Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects non-interactive Microsoft Entra ID service principal or managed identity sign-in events originating from an IP address, ASN, or country that has not been historically associated with that specific service principal. This behavior may indicate the use of compromised service principal credentials or stolen access tokens from adversary-controlled infrastructure.
Detects potential lateral movement by users who have recently been flagged for credential theft or infostealer activity. The rule correlates initial security alerts with subsequent Windows logon events (RDP, network/WinRM) or SMB share access, identifying users connecting to multiple distinct destinations within a 48-hour window.
Detects anomalous sign-in activity for service principals (non-interactive accounts) where the same application authenticates from multiple distinct countries within a 24-hour window. This behavior often indicates the unauthorized use of compromised service principal credentials, such as client secrets or certificates, from distributed attacker-controlled infrastructure.
Detects potential abuse of Azure Cloud Shell backing storage (acsCloudShell) to stage or persist malicious scripts following an Azure AD session compromise. Adversaries may use this storage to blend in with legitimate engineering operations while maintaining persistent access to their tooling.
Detects instances where an IAM user or role attempts to assume a role in a different AWS account (Cross-Account) without providing a valid ExternalID. This often indicates unauthorized attempts to access or abuse cross-account trust relationships, which is a common technique for lateral movement or privilege escalation in cloud environments.
Detects a suspicious pattern where a user authenticates to a remote access portal (like Citrix or VPN) without multi-factor authentication (MFA) or with an existing risk flag, followed by a surge in file activity (creation, modification, or renaming of >500 files or >200 distinct files) on the same account within a 24-hour window, potentially indicating compromised credential usage for staging data for exfiltration or ransomware.
This rule detects the installation or execution of common Remote Monitoring and Management (RMM) tools (e.g., AnyDesk, ScreenConnect, Atera, Splashtop, TeamViewer) on Windows endpoints within a 4-hour window of associated cloud identity risk activity (such as risky sign-ins, MFA changes, or privilege grants). It filters out legitimate activity initiated via standard software management pipelines (e.g., SCCM, Intune) to identify potential unauthorized use of remote access software by adversaries following account compromise.
Detects impossible-travel activity where a single user account authenticates successfully from multiple distinct countries or IP addresses within a short 15-minute window. This behavior is highly indicative of potential session hijacking or the concurrent use of a stolen session token by both an attacker and a legitimate user.
Detects instances where the Windows Terminal application (or related processes like OpenConsole) spawns suspicious command-line utilities such as PowerShell, CMD, curl, or certutil with indicators of potential download activity or command-line obfuscation. This pattern is often indicative of interactive adversary activity attempting to stage tools or execute payloads.
Detects successful user authentication to Microsoft Entra ID or Exchange Online using legacy authentication protocols (e.g., IMAP, POP3, SMTP AUTH, Exchange ActiveSync) that bypass modern MFA enforcement. The rule specifically alerts when these legacy sign-ins originate from a source IP address not previously associated with that specific user account, indicating potential credential abuse.
This rule detects potential session hijacking by correlating endpoint-based detections of known infostealer malware (e.g., Vidar, Lumma, Redline) with a subsequent cloud Identity Provider (IdP) login for the same user. The correlation specifically focuses on instances where the IdP authentication originates from an IP address different from the infected host, suggesting the use of stolen session cookies by an external actor to access corporate resources.
Detects the creation or modification of mailbox inbox rules that configure forwarding or redirection to external addresses, or rules that automatically delete or move messages based on sensitive keyword filters (e.g., 'invoice', 'password'). It specifically looks for indicators of mailbox hiding (hidden rules) which are frequently used by attackers to maintain persistence and conceal activity, particularly following unauthorized access or token theft.
Detects successful Azure AD sign-in events that are flagged with a medium or high risk level and identified as anomalous by Azure AD Identity Protection. The specific combination of successful authentication alongside risk details like unfamiliar features, anonymized IP addresses, or malicious IP addresses is highly indicative of potential cloud account takeover, potentially following session token theft or infostealer activity.
Detects an account performing a mass download or synchronization of files from SharePoint or OneDrive within a 30-minute window, occurring within two hours of a medium or high-risk Azure AD sign-in event. This pattern is indicative of potential account takeover and subsequent data exfiltration by an adversary using harvested credentials.
Detects a multi-stage activity chain indicative of infostealer malware, including reading the browser 'Local State' file (containing the master key), accessing a browser process (likely for memory dumping or token extraction), and initiating an immediate outbound network connection to an external destination.
Detects instances where a file is downloaded or exfiltrated, followed by the deletion or alteration of its version history within a 7-day window. This behavior is consistent with post-theft activities aimed at obfuscating access logs or sanitizing stolen data by removing original versioning markers, often observed in insider threat or compromised account scenarios.
Detects the modification of Microsoft IIS configuration to disable HTTP logging using the appcmd.exe utility. This technique is often used by adversaries to impair security monitoring and evade detection after compromising a web server.
Detects the execution of PowerShell with suspicious command-line patterns indicative of obfuscation or malicious intent, including encoded commands, Base64 decoding, IEX combined with common download cmdlets, and specific obfuscation techniques like backtick concatenation, character casting, or variable concatenation.
Detects the abuse of the Windows Background Intelligent Transfer Service (BITS) via the bitsadmin command-line tool or PowerShell's Start-BitsTransfer to download files (such as .exe, .dll, or .ps1) or facilitate potential persistence. Adversaries use these methods to transfer malicious payloads stealthily in the background or to maintain persistence on a compromised host.
Detects the Kothamine post-installation technique where npm/node spawns PowerShell to reflectively load a .NET assembly stager into memory. This behavior is followed by the PowerShell process spawning anomalous instances of RuntimeBroker.exe or svchost.exe. These spawned processes exhibit suspicious characteristics, such as executing from non-standard file paths, having missing command-line arguments (like the required '-k' for svchost), or having an illegitimate parent process (powershell.exe) instead of standard system parents like services.exe or wininit.exe.
The following analytic identifies cloud instances being modified by users who have not previously modified them. It leverages data from the Change data model, focusing on successful modifications of EC2 instances. This activity is significant because it can indicate unauthorized or suspicious changes by potentially compromised or malicious users. If confirmed malicious, this could lead to unauthorized access, configuration changes, or potential disruption of cloud services, posing a significant risk to the organization's cloud infrastructure.
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