Detections

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

2,982 detections

Detects Microsoft 365 sign-in activity consistent with adversary-in-the-middle (AiTM) token theft. The rule identifies successful sign-ins with multi-factor authentication, immediately followed by a new session attempt for the same user within 30 minutes from a different device, IP address, or location.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
203
Detects reconnaissance activity targeting sensitive personnel groups (payroll, HR, finance) via Microsoft Graph API. The rule identifies suspicious URI patterns combined with the use of the 'axios' User-Agent library, potentially indicating automated enumeration by an adversary to map high-value targets for future business email compromise or credential theft.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
103
Detects Microsoft Entra OAuth 2.0 device authorization grant flow completion immediately followed by non-interactive API access from automated user agents like python-requests. This behavior is indicative of device code phishing kits, where an attacker tricks a user into entering a code and then programmatically hijacks the resulting session token.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
003
Detects sign-in events using the OAuth 2.0 device code flow, which is a mechanism often abused in phishing campaigns (such as GhostCode) to lure users into authorizing malicious applications or granting access tokens without needing their actual credentials.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
003
Detects anomalous GitLab CI pipeline execution that matches patterns associated with GitRunner C2 abuse. The detection identifies pipelines triggered via API (CI_PIPELINE_SOURCE=api) with cloning disabled (GIT_STRATEGY=none) and a specific static job name (run_command), which can indicate the CI runner is being abused as a command-and-control channel for arbitrary script execution.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
004
Detects potential device code phishing patterns where a successful OAuth device-code authentication is rapidly followed by Microsoft Graph resource access from the same account. The rule identifies suspicious polling sessions (e.g., EvilTokens) by monitoring for successful device-code sign-ins and immediate, subsequent Graph API activity. It filters known first-party applications and incorporates risk-based triggers and reconnaissance behavioral patterns to minimize false positives.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
103
Detects anomalous post-authentication reconnaissance activities against the Microsoft Graph API, specifically the enumeration of directory objects, roles, or service principals. The rule triggers when a user account performs multi-endpoint enumeration via the Graph API within 30 minutes of a successful authentication session initiated via a device code flow that was flagged with elevated risk signals. This behavior is consistent with post-compromise reconnaissance techniques such as 'EvilTokens', where an adversary attempts to map the environment after gaining access.
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Arnold Chan@slaz
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Hunters
1 month ago
003
Detects automated post-compromise mailbox reconnaissance following an anomalous OAuth device code sign-in that exhibits high-risk indicators. The rule identifies programmatic access to a high volume of mail items within a short window following suspicious token issuance, which is characteristic of automated scanning or data exfiltration tooling.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
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Ankit Mehta@Secvyn
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Detection & Hunting Community
1 month ago
202
Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
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Ankit Mehta@Secvyn
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Hunters
1 month ago
102
Detects Microsoft Entra Privileged Identity Management (PIM) activations for high-privileged roles (e.g., Global Administrator) that occur outside of defined business hours or are performed without an associated justification or ticket number. This helps identify potentially unauthorized or abnormal use of elevated privileges.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
402
Detects a single user identity performing bulk destructive device actions (wipe, retire, remote lock, or delete) against multiple distinct devices within a short timeframe. This activity is indicative of potential unauthorized access and destructive intent, mirroring techniques observed in large-scale cloud-based identity compromise incidents.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
102
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
002
Detects suspicious force push events to the 'main' branch in GitHub repositories. The rule flags pushes that include hardcoded commit hashes associated with known malicious activity, pushes where the author and committer identities do not match, or pushes containing specific indicators such as 'indexe.cjs' or 'preinstall' scripts which are common in software supply chain attacks.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
105
Correlates an MFA method change with the next sign-in occurring from an ASN/country never seen for that user in 30 days, operationalizing TrustSphere's 2026 finding that reset-then-new-location access is the clearest signal separating a hijack from a genuine recovery.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
302
Aggregates MFA/passkey enrollments tenant-wide, alerting when an unusual number of distinct users register new authenticators within a short rolling window — a mass-takeover indicator rather than isolated recovery activity, especially when linked by a common actor or source ASN.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
102
Detects successful self-service password reset (SSPR) activities within Azure Active Directory. This event signifies that a user has successfully changed or reset their password using the self-service mechanism.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
This rule detects a potential vishing attack by correlating suspicious IT helpdesk requests (e.g., password or MFA reset without manager approval or verified callback) with subsequent sensitive Entra ID identity changes (e.g., self-service password resets, MFA device registration, or new device registration) occurring for the same user within a short time window. This activity is indicative of an attacker attempting to social-engineer helpdesk staff to bypass authentication controls and compromise a user account.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
Detects successful user sign-ins from geographically distant locations occurring within a timeframe that is physically impossible to traverse (implied speed > 900 km/h). The rule further filters for scenarios where the device used for authentication appears non-compliant or uses an unrecognized method, potentially indicating an attacker utilizing stolen credentials and bypassing MFA.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
Detects inbound Microsoft Teams calls or chats originating from an external or federated tenant where the caller's display name mimics internal IT support or helpdesk personnel, a technique used in social engineering and vishing campaigns.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
Detects a sequence of events where a user's MFA configuration is modified (typically via a help-desk impersonation vishing attack) followed closely by a successful sign-in from a new IP address. This pattern is indicative of attackers hijacking sessions or stealing credentials by coercing victims into resetting MFA settings.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
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