Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors authentication activity within Microsoft Entra ID (formerly Azure AD) involving the Device Code flow. This flow is often abused by attackers through phishing to obtain access tokens. The rule detects and lists occurrences of authentication attempts leveraging the device code grant, facilitating the investigation of potentially malicious token acquisition or replay attacks.
Detects execution of the MovieReaper initial loader binary. This malware employs advanced anti-analysis techniques, specifically manual PEB-walking to resolve APIs and evade detection by standard library loading hooks. The rule alerts on known file hashes and specific masquerading filenames.
Detects execution of the MovieReaper initial loader, which employs specific anti-sandboxing and anti-analysis techniques. The detection relies on identified file hashes, as well as heuristic analysis of process filenames containing common media-related keywords in sensitive directories and command line arguments indicating the presence of Global mutexes.
Detects execution artifacts of the MovieReaper stage 2 implant, specifically its capability to parse and load COFF modules into memory without writing them to disk. The rule monitors process command lines for 'module_init' and identifies suspicious API activity related to memory-based module loading, such as reflective DLL loading or remote thread creation.
Detects the creation of a Windows service named 'ProcAuditManager', which is associated with the SparroWocky threat. The rule flags the service creation event (Event ID 7045) and identifies if the service description matches the known malicious signature, which attempts to masquerade as a legitimate auditing tool.
Detects in-memory modification of the AmsiScanBuffer function within PowerShell processes, specifically targeting the injection of patch instructions (e.g., MOV EAX, 80070057; RET). This technique is characteristic of .NET loaders like PIVOTPIPE attempting to bypass Antimalware Scan Interface (AMSI) inspection before executing malicious payloads.
Detects the GHAPPIER four-stage malware loader, specifically targeting npm-based JavaScript files. The rule identifies malicious activity through specific artifacts including hardcoded C2 URLs (vercel.app domains), campaign markers, file paths, and eval-based execution patterns.
Detects instances where rundll32.exe is used to execute a DLL file directly from a remote WebDAV-mounted network path (indicated by the 'DavWWWRoot' string). This technique allows for the execution of arbitrary code without writing the malicious payload to the local disk, a common tactic seen in fileless malware delivery and campaigns like ClearFake.
Detects the creation of the file 'nb_hook_dbg.txt' within 'C:\Windows\Temp\', which is a specific debug artifact generated by the PIVOTPIPE loader during the initialization of its HookGate subsystem. This subsystem is responsible for implementing indirect system calls to bypass user-mode EDR hooks by decoding syscall numbers at runtime and utilizing the WoW64 transition.
This rule detects system calls originating from unbacked, private, or unknown memory regions, which is a common indicator of reflective code loading or process injection techniques. It also flags suspicious call stacks where standard processes like PowerShell, rundll32, or .NET execute system calls on ntdll.dll from non-standard module memory.
Detects the deletion of suspicious files associated with macOS malware families commonly referred to as FLATROOF or ROOFDECK. The rule monitors for the removal of files located in specific directories ('com.apple.iTunesCloud/SystemUpdate' or 'com.apple.internal.ck/iSync') using system utilities like 'rm' or via the 'loginwindow' process, which is indicative of malware attempting to clean its tracks after execution or persistence.
Detects GitHub push events where the actor pushing the changes does not match the commit author or committer identities, and the commit is not cryptographically signed. This pattern may indicate credential theft or account compromise where an adversary is pushing code using stolen credentials or impersonating authorized users.
This rule detects potential PIVOTPIPE activity by correlating AMSI patching indicators with anomalous memory protection changes. It identifies processes that perform frequent transitions to PAGE_EXECUTE_READWRITE or PAGE_NOACCESS, which is indicative of memory-based obfuscation techniques used to evade memory scanning and detection during sleep cycles.
Detects ROOFDECK backdoor persistence via macOS Launch Agents, tightened to require the implant's distinguishing masquerade artifacts (fake Apple-service drop paths, --type=renderer flag, loginwindow.plist impersonation, or the literal 'persist add|remove|check' CLI syntax) rather than generic LaunchAgents plist creation or launchctl load activity, which legitimate macOS software triggers constantly.
Detects Linux processes masquerading as 'php-fpm' or 'postgres' that match known SHA-256 hashes associated with the RedTail malware family. The rule identifies processes attempting to hide their identity using techniques similar to prctl(PR_SET_NAME) to rename themselves while running malicious code.
Detects the deletion of specific files associated with the indexed-btree malware loader, such as 'sharedLoad.min.js' or files within an 'extended/' directory. This behavior indicates potential anti-forensic cleanup following malicious code execution.
This rule detects a correlation between the creation or modification of a specific file name ('nloemfbihmhm') and the subsequent execution of processes from the 'Temp' directory involving related filenames ('kojuyn.ini', 'ogftogcyiblzjccmcbnw.exe', or 'nloemfbihmhm') within a 5-minute window. This behavior is indicative of a multi-stage execution chain, often used by malware to drop and execute secondary payloads.
Detects instances where a process deletes its own executable or script file within 15 seconds of being launched. This behavior is often associated with self-modifying implants, transient scripts, or malicious artifacts attempting to minimize their footprint on the host system immediately after execution.
This rule detects potentially malicious messages within Microsoft Teams that use common social engineering keywords related to security configuration changes (e.g., passkey, MFA, SSO). The detection specifically filters for users who have successfully logged in within the last 30 days to identify potential compromised accounts acting as internal senders.
Detects successful user logins to accounts with names containing support-related terminology such as 'IT Support', 'Help Desk', or 'IT Department'. These accounts are often highly privileged or sensitive targets for credential abuse.
This rule monitors successful user sign-ins using the 'deviceCode' authentication protocol that originate from an IP address previously unseen for that specific user within the last 24 hours. The Device Code flow is commonly targeted in phishing campaigns to bypass traditional credential-based MFA, making anomalous logins using this protocol a high-signal indicator of account compromise.
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