Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
545 detections
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This analytic detects Lumma Stealer download attempts using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where Snort signatures with specific IDs have been triggered. If confirmed malicious, this behavior could indicate an active infection of Lumma Stealer.
Detects a suspicious child process spawning from Microsoft Outlook where the executable image is located on a remote share (SMB/WebDav). This behavior is often associated with adversaries using Outlook to execute malicious code from network shares, potentially as part of persistence or execution techniques.
This analytic aggregates and summarizes alerts from Microsoft Defender for Endpoint. It extracts details such as source, file name, severity, process command line, IP address, registry key, signature, description, and unique ID. The detection is not intended to identify new activity from raw data but rather to leverage existing Microsoft Defender for Endpoint alerts for correlation and risk-based alerting. It filters out alerts with a 'clean' verdict and dynamically maps MITRE techniques and assigns risk scores based on the alert's severity.
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.
This analytic identifies the creation or modification of email inbox rules within an Office 365 environment. It specifically looks for `New-InboxRule` and `Set-InboxRule` operations in the O365 management activity logs where the rule parameters indicate actions such as mail forwarding (`ForwardTo`, `ForwardAsAttachmentTo`, `RedirectTo`), or mail manipulation like deletion (`SoftDeleteMessage`, `DeleteMessage`) or moving to specific folders (`MoveToFolder`, `CopyToFolder`). While legitimate users create inbox rules, adversaries often leverage these techniques to exfiltrate emails, maintain persistence, or hide their activities by deleting or moving security alerts.
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 identifies excessive AccessDenied events within an hour timeframe for IAM users in AWS. It leverages AWS CloudTrail logs to detect multiple failed access attempts from the same source IP and user identity. This activity is significant as it may indicate that an access key has been compromised and is being misused for unauthorized discovery actions. If confirmed malicious, this could allow attackers to gather information about the AWS environment, potentially leading to further exploitation or privilege escalation.
The analytic detects an Azure AD account with concurrent sessions originating from multiple unique IP addresses within a 5-minute window. It leverages Azure Active Directory NonInteractiveUserSignInLogs to identify this behavior by analyzing successful authentication events and counting distinct source IPs. This activity is significant as it may indicate session hijacking, where an attacker uses stolen session cookies to access corporate resources from a different location. If confirmed malicious, this could lead to unauthorized access to sensitive information and potential data breaches.
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 analytic identifies an Azure AD account experiencing more than 20 failed authentication attempts within a 10-minute window. This detection leverages Azure SignInLogs data, specifically monitoring for error code 50126 and unsuccessful authentication attempts. This behavior is significant as it may indicate a brute force attack targeting the account. If confirmed malicious, an attacker could potentially gain unauthorized access, leading to data breaches or further exploitation within the environment. Security teams should adjust the threshold based on their specific environment to reduce false positives.
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 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 analytic detects path traversal command-line execution, often used in malicious documents to execute code via msdt.exe for defense evasion. It leverages Endpoint Detection and Response (EDR) data, focusing on specific patterns in process paths. This activity is significant as it can indicate an attempt to bypass security controls and execute unauthorized code. If confirmed malicious, this behavior could lead to code execution, privilege escalation, or persistence within the environment, potentially allowing attackers to deploy malware or leverage other living-off-the-land binaries (LOLBins).
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.
The analytic detects suspicious behavior indicative of ProxyShell exploitation against on-premise Microsoft Exchange servers. It identifies HTTP POST requests to `autodiscover.json` containing `PowerShell` in the URI, leveraging server-side request forgery (SSRF) to access backend PowerShell. Monitoring this activity is crucial as it may indicate an attacker attempting to execute commands or scripts on the Exchange server. If confirmed malicious, this could lead to unauthorized access, privilege escalation, or persistent control over the Exchange environment.
This analytic detects the use of `mavinject.exe` for DLL injection into running processes. It specifically looks for command-line parameters such as `/INJECTRUNNING` and `/HMODULE`. This activity indicates potential arbitrary code execution, a common tactic for malware deployment and persistence. If confirmed malicious, this could allow attackers to execute unauthorized code, escalate privileges, and maintain persistence within the environment, posing a severe security risk.
This analytic detects the execution of AdvancedRun.exe, a utility that allows users to run programs with different administrative privileges, user accounts, or environment settings. It identifies the process by its name or original file name and flags common command-line arguments often used for configuration or specific execution parameters. Monitoring this activity is crucial as AdvancedRun can be leveraged by attackers for remote code execution, privilege escalation, or maintaining persistence within an environment, similar to tools like PsExec. If used maliciously, it could enable the execution of arbitrary commands or configuration-based automation.
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