Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of MSP360 or generic RMM-labeled binaries originating from common user download directories (Downloads or Temp folders) when the filename mimics common phishing lures such as invoice, e-card, RSVP, or document-related naming conventions. This activity indicates a potential social engineering attempt to execute remote monitoring and management tools.
Detects inbound emails that have been delivered to the user's Inbox or Junk folder despite failing SPF authentication checks. The detection logic triggers when these emails also lack a valid DMARC policy (none or not available), which prevents the mail server from enforcing rejection or quarantine, allowing spoofed or unauthenticated mail to bypass standard security filters.
Detects potential help-desk impersonation or social engineering activity involving account credential or MFA method resets, followed shortly by a sign-in from an unknown device or geography. The rule excludes activity tied to established ticketing systems or standard automated password expiration processes.
The following analytic identifies Living Off the Land Binaries and Scripts (LOLBAS) that can legitimately initiate public network connections but are communicating over uncommon destination ports.
It leverages the Network Traffic data model and applies per-binary common-port exclusions to reduce false positives while preserving suspicious non-standard communication.
This behavior may indicate payload download, command-and-control, proxy execution, or attempts to blend malicious traffic into trusted Windows binaries.
Join this detection with the Process Execution events to provide context and avoid false positives.
It leverages the Network Traffic data model and applies per-binary common-port exclusions to reduce false positives while preserving suspicious non-standard communication.
This behavior may indicate payload download, command-and-control, proxy execution, or attempts to blend malicious traffic into trusted Windows binaries.
Join this detection with the Process Execution events to provide context and avoid false positives.
This rule detects the use of 'docker cp' or 'sbx cp' commands which are susceptible to the CVE-2026-17106 (CopyEscape) vulnerability. This vulnerability allows a compromised container to perform arbitrary file writes or overwrites on the host system during archive extraction, potentially leading to container escape and privilege escalation by replacing critical system binaries like runc.
The following analytic identifies the creation of cloud compute instances by users who have not previously created them. It leverages data from the Change data model, focusing on 'create' actions by users, and cross-references with a baseline of known user activities. This activity is significant as it may indicate unauthorized access or misuse of cloud resources by new or compromised accounts. If confirmed malicious, attackers could deploy unauthorized compute instances, leading to potential data exfiltration, increased costs, or further exploitation within the cloud environment.
The following analytic detects the creation of a cloud compute instance in a region that has not been previously used within the last hour. It leverages cloud infrastructure logs and compares the regions of newly created instances against a lookup file of historically used regions. This activity is significant because the creation of instances in new regions can indicate unauthorized or suspicious activity, such as an attacker attempting to evade detection or establish a foothold in a less monitored area. If confirmed malicious, this could lead to unauthorized resource usage, data exfiltration, or further compromise of the cloud environment.
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.
The following analytic identifies a LOLBAS process being executed outside of it's expected location.
Processes being executed outside of expected locations may be an indicator that an adversary is attempting to evade defenses or execute malicious code.
The LOLBAS project documents Windows native binaries that can be abused by threat actors to perform tasks like executing malicious code.
Processes being executed outside of expected locations may be an indicator that an adversary is attempting to evade defenses or execute malicious code.
The LOLBAS project documents Windows native binaries that can be abused by threat actors to perform tasks like executing malicious code.
The following analytic detects the creation or connection to known suspicious named pipes, which is a technique often used by offensive tools.
It leverages Sysmon EventCodes 17 and 18 to identify known default pipe names used by RMM tools.
If confirmed malicious, this could allow an attacker to abuse these to potentially gain persistence, command and control, or further system compromise.
It leverages Sysmon EventCodes 17 and 18 to identify known default pipe names used by RMM tools.
If confirmed malicious, this could allow an attacker to abuse these to potentially gain persistence, command and control, or further system compromise.
The following analytic detects the creation or connection to known suspicious named pipes.
It leverages Sysmon EventCodes 17 and 18 to identify known default pipe names used by malicious or suspicious tools.
If confirmed malicious, this could allow an attacker to abuse these to potentially gain privilege escalation,
persistence, c2 communications, or further system compromise.
It leverages Sysmon EventCodes 17 and 18 to identify known default pipe names used by malicious or suspicious tools.
If confirmed malicious, this could allow an attacker to abuse these to potentially gain privilege escalation,
persistence, c2 communications, or further system compromise.
This rule correlates phishing emails containing URLs with successful, MFA-satisfied sign-ins from an ASN or network location that has not been associated with the user account within the previous 30 days. This pattern is highly indicative of an Adversary-in-the-Middle (AiTM) session hijacking attempt, where a user is phished and their session cookie is intercepted by an attacker.
This rule detects instances of 'javaw.exe' executing from unusual directories (e.g., AppData, Temp, Users\Public) while loading a 'jli.dll' file from a related non-standard path, or simultaneously being associated with a scheduled task execution involving 'GlobalTellurSync'. This behavior is indicative of potential DLL side-loading or a persistence mechanism where a legitimate Java executable is repurposed to run malicious code.
Matches distinctive DragonForce TURN/MQTT campaign artifact filenames only when combined with byte-level markers unique to the malware (PE structure, TURN/MQTT C2 infrastructure strings, or the loader's pipe-caret-pipe thread-trigger byte pattern), to avoid false positives on unrelated benign files sharing these names.
Detects the execution of control.exe with suspicious command-line arguments involving WebDAV paths (DavWWWRoot) and file extensions like .cpl or .dll, initiated by Windows task-related processes (svchost, taskeng, schtasks). This pattern is indicative of potential malicious payload loading or proxy execution where a scheduled task is used to trigger a secondary malicious component.
Detects the execution of renamed schtasks.exe binary, which is a legitimate Windows utility used for scheduling tasks.
One of the very common persistence techniques is schedule malicious tasks using schtasks.exe.
Since, it is heavily abused, it is also heavily monitored by security products. To evade detection, threat actors may rename the schtasks.exe binary to schedule their malicious tasks.
One of the very common persistence techniques is schedule malicious tasks using schtasks.exe.
Since, it is heavily abused, it is also heavily monitored by security products. To evade detection, threat actors may rename the schtasks.exe binary to schedule their malicious tasks.
Detects high-risk operations performed by the Entra ID/AAD Connect synchronization service account (e.g., Sync_* or ADToAADSyncServiceAccount). This account, which often holds broad directory permissions, is a prime target for attackers to gain persistence or escalate privileges within the cloud directory. The rule monitors for unauthorized sign-ins, sensitive configuration changes (such as modifications to federation trust, authentication policies, or directory synchronization settings), and password resets targeting the sync account itself.
This rule detects anomalous sign-in behavior for Azure Service Principals by comparing current activity against a 14-day baseline. It alerts on sign-ins from new ASNs or countries, significant spikes in sign-in volume, or unauthorized access to sensitive resources such as Microsoft Graph, Exchange Online, or Azure Key Vault, while filtering out known cloud egress ranges.
Detects unauthorized or suspicious modifications to audit and logging configurations across AWS, Azure, and GCP. The rule identifies actions such as stopping, deleting, or updating logging trails, diagnostic settings, or logging sinks, which may indicate an adversary attempting to impair visibility into their activities (Anti-Forensics).
This rule detects successful non-interactive sign-ins to high-value applications (e.g., Office 365, Azure, Okta) where no multi-factor authentication (MFA) challenge was performed during the current session. Such activity is a strong indicator of session hijacking or token replay attacks, where adversaries reuse stolen session cookies to bypass interactive login requirements and MFA.
Detects unauthorized access to DPAPI master key files located in the Windows user profile (%APPDATA%\Microsoft\Protect\). This activity is commonly associated with infostealers attempting to decrypt browser-stored credentials (cookies, passwords) by manually accessing the master key files after exfiltrating encrypted data stores.
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