Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
40,056 detections
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Detects unauthorized processes attempting to read or create sensitive browser credential files ('Login Data', 'Web Data', 'Cookies', 'logins.json', 'key4.db'). This activity is commonly associated with information-stealing malware (such as Lumma, StealC, Vidar, RedLine, and Amadey) that targets browser databases to extract stored secrets, often bypassing standard browser process access.
This rule detects a multi-stage attack chain where a device shows signs of credential theft (accessing browser credential stores or cookies) followed closely by a successful cloud authentication from that same user using a device identifier not previously observed in the last 30 days.
Detects instances where a process that is not a recognized web browser (chrome, msedge, firefox, brave, opera, or explorer) accesses multiple unique browser cookie files. This is a common pattern for credential harvesting malware attempting to steal browser sessions.
This rule detects the execution of common Remote Monitoring and Management (RMM) and remote access tools (e.g., ScreenConnect, AnyDesk, Atera, Splashtop, NinjaOne, Action1) when the command line includes silent install or installation flags. The detection correlates this activity with recent (within 72 hours) identity-related alerts (e.g., impossible travel, anomalous sign-in, credential compromise) for the same user, suggesting a potential high-risk scenario where an adversary is establishing remote access following a credential compromise.
This rule correlates endpoint security alerts for popular information-stealer malware (Lumma, StealC, Vidar, RedLine, Acreed, Atomic Stealer) with subsequent successful cloud identity authentication events from the same user account. The correlation window is set to 72 hours following an endpoint infostealer detection, which suggests potential account takeover or unauthorized access facilitated by credentials stolen from a compromised endpoint.
This rule detects network connections initiated by unsigned executables that were recently created (within one hour) in common staging directories such as AppData, Temp, or ProgramData. It specifically targets beacons to the Telegram Bot API or Discord webhooks, which are common patterns for command-and-control (C2) communication used by malware such as the Amadey bot.
Detects potential lateral movement by identifying NTLM authentication (Logon Type 3) to administrative network shares (ADMIN$, C$, IPC$) or high-frequency access to multiple hosts by the same user, which may indicate credential abuse or lateral movement attempts.
Detects a sequence indicative of credential harvesting and subsequent lateral movement propagation (e.g., NotPetya-style activity). The rule identifies processes accessing LSASS memory (credential dumping) followed within a one-hour window by network activity via SMB (TCP 445) or remote process execution via WMI.
Detects anomalous or potentially malicious LDAP queries on Domain Controllers, utilizing Event ID 1644 to monitor query filters. The rule identifies patterns commonly associated with reconnaissance and enumeration activities, including Kerberoasting (SPN enumeration), AS-REP roasting, delegation abuse, Active Directory Certificate Services (AD CS) enumeration, BloodHound collection, and bulk user, group, or computer discovery.
This rule performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
This rule performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
This rule performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
Detects automated reconnaissance using WMI or PowerShell to perform broad queries for system environment, security products, network adapters, software, and hardware attributes. The detection focuses on clusters of distinct WMI reconnaissance categories occurring within a 15-minute window, which is often indicative of pre-C2 profiling by adversaries.
Detects automated reconnaissance using WMI or PowerShell to perform broad queries for system environment, security products, network adapters, software, and hardware attributes. The detection focuses on clusters of distinct WMI reconnaissance categories occurring within a 15-minute window, which is often indicative of pre-C2 profiling by adversaries.
This rule detects potential DLL sideloading activity where legitimate, signed binaries (such as COTFileReadApp.exe or DeElevate64.exe) are executed from non-standard directories (e.g., AppData, Temp, Downloads) while loading specifically identified malicious or sideloaded DLLs. The detection identifies patterns where these binaries operate outside their expected vendor installation paths, indicating a likely attempt to hijack execution flow.
This rule detects potential exploitation of the Oracle PeopleSoft PSEMHUB component vulnerability (CVE-2026-35273). It identifies suspicious POST requests to the PSEMHUB HttpListeningConnector servlet, including obfuscated URL paths, followed by the creation of suspiciously named .jsp or .jspx files in the PSEMHUB.war application directory, which is indicative of a web shell deployment.
This rule detects potential credential stuffing attacks by monitoring high-volume authentication attempts against web application login endpoints. It specifically flags scenarios where a high number of unique source IP addresses interact with a login endpoint (e.g., /login, /signin) within a short window, which is characteristic of automated, distributed credential stuffing tools using proxy networks to rotate IPs.
Detects high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects instances where a process contacts multiple distinct AI-provider domains within a short time frame while simultaneously performing suspicious operations, such as accessing the LSASS memory, executing process injection, or establishing WMI persistence. This pattern is indicative of a potential 'ClosedQuorum' adversary behavior involving data exfiltration or AI-assisted malicious activity.
Detects the execution of known Windows 'Living-off-the-Land' binaries (rundll32.exe, regsvr32.exe, mshta.exe) when they originate from web browsers or office productivity applications, or when they are executed with command-line arguments indicative of network resource loading, remote scripting, or code execution bypasses.
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