Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detect web traffic to a recently expired domain followed by an exe file creation event
Detects the creation of a malicious DLL file named 'iphlpapi.dll' within the 'AppData\Local\Microsoft' directory, which is commonly used by applications like Microsoft Teams or OneDrive. This technique is often employed for DLL sideloading, where a legitimate application loads a malicious DLL placed in a specific directory, leading to code execution, persistence, privilege escalation, or defense evasion.
Detects the creation of system DLLs that are usually not present on the system (or at least not in system directories). This technique is commonly used to achieve DLL hijacking, which can lead to defense evasion, persistence, and privilege escalation.
Detects suspicious Windows Defender Application Control (WDAC) policy file creation from abnormal processes that could be abused by an attacker to block EDR/AV components while allowing their own malicious code to run on the system. The rule specifically looks for file creation events in the default WDAC policy directory and filters out known legitimate processes that manage these policies.
The analytic identifies instances of `mshta.exe` writing files to world-writable directories. It leverages Sysmon EventCode 11 logs to detect file write operations by `mshta.exe` to directories like `C:\Windows\Tasks` and `C:\Windows\Temp`. This activity is significant as it often indicates an attempt to establish persistence or execute malicious code, deviating from the utility's legitimate use. If confirmed malicious, this behavior could lead to the execution of multi-stage payloads, potentially resulting in full system compromise and unauthorized access to sensitive information.
The following analytic identifies the use of the right-to-left override (RTLO) character in file names. It leverages data from the Endpoint.Filesystem datamodel, specifically focusing on file creation events and file names containing the RTLO character (U+202E). This activity is significant because adversaries use RTLO to disguise malicious files as benign by reversing the text that follows the character. If confirmed malicious, this technique can deceive users and security tools, leading to the execution of harmful files and potential system compromise.
The following analytic detects the creation of files typically associated with SharpHound, a reconnaissance tool used for gathering domain and trust data. It leverages file modification events from the Endpoint.Filesystem data model, focusing on default file naming patterns like `*_BloodHound.zip` and various JSON files. This activity is significant as it indicates potential domain enumeration, which is a precursor to more targeted attacks. If confirmed malicious, an attacker could gain detailed insights into the domain structure, facilitating lateral movement and privilege escalation.
This analytic detects executable files (.exe or .dll) being written to Windows administrative SMB shares (Admin$, IPC$, C$). This behavior is significant as it is commonly used by tools like PsExec/PaExec for staging binaries before creating and starting services on remote endpoints, a technique often employed for lateral movement and remote code execution. If confirmed malicious, this activity could allow an attacker to execute arbitrary code remotely, potentially compromising additional systems within the network.
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.
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 following analytic detects suspicious creation of hidden files and directories, which may indicate an attacker's attempt to conceal malicious activities or unauthorized data. Hidden files and directories are often used to evade detection by security tools and administrators, providing a stealthy means for storing malware, logs, or sensitive information. By monitoring for unusual or unauthorized creation of hidden files and directories, this analytic helps identify potential attempts to hide malicious operations, enabling security teams to uncover and address hidden threats effectively.
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 the creation of an lsass.exe process dump using Windows Task Manager. It leverages Sysmon EventID 11 to identify file creation events where the target filename matches *lsass*.dmp. This activity is significant because creating an lsass dump can be a precursor to credential theft, as the dump file contains sensitive information such as user passwords. If confirmed malicious, an attacker could use the lsass dump to extract credentials and escalate privileges, potentially compromising the entire network.
The following analytic identifies the creation of Dynamic Link Libraries (DLLs) with a known history of exploitation in atypical locations. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process and filesystem events. This activity is significant as it may indicate DLL search order hijacking or sideloading, techniques used by attackers to execute arbitrary code, maintain persistence, or escalate privileges. If confirmed malicious, this activity could allow attackers to blend in with legitimate operations, posing a severe threat to system integrity and security.
This analytic detects email files (.pst or .ost) being created outside the standard Outlook directories. This activity is significant as it may indicate data exfiltration or unauthorized access to email data. If confirmed malicious, an attacker could potentially access sensitive email content, leading to data breaches or further exploitation within the network.
The following analytic detects the use of the Certipy tool to enumerate Active Directory Certificate Services (AD CS) environments by identifying unique file modifications. It leverages endpoint process and filesystem data to spot the creation of files with specific names or extensions associated with Certipy's information gathering and exfiltration activities. This activity is significant as it indicates potential reconnaissance and data exfiltration efforts by an attacker. If confirmed malicious, this could lead to unauthorized access to sensitive AD CS information, enabling further attacks or privilege escalation within the network.
The following analytic detects the creation of files in Linux init boot directories, which are used for automatic execution upon system startup. It leverages file system logs to identify new files in directories such as /etc/init.d/ and /etc/rc.d/. This activity is significant as it is a common persistence technique used by adversaries, malware authors, and red teamers. If confirmed malicious, this could allow an attacker to maintain persistence on the compromised host, potentially leading to further exploitation and unauthorized control over the system.
The following analytic detects unauthorized file creation in known crontab directories on Unix-based systems. It leverages filesystem data to identify new files in directories such as /etc/cron* and /var/spool/cron/*. This activity is significant as it may indicate an attempt by threat actors or malware to establish persistence on a compromised host. If confirmed malicious, this could allow attackers to execute arbitrary code at scheduled intervals, potentially leading to further system compromise and unauthorized access to sensitive information.
This analytic detects the creation of new files within the Linux kernel/driver directory. This activity is significant because this directory is typically reserved for kernel modules, and unauthorized file creation here can indicate a rootkit installation. If confirmed malicious, this could allow an attacker to gain high-level privileges, potentially compromising the entire system by executing code at the kernel level.
The analytic detects the creation of files containing passwords, cookies, and saved login account information by the Braodo stealer malware in temporary folders. Braodo often collects these credentials from browsers and applications, storing them in temp directories before exfiltration. This detection focuses on monitoring for the creation of files with patterns or formats commonly associated with stolen credentials. By identifying these activities, security teams can take needed action to prevent sensitive login data from being leaked, reducing the risk of unauthorized access to user accounts and systems.
The analytic detects the creation of files with extensions commonly associated with the Mimikatz Crypto module. It leverages the Endpoint.Filesystem data model to identify specific file names indicative of certificate export activities. This behavior is significant as it may indicate the use of Mimikatz to export cryptographic keys, which is a common tactic for credential theft. If confirmed malicious, this activity could allow an attacker to exfiltrate sensitive cryptographic material, potentially leading to unauthorized access and further compromise of the environment.
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