Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The analytic identifies a suspicious process executed from within common container/archive file types such as ZIP, ISO, IMG, and others. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it is a common technique used by adversaries to execute scripts or evade defenses. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, or persist within the environment, posing a significant security risk.
The analytic detects the creation or enabling of services on Linux platforms using the `systemctl` or `service` tools. It leverages Endpoint Detection and Response (EDR) logs, focusing on process names, parent processes, and command-line executions. This activity is significant as adversaries may create or modify services to maintain persistence or execute malicious payloads. If confirmed malicious, this behavior could lead to persistent access, data theft, ransomware deployment, or other damaging outcomes. Monitoring and investigating such activities are crucial for maintaining the security and integrity of the environment.
The analytic detects the execution of a batch command designed to recursively delete files or directories, a technique often used by ransomware like Reddot to delete files in the recycle bin and prevent recovery. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions that include specific flags for recursive and quiet deletions. This activity is significant as it indicates potential ransomware behavior aimed at data destruction. If confirmed malicious, it could lead to significant data loss and hinder recovery efforts, severely impacting business operations.
Detects .NET DLLs containing hardcoded Azure Storage Account credentials, such as access keys or SAS tokens. This technique was observed in the Axis Communications plugin for Autodesk Revit, where it could have enabled a supply chain attack.
The following analytic identifies processes running from file paths not typically associated with legitimate software. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process paths within the Endpoint data model. This activity is significant because adversaries often use unconventional file paths to execute malicious code without requiring administrative privileges. If confirmed malicious, this behavior could indicate an attempt to bypass security controls, leading to unauthorized software execution, potential system compromise, and further malicious activities within the environment.
This analytic detects instances where Chromium-based browsers (e.g., Google Chrome, Microsoft Edge, Brave, Opera, Vivaldi) are launched with the `--user-data-dir` command-line argument, combined with `--disable-gpu` or `--disable-3d-apis`. While `--user-data-dir` is a legitimate flag for multi-profile support or automation, its use alongside GPU/3D API disabling flags is frequently observed in malware and adversary tactics. This combination can indicate an attempt to run the browser in an isolated, potentially stealthy environment for activities such as credential harvesting, phishing delivery, or evasion of user session artifacts and analysis.
The following analytic identifies processes running from %temp% directory file paths. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process paths within the Endpoint data model. This activity is significant because adversaries often use unconventional file paths to execute malicious code without requiring administrative privileges. If confirmed malicious, this behavior could indicate an attempt to bypass security controls, leading to unauthorized software execution, potential system compromise, and further malicious activities within the environment.
Detects Chaos C++ ransomware payloads based on known file hashes and unique embedded strings from the malware.
Detects potential DLL side-loading activity associated with the Confucius threat group. This rule identifies when a legitimate executable, known to be abused by Confucius (e.g., fixmapi.exe), is run from a non-standard, user-writable directory and loads a suspicious DLL from the same location.
The analytic detects the use of Windows Curl.exe to upload a file to a remote destination. It identifies command-line arguments such as `-T`, `--upload-file`, `-d`, `--data`, and `-F` in process execution logs. This activity is significant because adversaries may use Curl to exfiltrate data or upload malicious payloads. If confirmed malicious, this could lead to data breaches or further compromise of the system. Analysts should review parallel processes and network logs to determine if the upload was successful and isolate the endpoint if necessary.
Detects attempts to suspend or terminate Endpoint Detection and Response (EDR) agent processes by targeting their Process IDs (PIDs). The rule identifies suspicious command-line arguments and tools (e.g., procdump, WerFault) used to interact with processes, specifically looking for these actions against a predefined list of common EDR agent executable names. It correlates process creation events with process ID resolution to identify the targeted EDR agent.
Detects loaders associated with RainyDay, Turian, and a new PlugX variant, used by threat actors like Naikon and BackdoorDiplomacy. The rule identifies the shared unpacking routine which uses a combination of RC4 decryption and LZNT1 decompression (via RtlDecompressBuffer), along with specific RC4 keys, PDB paths, and hardcoded payload filenames.
Detects a Windows command shell executing a batch file that subsequently spawns processes for system discovery (often for AV checking) and then either executes a potential payload or performs network reconnaissance. This behavior is consistent with the initial stages of the BlockBlasters malware campaign.
Detection for shai-hulud supply chain attack. All npm packages. [Why not externaldata()? 'cause it is computationally expensive, and it may not run)
This rule detects network connections initiated by a process with a command line containing "filesystem", "--json", and "--results=verified", which is used to scan the entire filesystem.
This specific combination of command-line arguments is associated with the Shai-Hulud malware.
This specific combination of command-line arguments is associated with the Shai-Hulud malware.
This rule detects the creation of an executable file (.exe) that is being extracted by an archive where the command line includes 'tar -xzf' and a '.tar.gz' archive.
This analytic identifies instances where a shell (PowerShell.exe or Cmd.exe) is spawned from W3WP.exe, the IIS worker process. This activity is significant as it may indicate webshell activity, often associated with exploitation attempts like those by the HAFNIUM Group on Exchange servers. If confirmed malicious, this behavior could allow attackers to execute arbitrary commands, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.
This analytic detects the execution of known remote access software within the environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and parent processes mapped to the Endpoint data model. The rule compares observed process names with a list of known remote access software. This activity is significant as adversaries often use remote access tools like AnyDesk, GoToMyPC, LogMeIn, and TeamViewer to maintain unauthorized access. If confirmed malicious, this could allow attackers to control systems remotely, exfiltrate data, or deploy additional malware, posing a severe threat to the organization's security.
This analytic identifies the execution of suspicious processes, such as `cmd.exe`, `powershell.exe`, or `bash.exe`, when they are spawned by web server processes like `w3wp.exe` or `nginx.exe`. This behavior is a strong indicator of WebShell activity, where an adversary exploits a web application vulnerability to gain persistent access and command execution capabilities on the web server. Successful exploitation could lead to arbitrary command execution, privilege escalation, and data exfiltration.
The analytic detects the writing of files from known remote access software to disk within the environment. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on file path, file name, and user information. This activity is significant as adversaries often use remote access tools like AnyDesk, GoToMyPC, LogMeIn, and TeamViewer to maintain unauthorized access. If confirmed malicious, this could allow attackers to persist in the environment, potentially leading to data exfiltration, further compromise, or complete control over affected systems.
The following analytic detects the execution of AppCmd.exe to install a new module in IIS. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as adversaries may use it to install webshells or backdoors, leading to credit card scraping, persistence, and further post-exploitation. If confirmed malicious, this could allow attackers to maintain persistent access, execute arbitrary code, and potentially exfiltrate sensitive information from the compromised web server.
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