Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
472 detections
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The following analytic identifies when a new device is enrolled on an Okta account. It uses OktaIm2 logs ingested via the Splunk Add-on for Okta Identity Cloud to detect the creation of new device enrollments. This activity is significant as it may indicate a legitimate user settinging up a new device or an adversary adding a device to maintain unauthorized access. If confirmed malicious, this could lead to potential account takeover, unauthorized access, and persistent control over the compromised Okta account. Monitoring this behavior is crucial for detecting and mitigating unauthorized access attempts.
This correlation rule identifies when a user exceeds a predefined risk threshold based on multiple suspicious Okta activities within a 24-hour period. It aggregates risk events from "Suspicious Okta Activity," "Okta Account Takeover," and "Okta MFA Exhaustion" analytic stories. The detection is significant as it highlights potentially compromised user accounts exhibiting multiple tactics, techniques, and procedures (TTPs). If confirmed malicious, this activity could indicate a serious security breach, allowing attackers to gain unauthorized access, escalate privileges, or persist within the environment.
The following analytic detects attempts to disable multi-factor authentication (MFA) for an Azure AD user. It leverages Azure Active Directory AuditLogs to identify the "Disable Strong Authentication" operation. This activity is significant because disabling MFA can allow adversaries to maintain persistence using compromised accounts without raising suspicion. If confirmed malicious, this action could enable attackers to bypass an essential security control, potentially leading to unauthorized access and prolonged undetected presence in the environment.
The analytic detects the registration of a new Multi-Factor Authentication (MFA) method for an Azure AD account. It leverages Azure AD AuditLogs to identify when a user registers new security information. This activity is significant because adversaries who gain unauthorized access to an account may add their own MFA method to maintain persistence. If confirmed malicious, this could allow attackers to bypass existing security controls, maintain long-term access, and potentially escalate their privileges within the environment.
The following analytic identifies suspicious command-line parameters associated with the use of Impacket's smbexec.py for lateral movement. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns indicative of Impacket tool usage. This activity is significant as both Red Teams and adversaries use Impacket for remote code execution and lateral movement. If confirmed malicious, this activity could allow attackers to execute commands on remote endpoints, potentially leading to unauthorized access, data exfiltration, or further compromise of the network.
The following analytic detects when a user in an Azure AD environment grants consent to an OAuth application. It leverages Azure AD audit logs to identify events where users approve application consents. This activity is significant as it can expose organizational data to third-party applications, a common tactic used by malicious actors to gain unauthorized access. If confirmed malicious, this could lead to unauthorized access to sensitive information and resources. Immediate investigation is required to validate the application's legitimacy, review permissions, and mitigate potential risks.
This detection identifies when a new Microsoft Intune device health script has been added, updated, or deleted. Intune device remediation scripts can be used by administrators for remote device management, but this functionality can also be abused for SYSTEM-level code execution and lateral movement to Intune-managed devices.
The following analytic detects high-risk sign-in attempts against Azure Active Directory, identified by Azure Identity Protection. It leverages the RiskyUsers and UserRiskEvents log categories from Azure AD events ingested via EventHub. This activity is significant as it indicates potentially compromised accounts, flagged by heuristics and machine learning. If confirmed malicious, attackers could gain unauthorized access to sensitive resources, leading to data breaches or further exploitation within the environment.
This detection identifies when an administrator manually triggers device management configuration policy sync events, on-demand remediation scripts, or remotely restarts devices within Microsoft Intune. While this functionality can be used legitimately to expedite policy delivery, it can also be abused by an attacker to quickly deploy malicious payloads or disrupt systems.
The following analytic detects suspicious database file and directory discovery activities, which may signal an attacker attempt to locate and assess critical database assets on a compromised system. This behavior is often a precursor to data theft, unauthorized access, or privilege escalation, as attackers seek to identify valuable information stored in databases. By monitoring for unusual or unauthorized attempts to locate database files and directories, this analytic aids in early detection of potential reconnaissance or data breach efforts, enabling security teams to respond swiftly and mitigate the risk of further compromise.
The following analytic detects the addition of a new custom domain within an Azure Active Directory (AD) tenant. It leverages Azure AD AuditLogs to identify successful "Add unverified domain" operations. This activity is significant as it may indicate an adversary attempting to establish persistence by setting up identity federation backdoors, allowing them to impersonate users and bypass authentication mechanisms. If confirmed malicious, this could enable attackers to gain unauthorized access, escalate privileges, and maintain long-term access to the Azure AD environment, posing a severe security risk.
The following analytic detects the assignment of privileged Azure Active Directory roles to a user. It leverages Azure AD audit logs, specifically monitoring the "Add member to role" operation. This activity is significant as adversaries may assign privileged roles to compromised accounts to maintain persistence within the Azure AD environment. If confirmed malicious, this could allow attackers to escalate privileges, access sensitive information, and maintain long-term control over the Azure AD infrastructure.
The analytic identifies AWS console login attempts by users from a new region. It leverages AWS CloudTrail events and compares current login regions against a baseline of previously seen regions for each user. This activity is significant as it may indicate unauthorized access attempts or compromised credentials. If confirmed malicious, an attacker could gain unauthorized access to AWS resources, potentially leading to data breaches, resource manipulation, or further lateral movement within the cloud environment.
This analytic detects file transfers flagged as malware that occurred over non-standard ports (other than 80 and 443) from Cisco Secure Firewall Threat Defense logs. Adversaries may attempt to bypass protocol-based detection or use alternate ports to blend in with other traffic. This analytic identifies these non-conventional flows and surfaces potential evasion techniques. If confirmed malicious, this indicates potential malware delivery or other nefarious activity.
The following analytic detects `spoolsv.exe` writing a `.dll` file, which is unusual behavior and may indicate exploitation of vulnerabilities like CVE-2021-34527 (PrintNightmare). This detection leverages Sysmon EventID 11 to monitor file creation events in the `\spool\drivers\x64\` directory. This activity is significant because `spoolsv.exe` typically does not write DLL files, and such behavior could signify an ongoing attack. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or maintain persistence on the compromised system.
The following analytic detects a suspicious registry modification aimed at disabling security audit logs by adding a specific registry entry. It leverages data from the Endpoint.Registry data model, focusing on changes to the "Control\\MiniNt" registry path. This activity is significant because it can prevent Windows from logging any events to the Security Log, effectively blinding security monitoring efforts. If confirmed malicious, this technique could allow an attacker to operate undetected, making it difficult to trace their actions and compromising the integrity of security audits.
This analytic identifies the assignment of the 'Application Administrator' role to an Azure AD user. This activity is significant because users in this role can manage all aspects of enterprise applications, including credentials, which can be used to impersonate application identities. If confirmed malicious, an attacker could escalate privileges, manage application settings, and potentially access sensitive resources by impersonating application identities, posing a significant security risk to the Azure AD tenant.
This analytic identifies potential privilege escalation activities within an organization's Active Directory (AD) environment by correlating multiple analytics from the "Active Directory Privilege Escalation" analytic story within a specified time frame. This is significant for a SOC as it helps identify coordinated attempts to gain elevated privileges, which could indicate a serious security threat. If confirmed malicious, this activity could allow attackers to gain unauthorized access to sensitive systems and data, leading to potential data breaches and further compromise of the network.
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 following analytic detects when a single service principal in Azure AD creates more than three unique OAuth applications within a 10-minute span. It leverages Azure AD audit logs, specifically monitoring the 'Add service principal' operation initiated by service principals. This behavior is significant as it may indicate an attacker using a compromised or malicious service principal to rapidly establish multiple service principals, potentially staging an attack. If confirmed malicious, this activity could facilitate network infiltration or expansion, allowing the attacker to gain unauthorized access and persist within the environment.
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.
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