Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects suspicious sign-in attempts to Microsoft services (login.microsoftonline.com, graph.microsoft.com, outlook.office365.com) that occur within 30 minutes of a user clicking on a URL associated with these services. The sign-in is considered suspicious if it originates from a user agent commonly used by automated tools (e.g., axios, curl, python-requests, httpclient, Go-http-client) and is flagged with a 'atRisk' or 'high' risk level by Azure AD. This combination suggests a potential credential compromise following a phishing attempt, where an attacker might be using automated tools to leverage stolen credentials.
Detects anomalous non-interactive OAuth token requests against Microsoft Graph that claim multi-factor authentication (MFA) satisfaction from unmanaged devices. This behavior is indicative of Adversary-in-the-Middle (AiTM) token replay attacks, where captured session tokens are reused by an attacker to bypass authentication controls, consistent with tactics used by threat actors like Storm-2755 (Payroll Pirate).
Detects OAuth consent grants or permission additions in Microsoft Entra ID (Azure AD) audit logs that occur in conjunction with device login flow artifacts. This pattern is indicative of 'ConsentFix' or device code phishing attacks, where users are manipulated into authorizing malicious applications, potentially bypassing MFA requirements by using the device code flow.
Detects instances where a shell interpreter (bash or sh) accesses sensitive cloud and environment configuration files, specifically when initiated by parent processes associated with IDE-integrated development tools or AI assistants (claude, cursor, copilot-cli). This behavior suggests potential unauthorized access to credentials or environment variables.
Detects MCP (Model Context Protocol) server processes or developer tools spawned by IDE extensions performing environment variable enumeration to access cloud credentials (e.g., AWS, Azure, GCP, GitHub tokens) followed by anomalous outbound network connections, indicating potential exfiltration of sensitive developer environment secrets.
Detects activity associated with the 'MiniBrowse.exe' process, which exhibits behaviors characteristic of unauthorized browser credential and cookie harvesting. This includes targeting browser 'Login Data' files, accessing cookies, attempting to interact with legitimate browser processes (chrome.exe, msedge.exe) via cross-process operations, and writing logs to 'edgeLog.txt'.
Detects instances where a process that is not a known web browser (specifically excluding chrome.exe and msedge.exe) attempts to access sensitive browser files such as Login Data, Cookies, or Local State. This behavior is indicative of unauthorized attempts to steal stored web credentials, commonly associated with infostealer malware or browser credential theft tools.
This rule detects potential device code phishing attempts by correlating URL click events with sign-in logs using the 'deviceCode' authentication protocol. It specifically looks for successful or failed sign-ins (result types 0, 50074, 50076, 500121) that occur after a user clicks on a URL.
This rule detects potential session token theft or replay attacks by identifying non-interactive sign-in events that occur from a different IP or geographic location than the user's most recent successful MFA-authenticated interactive session. It flags cases where a non-interactive token is used within a short timeframe (1 hour) of an interactive session from a different location, which may indicate the exfiltration and subsequent use of session cookies or OAuth tokens.
Detects potential Pass-the-Hash (PtH) activity by identifying NTLM Type 3 logons where the account domain originates from outside the local or known corporate domain. The rule specifically excludes system-related accounts such as ANONYMOUS LOGON, WORKGROUP, and NT AUTHORITY, focusing on attempts to authenticate against internal resources using potentially forged or captured credentials.
Detects node.exe accessing sensitive SSH configuration and key files (id_rsa, id_ed25519, id_ecdsa, known_hosts, authorized_keys) within the user's .ssh directory. This behavior is associated with the Miasma and MYRA infostealers identified in the Polymarket Trap npm supply chain attack campaign, which exfiltrate developer credentials.
This rule detects suspicious activity related to accessing or dumping the NTDS.dit file, which contains Active Directory credential information. It looks for process creation events involving tools commonly used for NTDS.dit extraction (e.g., ntdsutil, secretsdump), file access events on NTDS.dit paths, and privilege use (SeBackupPrivilege, SeRestorePrivilege, SeDebugPrivilege) often associated with credential dumping.
This rule detects potential Golden Ticket attacks by looking for multiple successful Kerberos authentication events (EventID 4624) with LogonType 3 (network logon) and a specific TicketEncryptionType (0x17), originating from the same IP address and targeting the same user, within a short timeframe and with a long ticket lifetime. A Golden Ticket attack involves an adversary forging Kerberos Ticket Granting Tickets (TGTs) to gain unauthorized access to resources.
This rule detects potential Kerberoasting attacks by identifying a high number of Kerberos Ticket-Granting Service (TGS) requests (EventID 4769) for Service Principal Names (SPNs) that are encrypted with RC4 (indicated by TicketOptions containing '0x40810000'). A threshold of 15 or more TGS requests from a single IP address for a target user is used to flag suspicious activity.
Detects the AWS CLI being spawned by processes associated with AI coding extensions (e.g., VS Code extension hosts, Cursor, Windsurf) while executing commands indicative of cloud credential discovery or harvesting (e.g., sts, get-caller-identity, configure export). This activity is indicative of a supply chain compromise or exploitation where an adversary leverages an AI coding tool environment to access cloud credentials stored on the developer's workstation.
Detects unauthorized execution of AWS CLI commands within a shell spawned by Amazon Q or AWS language server processes. This activity typically involves the 'aws sts get-caller-identity' command being piped to 'curl' for remote exfiltration of cloud credentials, a behavior associated with the exploitation of CVE-2026-12957 in MCP auto-execution.
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
Detects unauthorized processes attempting to access, modify, or create web browser data files such as 'Login Data' (credentials), 'Cookies', and 'Local State'. This rule identifies potential credential theft activity where non-browser processes interact with sensitive browser storage files, which is a common tactic used by info-stealing malware.
Detects the creation of log or data files in temporary directories (e.g., AppData, Temp) by non-standard processes. This behavior is indicative of keylogging activity performed by malware families such as Atlas RAT and Gh0stRAT, commonly associated with the threat actor TA4922.
Detects BQTLock ransomware activity where the BQT.exe process accesses browser credential stores (Chrome, Firefox, Opera) and writes the extracted data to a temporary file at C:\Windows\Temp\bqt_passwords.txt.
Detects Node.js processes attempting to access sensitive files or environment variables associated with Claude AI (e.g., Anthropic API keys, .claude configuration files), which may indicate credential harvesting activity by malicious code.
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