Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
9,759 detections
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The 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 the Endpoint datamodel, specifically monitoring process and filesystem events to identify `.dll` file creation within the `\spool\drivers\x64\` path. This activity is significant as it may signify an attacker attempting to execute malicious code via the Print Spooler service. If confirmed malicious, this could lead to unauthorized code execution and potential system compromise. Immediate endpoint isolation and further investigation are recommended.
This analytic detects the use of Plink (including renamed versions like pvhost.exe) for protocol tunneling, which may be used for egress or lateral movement within an organization. It identifies specific command-line options (-R, -L, -D, -l, -N, -P, -pw) commonly used for port forwarding and tunneling by analyzing process execution logs from Endpoint Detection and Response (EDR) agents. This activity is significant as it may indicate an attempt to bypass network security controls or establish unauthorized connections. If confirmed malicious, this could allow an attacker to exfiltrate data, move laterally across the network, or maintain persistent access, posing a severe threat to the organization's security. The detection covers both the original Plink executable and potential renamed versions, enhancing its ability to catch evasion attempts.
The following analytic detects the use of COM objects like CMLUA or CMSTPLUA to bypass User Account Control (UAC). It leverages Sysmon EventCode 7 to identify the loading of specific DLLs (CMLUA.dll, CMSTPLUA.dll, CMLUAUTIL.dll) by processes not typically associated with these libraries. This activity is significant as it indicates an attempt to gain elevated privileges, a common tactic used by ransomware adversaries. If confirmed malicious, this could allow attackers to execute code with administrative rights, leading to potential system compromise and further malicious activities.
The following analytic detects the use of curl on Linux or MacOS systems to download a file from a remote source and pipe it directly to bash for execution. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, command-line arguments, and parent processes. This activity is significant as it is commonly associated with malicious actions such as coinminers and exploitation of vulnerabilities like CVE-2021-44228 in Log4j. If confirmed malicious, this behavior could lead to unauthorized code execution, system compromise, and further exploitation within the environment.
The following analytic detects the usage of headless browsers within an organization. It identifies processes containing the "--headless" and "--disable-gpu" command line arguments, which are indicative of headless browsing. This detection leverages data from the Endpoint.Processes datamodel to identify such processes. Monitoring headless browser usage is significant as these tools can be exploited by adversaries for malicious activities like web scraping, automated testing, and undetected web interactions. If confirmed malicious, this activity could lead to unauthorized data extraction, automated attacks, or other covert operations on web applications.
The following analytic detects the execution of 7z.exe, a 7-Zip utility, spawned from rundll32.exe or dllhost.exe. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process names and parent processes. This activity is significant as it may indicate an adversary attempting to use 7-Zip for data exfiltration, often by renaming the executable to evade detection. If confirmed malicious, this could lead to unauthorized data archiving and exfiltration, compromising sensitive information and potentially leading to further system exploitation.
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 the use of `wmic.exe` with the `delete` command to remove an executable path. This activity often indicates an adversary attempting to disable security tools or other critical processes, facilitating further compromise and persistence within the environment, potentially for malicious activities like cryptocurrency mining.
The analytic detects the use of Rubeus command line parameters, a toolset for Kerberos attacks within Active Directory environments. It leverages Endpoint Detection and Response (EDR) data to identify specific command-line arguments associated with actions like ticket manipulation, kerberoasting, and password spraying. This activity is significant as Rubeus is commonly used by adversaries to exploit Kerberos for privilege escalation and lateral movement. If confirmed malicious, this could lead to unauthorized access, persistence, and potential compromise of sensitive information within the network.
This analytic detects the use of `wget` to download a file from a remote source and pipe its content directly to `bash` for execution. This behavior is commonly associated with malicious activities such as deploying coinminers or exploiting vulnerabilities like CVE-2021-44228 (Log4j). Successful execution of such commands could lead to arbitrary code execution, system compromise, and unauthorized data access.
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 analytic identifies a suspicious `explorer.exe` process with the `/root` command-line parameter. This detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on process and command-line data. The presence of `/root` in `explorer.exe` is significant as it may indicate parent process spoofing, a technique used by malware to evade detection. If confirmed malicious, this activity could allow an attacker to operate undetected, potentially leading to unauthorized access, privilege escalation, or persistent threats within the environment.
The analytic detects the creation of specific AzureHound-related files, such as `*-azurecollection.zip` and various `.json` files, on disk. It leverages data from the Endpoint.Filesystem datamodel, focusing on file creation events with specific filenames. This activity is significant because AzureHound is a tool used to gather information about Azure environments, similar to SharpHound for on-premises Active Directory. If confirmed malicious, this activity could indicate an attacker is collecting sensitive Azure environment data, potentially leading to further exploitation or privilege escalation within the cloud infrastructure.
The analytic detects the deletion of shadow copies using the vssadmin.exe or wmic.exe utilities. This activity is significant because deleting shadow copies is a common tactic used by attackers to prevent recovery and hide their tracks. If confirmed malicious, this action could hinder incident response efforts and allow attackers to maintain persistence and cover their activities, making it crucial for security teams to investigate promptly.
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 detects the spawning of a PowerShell process as a child or grandchild of commonly abused processes like services.exe, wmiprvse.exe, svchost.exe, wsmprovhost.exe, and mmc.exe. This activity is significant as it often indicates lateral movement or remote code execution attempts by adversaries. If confirmed malicious, this behavior could allow attackers to execute code remotely, escalate privileges, or persist within the environment.
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 analytic identifies a process command line querying the CachedLogonsCount registry value in the Winlogon registry. This activity can indicate the use of post-exploitation tools like Winpeas, which gather information about login caching settings. If confirmed malicious, this activity could help attackers understand login caching configurations, potentially aiding in credential theft or lateral movement within the network.
The following analytic detects suspicious registry modifications that implement auto admin logon by adding DefaultUserName and DefaultPassword values. It leverages data from the Endpoint.Registry data model, specifically monitoring changes to the "SOFTWARE\Microsoft\Windows NT\CurrentVersion\Winlogon" registry path. This activity is significant because it is associated with BlackMatter ransomware, which uses this technique to automatically log on to compromised hosts and continue encryption after a safe mode boot. If confirmed malicious, this could allow attackers to maintain persistence and further encrypt the network, leading to significant data loss and operational disruption.
The following analytic detects the use of Impacket's `wmiexec.py` tool for lateral movement by identifying specific command-line parameters. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes spawned by `wmiprvse.exe` with command-line patterns indicative of Impacket usage. This activity is significant as Impacket tools are commonly used by adversaries for remote code execution and lateral movement within a network. If confirmed malicious, this could allow attackers to execute arbitrary commands on remote systems, potentially leading to further compromise and data exfiltration.
The following analytic detects the potential abuse of the verclsid.exe utility to execute malicious files via generated CLSIDs. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns associated with verclsid.exe. This activity is significant because verclsid.exe is a legitimate Windows application used to verify CLSID COM objects, and its misuse can indicate an attempt to bypass security controls. If confirmed malicious, this technique could allow an attacker to execute arbitrary code, potentially leading to system compromise or further malicious activities.
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