Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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KQL Query from file: JivaChat Installer - Full Chain
KQL Query from file: JivaChat Installer - Full Chain
Detects the on-disk presence of a malicious Firefox browser extension, 'pdf-para-texto@extensao.local', used for credential or data harvesting. The rule monitors for the creation of its manifest file or XPI package in specific directories, indicating the staging or installation of the malicious extension.
Detects the on-disk presence of a malicious Firefox browser extension, 'pdf-para-texto@extensao.local', used for credential or data harvesting. The rule monitors for the creation of its manifest file or XPI package in specific directories, indicating the staging or installation of the malicious extension.
Detects the on-disk presence of a malicious Firefox browser extension, 'pdf-para-texto@extensao.local', used for credential or data harvesting. The rule monitors for the creation of its manifest file or XPI package in specific directories, indicating the staging or installation of the malicious extension.
Detects the modification or creation of COM InProcServer32 registry keys within HKCU or HKU hives where the associated server value points to a DLL located in the AppData directory. This pattern is commonly used for persistence and privilege escalation via COM hijacking.
Detects the on-disk presence of a malicious Firefox browser extension, 'pdf-para-texto@extensao.local', used for credential or data harvesting. The rule monitors for the creation of its manifest file or XPI package in specific directories, indicating the staging or installation of the malicious extension.
This rule detects the presence of the malicious 'pdf-para-texto@extensao.local' Firefox extension on disk. This extension is known to perform browser-based credential interception by patching the WebAuthn PublicKeyCredential interface at document_start on Google-related domains to facilitate account takeover.
Detects the WAV-based loader staging technique: a RIFF/WAVE file carrying a high-entropy appended blob, or a companion DLL chain (rdCore.dll/WMPCL.dll/WPFLocalizeExtension.dll) referencing the hidden audio payload and the encrypted monitor.raw container used to unpack the final RAT
Detects the WAV-based loader staging technique: a RIFF/WAVE file carrying a high-entropy appended blob, or a companion DLL chain (rdCore.dll/WMPCL.dll/WPFLocalizeExtension.dll) referencing the hidden audio payload and the encrypted monitor.raw container used to unpack the final RAT
Detects the WAV-based loader staging technique: a RIFF/WAVE file carrying a high-entropy appended blob, or a companion DLL chain (rdCore.dll/WMPCL.dll/WPFLocalizeExtension.dll) referencing the hidden audio payload and the encrypted monitor.raw container used to unpack the final RAT
Detects behavior indicative of the MLTBackdoor malware, specifically the creation or modification of a DLL file (such as *dlp.dll) shortly after or before the creation of an RC4-encrypted 'data.bin' file on the same host. The rule also looks for an optional preceding archive extraction event of common file types from Temp or Downloads directories by standard extraction utilities, which may indicate the staging of the initial payload.
Detects .ps1-named files dropped to disk that are never actually executed by a PowerShell interpreter (powershell.exe / pwsh.exe) within a short window afterward. NeedyMantis's second-stage loader (e.g. encryptbase64.ps1) is raw x64 shellcode, not a real script -- it's read and executed directly by the dropping process, so no genuine PowerShell host process ever references the file by name. Replaces an earlier version of this rule that watched DeviceImageLoadEvents for a .ps1 extension: Windows can only emit an image-load event for a file with a valid PE header loaded via the OS loader, and raw shellcode has no PE header and is never mapped that way, so that approach would not have fired on this malware. Caveat: legitimate deployment tooling that stages a script for delayed or remote execution can also produce this create/execute mismatch; tune the window and add known-good deployment-tool exclusions for your environment.
Detects endpoint, process, and network activity associated with the 'TaskStomp' threat actor, specifically targeting known malicious file hashes, command-and-control domains, and specific URLs used in their campaigns.
IOC hunt for the HEAVYGRAM/CRUDEEXCLUDE campaign: matches known SHA256 file hashes (first-stage malware, implant, RAR/ZIP artefacts) via DeviceFileEvents and DeviceProcessEvents, plus known-malicious domains/staging infrastructure by parsed hostname across network connections, process command lines, and file origin URLs.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule monitors for file creation or existence patterns in the user's Local Temp directory that are commonly associated with infostealer malware, specifically looking for naming conventions like 'evo_cl_*.exe', 'evo_db_*.db', or the presence of a 'stolen.zip' file within subdirectories.
This rule monitors for the presence of a file named '_socket.pyd', which is a standard Python library component. The alert triggers when this file appears within a specific directory path 'Traiolx Custom Utils' or matches a known file hash associated with potentially malicious activity or unauthorized use of Python modules.
Detects the presence or execution of artifacts associated with the TrustSink proof-of-concept (deploy.py, cleanup_eam.py, deploy_state.json), which is used to register or remove rogue Entra authentication providers.
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