Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,088 detections
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The following analytic identifies AWS console login events by users from a new country. It leverages AWS CloudTrail events and compares them against a lookup file of previously seen users and their login locations. This activity is significant because logins from new countries can indicate potential unauthorized access or compromised accounts. If confirmed malicious, this could lead to unauthorized access to AWS resources, data exfiltration, or further exploitation within the AWS environment.
The following analytic identifies the creation of a new AWS IAM policy version that allows access to all resources. It detects this activity by analyzing AWS CloudTrail logs for the CreatePolicyVersion event with a policy document that grants broad permissions. This behavior is significant because it violates the principle of least privilege, potentially exposing the environment to misuse or abuse. If confirmed malicious, an attacker could gain extensive access to AWS resources, leading to unauthorized actions, data exfiltration, or further compromise of the AWS environment.
This analytic identifies a successful authentication event against an Azure AD tenant using PowerShell cmdlets. This detection leverages Azure AD SignInLogs to identify successful logins where the appDisplayName is "Microsoft Azure PowerShell." This activity is significant because it is uncommon for regular, non-administrative users to authenticate using PowerShell, and it may indicate enumeration and discovery techniques by an attacker. If confirmed malicious, this activity could allow attackers to perform extensive reconnaissance, potentially leading to privilege escalation or further exploitation within the Azure environment.
This analytic identifies failed authentication attempts against an Azure AD tenant during the Multi-Factor Authentication (MFA) challenge, specifically flagged by error code 500121. It leverages Azure AD SignInLogs to detect these events. This activity is significant as it may indicate an adversary attempting to authenticate using compromised credentials on an account with MFA enabled. If confirmed malicious, this could suggest an ongoing effort to bypass MFA protections, potentially leading to unauthorized access and further compromise of the affected account.
The 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.
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 identifies a successful single-factor authentication event against Google Cloud Platform (GCP) for an account without Multi-Factor Authentication (MFA) enabled. It uses Google Workspace login event data to detect instances where MFA is not utilized. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to GCP resources, potentially leading to data breaches, service disruptions, or further exploitation within the cloud environment.
The following analytic detects the creation of AWS KMS keys with an encryption policy accessible to everyone, including external entities. It leverages AWS CloudTrail logs to identify `CreateKey` or `PutKeyPolicy` events where the `kms:Encrypt` action is granted to all principals. This activity is significant as it may indicate a compromised account, allowing an attacker to misuse the encryption key to target other organizations. If confirmed malicious, this could lead to unauthorized data encryption, potentially disrupting operations and compromising sensitive information across multiple entities.
The following analytic detects multiple failed multi-factor authentication (MFA) requests for a single user within a Google Cloud Platform (GCP) tenant. It triggers when 10 or more MFA prompts fail within a 5-minute window, using Google Workspace login failure events. This behavior is significant as it may indicate an adversary attempting to bypass MFA by bombarding the user with repeated authentication requests. If confirmed malicious, this activity could lead to unauthorized access, allowing attackers to compromise accounts and potentially escalate privileges within the GCP environment.
The analytic identifies AWS console login events by users from a new city within the last hour. It leverages AWS CloudTrail events and compares them against a lookup file of previously seen user locations. This activity is significant for a SOC as it may indicate unauthorized access or credential compromise, especially if the login originates from an unusual location. If confirmed malicious, this could lead to unauthorized access to AWS resources, data exfiltration, or further exploitation within the cloud environment.
This analytic detects an abnormally high number of cloud instances launched within a 4-hour period. It leverages cloud infrastructure logs and applies a probability density model to identify outliers based on historical data. This activity is significant for a SOC because a sudden spike in instance creation could indicate unauthorized access or misuse of cloud resources. If confirmed malicious, this behavior could lead to resource exhaustion, increased costs, or provide attackers with additional compute resources to further their objectives.
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.
The following analytic identifies a successful Console Login authentication event for an AWS IAM user account without Multi-Factor Authentication (MFA) enabled. It leverages AWS CloudTrail logs to detect instances where MFA was not used during login. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to the AWS environment, potentially leading to data exfiltration, resource manipulation, or further privilege escalation.
The following analytic identifies multiple failed multi-factor authentication (MFA) requests for a single user within an Azure AD tenant. It leverages Azure AD Sign-in Logs, specifically error code 500121, to detect more than 10 failed MFA attempts within 10 minutes. This behavior is significant as it may indicate an adversary attempting to bypass MFA by bombarding the user with repeated authentication prompts. If confirmed malicious, this activity could lead to unauthorized access, allowing attackers to compromise user accounts and potentially escalate their privileges within the environment.
The analytic detects failed authentication attempts during the Multi-Factor Authentication (MFA) challenge on a Google Cloud Platform (GCP) tenant. It uses Google Workspace login failure events to identify instances where MFA methods were challenged but not successfully completed. This activity is significant as it may indicate an adversary attempting to access an account with compromised credentials despite MFA protection. If confirmed malicious, this could lead to unauthorized access attempts, potentially compromising sensitive data and resources within the GCP environment.
The following analytic identifies alerts triggered by the Office 365 Security and Compliance Center, indicating potential threats or policy violations. It leverages data from the `o365_management_activity` dataset, focusing on events where the workload is SecurityComplianceCenter and the operation is AlertTriggered. This activity is significant as it highlights security and compliance issues within the O365 environment, which are crucial for maintaining organizational security. If confirmed malicious, these alerts could indicate attempts to breach security policies, leading to unauthorized access, data exfiltration, or other malicious activities.
The following analytic identifies the creation of a new AWS IAM policy version that allows access to all resources. It detects this activity by analyzing AWS CloudTrail logs for the CreatePolicyVersion event with a policy document that grants broad permissions. This behavior is significant because it violates the principle of least privilege, potentially exposing the environment to misuse or abuse. If confirmed malicious, an attacker could gain extensive access to AWS resources, leading to unauthorized actions, data exfiltration, or further compromise of the AWS environment.
The analytic identifies multiple failed multi-factor authentication (MFA) requests for a single user within a PingID environment. It triggers when 10 or more MFA prompts fail within 10 minutes, using JSON logs from PingID. This activity is significant as it may indicate an adversary attempting to bypass MFA by bombarding the user with repeated authentication requests. If confirmed malicious, this could lead to unauthorized access, as the user might eventually accept the fraudulent request, compromising the security of the account and potentially the entire network.
This analytic identifies failed authentication attempts during the Multi-Factor Authentication (MFA) challenge in an Okta tenant. It specifically looks for events where the authentication signature is `user.authentication.auth_via_mfa` and the action is `failure`. This activity is significant as it may indicate an adversary attempting to authenticate with compromised credentials on an account with MFA enabled, potentially suggesting an ongoing attempt to bypass MFA protections and gain unauthorized access.
The analytic identifies threats detected by Okta ThreatInsight, such as password spraying, login failures, and high counts of unknown user login attempts. It leverages Okta Identity Management logs, specifically focusing on `security.threat.detected` events. This activity is significant for a SOC as it highlights potential unauthorized access attempts and credential-based attacks. If confirmed malicious, these activities could lead to unauthorized access, data breaches, and further exploitation of compromised accounts, posing a significant risk to the organization's security posture.
The analytic identifies authentication events of service principals in Azure Active Directory. It leverages the `azure_monitor_aad` data source, specifically targeting "Sign-in activity" within ServicePrincipalSignInLogs. This detection gathers details such as sign-in frequency, timing, source IPs, and accessed resources. Monitoring these events is significant for SOC teams to distinguish between normal application authentication and potential anomalies, which could indicate compromised credentials or malicious activities. If confirmed malicious, attackers could gain unauthorized access to resources, leading to data breaches or further exploitation within the environment.
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