Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects outbound network connections (HTTP/TLS) from internal hosts to a known malicious IP address associated with Adversary-in-the-Middle (AiTM) phishing infrastructure, specifically targeting Microsoft 365 credential and session cookie theft.
Detects outbound network connections (HTTP/TLS) from internal hosts to a known malicious IP address associated with Adversary-in-the-Middle (AiTM) phishing infrastructure, specifically targeting Microsoft 365 credential and session cookie theft.
Detects unauthorized processes attempting to read or manipulate local storage, session storage, or database files associated with messaging applications like Telegram and WhatsApp, or email clients like Outlook and Thunderbird. This behavior is indicative of credential or data theft by malicious software or unauthorized scripts.
Detects bulk read operations on AWS Secrets Manager or similar cloud secret stores where the accessed resources contain keywords related to cryptocurrency custody, private keys, or wallet material. This pattern is indicative of unauthorized exfiltration attempts by threat actors such as Slim Spider targeting digital asset infrastructure.
Detects instances where a process other than the legitimate Firefox browser executable loads the NSS (Network Security Services) libraries nss3.dll or mozglue.dll from the Firefox installation directory. This behavior is indicative of unauthorized attempts to decrypt saved browser credentials by interacting with Firefox-specific security modules, a technique commonly used by credential-stealing malware.
Detects non-browser processes accessing sensitive browser-stored credential and cookie databases concurrently with access to Discord local storage, which is a common behavior of information-stealing malware (e.g., x47.c) to aggregate credentials for exfiltration.
Detects the use of rundll32.exe to execute comsvcs.dll's MiniDump functionality against the LSASS process, a common technique for dumping credentials. The rule includes behavioral correlation by identifying the same user account executing this pattern on multiple devices within a one-hour window.
Detects the use of rundll32.exe to execute comsvcs.dll's MiniDump functionality against the LSASS process, a common technique for dumping credentials. The rule includes behavioral correlation by identifying the same user account executing this pattern on multiple devices within a one-hour window.
Detects activity related to potential browser credential theft, specifically targeting Chrome and Microsoft Edge. The rule monitors for the loading of a specific suspicious file, the presence of browser-specific decryption artifacts such as 'browser_decryption.log' or 'ProtectR3.dll', and process command-line arguments containing keywords like 'DecryptData' or 'Elevation Service' associated with browser credential extraction.
Detects anomalous, mass-access behavior targeting plaintext credential files, certificate stores, private keys, or password-manager databases located on general-purpose network shares. Such activity is often indicative of an adversary conducting discovery or collection of credentials for lateral movement and privilege escalation.
This rule detects potential Adversary-in-the-Middle (AiTM) activity by identifying a pattern where a successful multi-factor authentication sign-in event is quickly followed by another successful sign-in for the same user from a different IP address, device, or geographic location. This behavior is indicative of session cookie theft and replay, commonly associated with phishing toolkits like Evilginx or NovaCookies.
Detects high or medium severity security alerts related to Kerberos Golden Ticket forgery, as identified by Microsoft Defender for Identity. This rule filters for specific alert names indicative of forged TGTs minted from the krbtgt account, excluding generic or informational ticket anomalies.
Detects potential credential reuse attacks such as Pass-the-Hash, Pass-the-Ticket, or Overpass-the-Hash. The rule identifies a 'NewCredentials' logon (e.g., runas /netonly) followed by a network or remote interactive logon to a target system (such as a domain controller) by the same user, without an interactive logon session occurring between the events, which is indicative of using stolen credentials to move laterally.
Detects suspicious processes accessing cryptocurrency wallet data files or browser extension settings, characteristic of infostealer malware such as AMOS or GhostCode. The rule excludes common browser processes and legitimate wallet applications to identify unauthorized attempts to harvest wallet credentials, private keys, or seed phrases.
Detects the 'GhostCode' attack pattern where an adversary acquires a Primary Refresh Token (PRT) shortly after a successful OAuth device code authentication. This correlation identifies potential session hijacking or token theft resulting from an adversary-controlled device registration.
Detects a process accessing browser credential files (Login Data) followed by an outbound network connection to a suspicious exfiltration endpoint commonly associated with credential-stealing malware.
This rule detects processes other than known web browsers (Chrome, Edge, Firefox, Brave, Opera) accessing sensitive browser-related files (Login Data, Cookies, Web Data) and initiating an external network connection within 15 minutes. This behavior is highly characteristic of credential and session cookie theft, often utilized by info-stealing malware for subsequent session hijacking.
Detects network communication to specific API endpoints associated with the RatHat Android malware, which leverages accessibility services for overlay-based credential harvesting and data exfiltration.
Detects instances where a non-browser process accesses multiple distinct browser credential or session artifacts (such as Login Data, Cookies, or Local State) across different browser profiles in a short period. This behavior is indicative of credential harvesting activities, often associated with C2 frameworks or post-exploitation tools attempting to steal session cookies, 2FA backup codes, or saved passwords.
Detects processes attempting to open a handle to the Local Security Authority Subsystem Service (LSASS) process with access rights commonly associated with credential dumping. This detection focuses on identifying suspicious cross-process access requests originating from non-standard or non-authorized processes, such as those used by C2 frameworks like OnyxC2 for extracting cached Windows credentials.
These rules monitor for suspicious WordPress authentication activity, including brute force and credential spraying attacks targeting XML-RPC endpoints and the standard wp-login.php interface. The rule set includes detections for high-frequency login attempts and subsequent indicators of potential successful authentication.
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