Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects changes to Entra ID Conditional Access policies that degrade security posture. This includes deleting a policy, disabling an enabled policy, removing grant controls (like MFA requirements), expanding trusted location/IP ranges, or adding user/group/role exclusions. Such activities are indicative of an attacker attempting to weaken authentication and security enforcement to maintain persistent access or facilitate further lateral movement.
The following analytic detects the assignment of privileged roles to service principals in Azure Active Directory (AD). It leverages the AuditLogs log category from ingested Azure AD events. This activity is significant because assigning elevated permissions to non-human entities can lead to unauthorized access or malicious activities. If confirmed malicious, attackers could exploit these service principals to gain elevated access to Azure resources, potentially compromising sensitive data and critical infrastructure. Monitoring this behavior helps prevent privilege escalation and ensures the security of Azure environments.
The following analytic identifies the assignment of sensitive and privileged Azure Active Directory roles to an Azure AD user. Adversaries and red teams alike may assign these roles to a compromised account to establish Persistence in an Azure AD environment. This detection leverages the O365 Universal Audit Log data source.
Detects unauthorized attempts to disable, suspend, or downgrade critical native cloud security and monitoring services (e.g., AWS GuardDuty, AWS Security Hub, Azure Defender for Cloud, and GCP Security Command Center). Attackers often perform these actions to evade detection of subsequent malicious activity within the cloud environment.
Detects instances where a user account associated with a detected infostealer malware infection (e.g., Redline, Raccoon, Vidar) successfully authenticates to a cloud service from a suspicious network location, such as a VPN, residential proxy, or Tor exit node, within 24 hours of the infection alert.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
Detects a suspected device-code phishing attack where a user visits a known malicious lure domain and shortly thereafter completes a successful Microsoft 365 device-code authentication. This rule correlates network events with sign-in logs within a 10-minute window to identify session hijacking attempts that bypass traditional MFA.
Detects a suspected device-code phishing attack where a user visits a known malicious lure domain and shortly thereafter completes a successful Microsoft 365 device-code authentication. This rule correlates network events with sign-in logs within a 10-minute window to identify session hijacking attempts that bypass traditional MFA.
Detects modifications to Azure DevOps pipelines or service connections that include indicators of outbound tunneling or reverse proxy tools (e.g., ngrok, socat, chisel, or SSH reverse tunnels). This behavior is characteristic of an attacker attempting to establish a command-and-control channel or bypass firewall restrictions by tunneling traffic out of the CI/CD pipeline execution environment.
Detects modifications to domain federation settings in Microsoft Entra ID (formerly Azure AD) where a domain is converted from a managed authentication state to a federated authentication state. This type of configuration change is often used by adversaries to establish persistence or facilitate domain-level identity deception.
Detects the use of standard Linux command-line utilities (e.g., cat, curl, vi) to read or reference sensitive cloud credential files or Kubernetes service account tokens. This behavior is a common indicator of credential theft or discovery activities following initial access to a Linux host.
Detects an anomalous volume of file downloads from SharePoint or OneDrive by a user on an unmanaged, non-compliant device, shortly following a suspicious or risky sign-in event. The rule establishes a baseline for individual user behavior over 30 days and alerts when the current hourly download activity significantly exceeds that baseline.
This rule detects potentially compromised accounts by correlating suspicious authentication activity (such as risky sign-ins, impossible travel, or malicious OAuth/Mail-rule configurations) with a subsequent spike in SharePoint or OneDrive file access, downloads, or external link sharing within a one-hour window. This behavior is indicative of an adversary performing cloud-based data exfiltration after gaining unauthorized access to an account.
Detects anomalous authentication patterns where a single source IP targets a high number of unique user accounts with failed authentication attempts over a rolling window. By filtering out SSO/Federated methods and specific service account patterns, this rule isolates low-and-slow brute-force or password-spraying activities designed to evade standard account lockout mechanisms.
This rule detects a suspicious sequence of events where a user performs an unusual device-code authentication (potentially indicative of device code phishing) followed shortly by an OAuth application consent or permission grant event. It flags potential compromise if the sign-in is new for the user or occurs in a short timeframe, with optional indicators associated with the 'maillive.sbs' phishing infrastructure.
Detects anomalous device-authorization-grant (RFC 8628) activity indicative of device-code phishing attacks (e.g., Tycoon2FA). The rule identifies user accounts exhibiting a rapid succession of 'authorization_pending' (70016) status polling attempts followed by a successful token issuance (0), constrained to a short time window and excluding known first-party Microsoft CLI/dev-tool applications.
This rule detects a password-spraying attack pattern directed at privileged or manager-titled accounts. It monitors for multiple failed sign-in attempts from a single source IP address against a large volume of distinct user accounts identified as managers or senior staff. The detection logic filters for low-frequency attempts per account, which is indicative of a distributed spray attack designed to evade account lockout thresholds while focusing on high-value targets.
Detects modifications to Microsoft Entra ID (formerly Azure AD) authentication policies, specifically the registration, enablement, or modification of External Authentication Methods (EAMs). This activity can indicate an attempt to add a rogue authentication provider for persistent unauthorized access, bypassing standard MFA or conditional access policies.
This rule detects anomalous activity associated with the Antino backdoor, which uses Microsoft OneDrive as a dead-drop command-and-control (C2) channel. It identifies specific file paths related to heartbeat check-ins, operator tool drops, and exfiltration retrieval, summarizing events by user and IP to highlight potential malicious persistent communication and data transfer patterns.
Detects anomalous authentication patterns associated with AI agent or service account credentials. The rule monitors for logins originating from multiple disparate network locations, ASNs, or countries within a 15-minute window, and detects unexpected MFA challenges directed at accounts that typically function as automated, headless identities.
Detects registration of a new actor-controlled MFA authentication method (phone, authenticator app, or software OTP token) via an Update user operation, matching the NO_DEVICE/NO_DEVICE_TOKEN/SoftwareTokenActivated pattern used to convert temporary compromise into durable identity persistence
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