Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
608 detections
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This analytic detects when an unusual number of NTLM authentications is attempted by the same source. This activity generally results when an attacker attempts to brute force, password spray, or otherwise authenticate to a domain joined Windows device using an NTLM based process/attack. This same activity may also generate a large number of EventID 4776 events in as well.
The analytic detects multiple failed attempts to assume an AWS IAM role, indicating a potential brute force attack. It leverages AWS CloudTrail logs to identify `MalformedPolicyDocumentException` errors with a status of `failure` and filters out legitimate AWS services. This activity is significant as repeated failures to assume roles can indicate an adversary attempting to guess role names, which is a precursor to unauthorized access. If confirmed malicious, this could lead to unauthorized access to AWS resources, potentially compromising sensitive data and services.
The following analytic detects CrowdStrike alerts for non-admin accounts with duplicate password risk, identifying instances where multiple non-admin users share the same password. This practice weakens security and increases the potential for unauthorized access. Addressing these alerts is essential to ensure each user account has a unique, strong password, thereby enhancing overall security and protecting sensitive information.
The following analytic identifies unsuccessful login attempts to the AWS Management Console using a specific user identity. It leverages AWS CloudTrail logs to detect failed authentication events associated with the AWS ConsoleLogin action. This activity is significant for a SOC because repeated failed login attempts may indicate a brute force attack or unauthorized access attempts. If confirmed malicious, an attacker could potentially gain access to AWS account services and resources, leading to data breaches, resource manipulation, or further exploitation within the AWS environment.
The analytic detects when a device is the target of numerous NTLM authentications using a null domain. This activity generally results when an attacker attempts to brute force, password spray, or otherwise authenticate to a domain joined Windows device from a non-domain device. This activity may also generate a large number of EventID 4776 events in tandem, however these events will not indicate the attacker or target device.
The analytic detects patterns of successful and failed Okta MFA push attempts to identify potential MFA exhaustion attacks. It leverages Okta event logs, specifically focusing on push verification events, and uses statistical evaluations to determine suspicious activity. This activity is significant as it may indicate an attacker attempting to bypass MFA by overwhelming the user with push notifications. If confirmed malicious, this could lead to unauthorized access, compromising the security of the affected accounts and potentially the entire environment.
The following analytic detects multiple failed attempts to assume an AWS IAM role, indicating a potential brute force attack. It leverages AWS CloudTrail logs to identify `MalformedPolicyDocumentException` errors with a status of `failure` and filters out legitimate AWS services. This activity is significant as repeated failures to assume roles can indicate an adversary attempting to guess role names, which is a precursor to unauthorized access. If confirmed malicious, this could lead to unauthorized access to AWS resources, potentially compromising sensitive data and services.
This analytic detects an unusual number of NTLM authentications targeting a single destination using a null domain. This activity is indicative of an attacker attempting to brute force or password spray a domain-joined Windows device from a non-domain device. Such activity may also generate a high volume of EventID 4776 events, though these events might not specify the attacker or target device.
The analytic detects an Azure AD account successfully authenticating from multiple unique IP addresses within a 30-minute window. It leverages Azure AD SignInLogs to identify instances where the same user logs in from different IPs in a short time frame. This behavior is significant as it may indicate compromised credentials being used by an adversary, potentially following a phishing attack. If confirmed malicious, this activity could allow unauthorized access to corporate resources, leading to data breaches or further exploitation within the network.
The following analytic detects multiple failed login attempts in Office365 Azure Active Directory from a single source IP address. It leverages Office365 management activity logs, specifically AzureActiveDirectoryStsLogon records, aggregating these logs in 5-minute intervals to count failed login attempts. This activity is significant as it may indicate brute-force attacks or password spraying, which are critical to monitor. If confirmed malicious, an attacker could gain unauthorized access to Office365 accounts, leading to potential data breaches, lateral movement within the organization, or further malicious activities using the compromised account.
This analytic identifies when a single user account attempts to authenticate to Azure/EntraID/Office 365 from multiple distinct operating systems within a short timeframe. This behavior can indicate an attacker's attempt to enumerate various logon capabilities, potentially to discover weaknesses in an organization's MFA or conditional access configurations. Tools like "MFASweep" are known to trigger this detection.
The following analytic identifies instances where more than 10 unique user accounts fail to authenticate from a single IP address within a 5-minute window. This detection leverages O365 audit logs, specifically Azure Active Directory login failures (AzureActiveDirectoryStsLogon). Such activity is significant as it may indicate brute-force attacks or password spraying attempts. If confirmed malicious, this behavior suggests an external entity is attempting to breach security by targeting multiple accounts, potentially leading to unauthorized access. Immediate action is required to block or monitor the suspicious IP and notify affected users to enhance their security measures.
The analytic detects when an unusual number of NTLM authentications is attempted by the same source against multiple destinations. This activity generally results when an attacker attempts to brute force, password spray, or otherwise authenticate to multiple domain-joined Windows devices using an NTLM-based process/attack. This same activity may also generate a large number of EventID 4776 events as well.
The following analytic detects CrowdStrike alerts for Medium Identity Risk Severity with a risk score of 55% or higher. These alerts indicate significant vulnerabilities in user identities, such as suspicious behavior or compromised credentials. Promptly investigating and addressing these alerts is crucial to prevent potential security breaches and ensure the integrity and protection of sensitive information and systems.
The following analytic identifies instances where more than 10 unique user accounts have failed to authenticate from a single IP address within a 5-minute window in an Okta tenant. This detection uses OktaIm2 logs ingested via the Splunk Add-on for Okta Identity Cloud. Such activity is significant as it may indicate brute-force attacks or password spraying attempts. If confirmed malicious, this behavior suggests an external entity is attempting to compromise multiple user accounts, potentially leading to unauthorized access to organizational resources and data breaches.
The analytic detects an IP address with 20 or more failed authentication attempts to an Azure AD tenant within 10 minutes. It leverages Azure AD SignInLogs to identify repeated failed logins from the same IP. This behavior is significant as it may indicate a brute force attack aimed at gaining unauthorized access or escalating privileges. If confirmed malicious, the attacker could potentially compromise user accounts, leading to unauthorized access to sensitive information and resources within the Azure 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.
The following analytic detects CrowdStrike alerts for admin accounts with duplicate password risk, identifying instances where administrative users share the same password. This practice significantly increases the risk of unauthorized access and potential breaches. Addressing these alerts promptly is crucial for maintaining strong security protocols, ensuring each admin account uses a unique, secure password to protect critical systems and data.
The analytic detects accounts experiencing a high number of Single Sign-On (SSO) logon errors within Office 365. It specifically looks for `UserLoginFailed` operations with `LogonError` containing "Sso" in the `o365_management_activity` data. A count of 5 or more such errors from the same source, vendor account, vendor product, destination, signature, and user agent within a given timeframe is considered anomalous. This activity can indicate brute-force attempts against SSO, credential stuffing, or attempts to reuse hijacked SSO tokens, potentially leading to unauthorized account access, data breaches, or further compromise.
The analytic detects an IP address with 20 or more failed authentication attempts to the AWS Web Console within a 5-minute window. This detection leverages CloudTrail logs, aggregating failed login events by IP address and time span. This activity is significant as it may indicate a brute force attack aimed at gaining unauthorized access or escalating privileges within an AWS environment. If confirmed malicious, this could lead to unauthorized access, data breaches, or further exploitation of AWS resources.
The following analytic identifies an excessive number of authentication failures, including failed attempts against MFA prompt codes. It uses data from the `o365_management_activity` dataset, focusing on events where the authentication status is marked as failure. This behavior is significant as it may indicate a brute force attack or an attempt to compromise user accounts. If confirmed malicious, this activity could lead to unauthorized access, data breaches, or further exploitation within the environment.
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