Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a successful device-code sign-in followed within 60 minutes by non-interactive replay from a different IP AND a persistence action (inbox rule, app consent, device add) from a non-original IP. Persistence is now mandatory (inner join) instead of optional, and the retired AADSignInEventsBeta table is replaced by EntraIdSignInEvents.
The following analytic detects instances where Azure AD has blocked a user's attempt to grant consent to a risky or potentially malicious application.
This detection leverages Azure AD audit logs, focusing on user consent actions and system-driven blocks.
Monitoring these blocked consent attempts is crucial as it highlights potential threats early on, indicating that a user might be targeted or that malicious applications are attempting to infiltrate the organization.
If confirmed malicious, this activity suggests that Azure's security measures successfully prevented a harmful application from accessing organizational data, warranting immediate investigation to understand the context and take preventive measures.
This detection leverages Azure AD audit logs, focusing on user consent actions and system-driven blocks.
Monitoring these blocked consent attempts is crucial as it highlights potential threats early on, indicating that a user might be targeted or that malicious applications are attempting to infiltrate the organization.
If confirmed malicious, this activity suggests that Azure's security measures successfully prevented a harmful application from accessing organizational data, warranting immediate investigation to understand the context and take preventive measures.
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 single identity/IP querying Microsoft Graph endpoints for directory roles, role management, registered authentication methods, applications, service principals, OAuth2 permission grants, and app role assignments within a short window - control-plane reconnaissance mapping privilege escalation and persistence opportunities
Detects the rare 'AssumeRoot' event in AWS STS followed by high-impact administrative or destructive API calls within a one-hour window. This behavior often indicates an adversary attempting to gain elevated, privileged access to perform unauthorized actions such as disabling logging, deleting infrastructure, or modifying IAM policies.
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 sign-in activity originating from a known suspicious VPN/proxy IP range targeting critical Microsoft 365 applications. The rule specifically monitors for instances where multi-factor authentication (MFA) enforcement appears to be absent or failed, suggesting a potential account compromise and subsequent data access attempt via a proxy/VPN.
Detects high-volume retrieval of secrets by a single principal within a one-hour window across AWS Secrets Manager, Azure Key Vault, and Google Cloud Secret Manager. This behavior is indicative of bulk credential harvesting or automated sensitive data exfiltration following unauthorized access or privilege escalation in cloud environments.
This rule detects potential privilege escalation in cloud environments (AWS, Azure, GCP) by identifying the attachment or update of overly permissive policies (e.g., wildcard permissions or administrative roles) followed by rapid execution of high-privilege actions (like creating new users, keys, or profiles) by the same actor within 15 minutes.
Detects chained AWS STS AssumeRole/AssumeRoleWithSAML/AssumeRoleWithWebIdentity events where a principal assumes a role in a different account and then quickly performs another role assumption from that new context. This pattern, often referred to as 'role chaining' or 'role laundering', is frequently used to obfuscate identity tracking and facilitate lateral movement across AWS account boundaries.
Okta flagged a password as present in a known breach corpus and still issued a session
for the same account within the same hour. Indicates the tenant's sign-on policy is not
enforcing the breached-credential signal and the account is likely under attacker control.
for the same account within the same hour. Indicates the tenant's sign-on policy is not
enforcing the breached-credential signal and the account is likely under attacker control.
The following analytic detects cloud provisioning activities originating from previously unseen countries. 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 potential compromise of cloud resources. If confirmed malicious, an attacker could gain control over cloud assets, leading to data breaches, service disruptions, or further infiltration into the network.
This analytic detects mailbox rule creation, a common technique used in Business Email Compromise. It uses a scoring mechanism to identify a combination of attributes often featured in mailbox rules created by attackers. This may indicate that an attacker has gained access to the account.
Detects anomalous AWS Bedrock activity indicative of LLMjacking by correlating multiple phases of an attack chain (Model Enablement, Reconnaissance, Probing, and Execution) performed by a single identity within a short timeframe. This rule identifies attackers leveraging stolen IAM credentials to discover available AI models, probe for vulnerabilities, and execute unauthorized inference requests at scale.
This rule detects potentially malicious reuse of an existing Entra ID (Azure AD) refresh or session token (via UniqueTokenIdentifier) across multiple, distinct device IDs, IP addresses, or user-agent strings within a short period (default 4 hours). It specifically flags instances where the authentication was completed via a non-interactive token claim, suggesting the adversary is bypassing MFA by hijacking an active session.
Detects instances where an identity associated with AI or automated agents (service accounts, service principals, bots, or assistants) is assigned to highly privileged administrative roles or security groups in the directory. This behavior potentially indicates an attempt to escalate privileges using a compromised or improperly configured agent identity.
Detects anomalous GCP IAM Service Account Credential API calls where a principal impersonates multiple distinct service accounts within a short time window. This behavior often indicates a credential delegation chain or a multi-stage privilege escalation attempt within a GCP environment.
This rule monitors for high-impact configuration API calls and the creation of new administrator accounts within the Cisco Secure Firewall Management Center (FMC). These actions are indicative of post-exploitation activity related to CVE-2026-20079, which allows for authentication bypass. The detection focuses on sensitive administrative actions such as policy deployment, certificate exports, and user account creation which, if performed without valid session context, suggest an unauthorized actor.
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 detects cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
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