flows.
Detects a sequence of user activities—authentication, MFA registration, Graph API reconnaissance, and data exfiltration—originating from a rotating set of distinct source IP addresses for the same user within a 24-hour period. This behavior is indicative of coordinated infrastructure rotation tactics used by threat actors in cloud intrusions.
Detects anomalous usage of the OAuth 2.0 Device Authorization Grant flow (Device Code Flow). This flow is frequently abused by attackers to bypass MFA by tricking users into authenticating an attacker-controlled device or session, potentially leading to token theft or unauthorized access to sensitive enterprise applications.
Detects internal Microsoft Teams messages containing lures related to passkey or SSO enrollment, which is indicative of a compromised account attempting to perform lateral phishing to harvest credentials or bypass multi-factor authentication.
Detects Microsoft Teams chat and message events originating from unverified or external tenants that attempt to impersonate internal IT helpdesk personas. This activity is often part of a multi-stage social engineering campaign, potentially following email bombing, where attackers aim to trick users into executing malicious files or installing remote access tools.
Detects instances of OAuth device code flow authentication from suspicious sources (e.g., unfamiliar devices, non-compliant/unmanaged devices, or unusual geographic locations) that are followed closely by an OAuth application consent event. This behavior is indicative of potential consent phishing or device code phishing attacks attempting to gain persistent access to cloud resources.
Detects anomalous, high-frequency access to LinkedIn 'about' pages, which may indicate reconnaissance activity or attempts to gather sensitive organizational information by an adversary. The rule uses threshold-based aggregation to filter out standard search engine crawlers and identify potentially malicious scanning behavior.
Detects anomalous, high-frequency access to LinkedIn 'about' pages, which may indicate reconnaissance activity or attempts to gather sensitive organizational information by an adversary. The rule uses threshold-based aggregation to filter out standard search engine crawlers and identify potentially malicious scanning behavior.
Detects anomalous, high-frequency access to LinkedIn 'about' pages, which may indicate reconnaissance activity or attempts to gather sensitive organizational information by an adversary. The rule uses threshold-based aggregation to filter out standard search engine crawlers and identify potentially malicious scanning behavior.
Detects anomalous, high-frequency access to LinkedIn 'about' pages, which may indicate reconnaissance activity or attempts to gather sensitive organizational information by an adversary. The rule uses threshold-based aggregation to filter out standard search engine crawlers and identify potentially malicious scanning behavior.
This rule detects Git repository modification events (such as pushes, branch creation, or reference creation) where the reference name matches a hexadecimal string (often indicative of a specific commit hash being pushed as a branch or tag) and the host is not github.com. This may indicate suspicious repository activity or interaction with non-standard or unauthorized code repositories.
Detects the creation of a git branch with a name consisting of exactly 40 hexadecimal characters. This naming convention is a known technique used to bypass security controls such as commit-pin verification in AI coding agent plugins and other CI/CD integrations (often associated with Plugin4Shell research).
Detects anomalous serialized object payloads within authenticated GraphQL subscription requests to GitLab Duo Chat endpoints. This pattern is indicative of exploitation attempts targeting the insecure deserialization vulnerability in GitLab EE (CVE-2026-87719), where malicious payloads are injected into serialized data streams.
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 suspicious administrative activity within Google Tag Manager, including tag creation, updates, and container publishing, combined with logins originating from multiple IP addresses or geographical locations for the same account. This is indicative of potential account compromise or unauthorized configuration changes.
Detects anomalous reuse of an authenticated Microsoft 365 session cookie shortly after a successful MFA-satisfied sign-in. The detection identifies scenarios where the subsequent access originates from a different IP address, device, or user agent without an intervening MFA challenge, which is a pattern indicative of session hijacking techniques like Adversary-in-the-Middle (AiTM) or session token replay.
Detects the creation of a WordPress administrator account within one hour of a recorded web request to a known web shell path (Mushr00w) or suspect plugin upload directory. This correlation is a high-fidelity indicator of post-exploitation persistence and administrative account hijacking.
Detects unauthenticated execution of sensitive Grafana MCP tools (tools/call, grafana_api_request) by identifying session IDs that lack a corresponding authenticated handshake event. This behavior is indicative of potential session spoofing or abuse of the MCP protocol where an attacker attempts to interact with privileged tools without performing a valid authentication handshake.
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.
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