Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects administrative actions in Azure that disable or modify diagnostic settings, which stops the flow of logs to services like Azure Sentinel/Log Analytics, or deletes policy assignments. Such actions are often performed by adversaries to blind security operations monitoring prior to lateral movement or further malicious activity.
This rule detects modifications to AWS CloudTrail configurations that reduce logging visibility, such as stopping the logging service, deleting a trail, or updating a trail to include restrictive event selectors (e.g., non-multi-region, read-only events, or excluding management events). These actions are indicative of an attacker attempting to evade detection by limiting the audit trail available to security analysts.
Detects modifications to Google Cloud Storage bucket IAM policies that grant access to 'allUsers' or 'allAuthenticatedUsers'. This activity indicates a potential misconfiguration or an attempt by an attacker to stage or exfiltrate data by making bucket contents publicly accessible.
Detects instances where an IAM user or role attempts to assume a role in a different AWS account (Cross-Account) without providing a valid ExternalID. This often indicates unauthorized attempts to access or abuse cross-account trust relationships, which is a common technique for lateral movement or privilege escalation in cloud environments.
This rule detects scenarios where a user account grants high-privilege permissions (e.g., mail access or file modification) to an OAuth application within a short time frame (2 hours) following a sign-in event flagged as risky by Entra ID (Azure AD). This pattern is indicative of an adversary abusing OAuth consent flows as a persistence and credential-access mechanism following account compromise.
This rule detects potentially malicious bulk mailbox exfiltration operations (such as New-MailboxExportRequest, New-ComplianceSearch, or Search-Mailbox) performed by an account within 24 hours of experiencing a high or medium-risk sign-in event, suggesting post-compromise data harvesting.
Detects anomalous authentication behavior where a single session identifier is used to access three or more distinct SaaS applications within a one-hour window. This behavior often indicates the unauthorized use of a stolen session cookie or OAuth token (Pass-the-Cookie) across multiple SSO-integrated platforms.
Detects AWS CloudTrail events where an actor performs identity or session token manipulation, specifically through the use of sts:GetFederationToken or sts:AssumeRole, or by modifying MFA configurations such as DeactivateMFADevice or CreateVirtualMFADevice on privileged accounts. This activity may indicate an attempt to gain persistent access, bypass security controls, or masquerade as a legitimate principal.
Detects the addition of a new client secret or certificate to an application or service principal by a user account. This activity is correlated with recent high-risk or suspicious sign-in events. Adversaries often perform this action following account takeover to establish durable, MFA-immune persistence in the cloud tenant.
Detects instances where a user performs high-risk sign-in activities (such as impossible travel or triggered risk events) followed by the registration of new security information, MFA methods, or rogue OAuth devices within a 30-minute window. This behavior is indicative of an attacker establishing persistence on a compromised account by bypassing or hardening MFA requirements.
Detects impossible travel authentication patterns where a user logs in from two geographically distant locations within a short time frame, while specifically filtering for sessions that reuse existing refresh or session tokens instead of performing fresh interactive authentication.
Detects potential account compromise by aggregating multiple high-fidelity indicators of adversary activity for a single user within a 72-hour window. The rule triggers when at least three distinct stages of an attack chain are identified, specifically: credential theft/infostealer activity, anomalous sign-in (token reuse/impossible travel), mailbox or OAuth configuration changes, and mass data exfiltration.
This rule detects administrative or user activity within Azure via AzureActivity logs and web request patterns in AppServiceHTTPLogs that originate from a predefined list of known malicious IP addresses.
The following analytic identifies cloud instances being modified by users who have not previously modified them. It leverages data from the Change data model, focusing on successful modifications of EC2 instances. This activity is significant because it can indicate unauthorized or suspicious changes by potentially compromised or malicious users. If confirmed malicious, this could lead to unauthorized access, configuration changes, or potential disruption of cloud services, posing a significant risk to the organization's cloud infrastructure.
The following analytic detects cloud provisioning activities originating from previously unseen cities. It leverages cloud infrastructure logs and compares the geographic location of the source IP address against a baseline of known locations. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from an unexpected location. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
The following analytic detects cloud provisioning activities originating from previously unseen IP addresses. It leverages cloud infrastructure logs to identify events where resources are created or started, and cross-references these with a baseline of known IP addresses. This activity is significant as it may indicate unauthorized access or potential misuse of cloud resources. If confirmed malicious, an attacker could gain unauthorized control over cloud resources, leading to data breaches, service disruptions, or increased operational costs.
The following analytic detects cloud provisioning activities originating from previously unseen regions. It leverages cloud infrastructure logs to identify events where resources are started or created, and cross-references these with a baseline of known regions. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from unfamiliar locations. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
This rule monitors for the addition of new credentials (secrets) to service principals or applications in an Azure/Entra ID environment. It then correlates this event with subsequent mailbox activity (such as accessing mail items, sending mail, or message binding) performed by the application within 7 days of the credential creation. This detection pattern is indicative of potential OAuth application-based persistence and mailbox data exfiltration.
Detects a sequence of potentially malicious local command execution (via PowerShell, cmd, or mshta) that mirrors the 'ClickFix' social engineering pattern, followed by an OAuth application consent grant or device-code authorization by the same user within a short timeframe. This behavior is indicative of an adversary attempting to bypass MFA by tricking a user into authorizing a malicious application after establishing local execution on their endpoint.
Detects the creation of scheduled tasks, recurring jobs, or webhook subscriptions by a user identity flagged as an AI_AGENT. This activity is monitored for persistence, especially when the event lacks a descriptive context or targets external networks, suggesting potential unauthorized agent behavioral drift or malicious persistence.
Detects instances where a user grants OAuth application permissions to an unverified third-party application. The rule specifically monitors for high-privilege scopes such as Mail.Read, Files.ReadWrite.All, or full_access_as_app, which are commonly abused in illicit consent grant attacks to achieve persistent access to sensitive mailbox and cloud data.
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