Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous authentication behavior where the same session token or identifier is utilized by multiple distinct IP addresses or User-Agent strings within a short timeframe. This behavior is indicative of Adversary-in-the-Middle (AiTM) attacks, such as those employing Evilginx, where an attacker intercepts and replays stolen session cookies to bypass standard authentication and MFA controls.
Detects potential vishing or account takeover precursor activity where an external or guest Microsoft Teams user, impersonating IT or Help Desk support, communicates with a user who subsequently modifies their credentials or MFA configuration within the same 24-hour period.
Detects instances where a process not associated with standard web browsers accesses, copies, or modifies sensitive browser files such as cookies, local storage, or session tokens. This behavior is highly indicative of information-stealer malware (e.g., Vidar, Lumma, RedLine) attempting to exfiltrate session data for account hijacking.
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 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 the creation of a Volume Shadow Copy followed by an attempt to access or copy sensitive files, specifically the NTDS.dit database or the SYSTEM registry hive, from that shadow copy. This behavior is indicative of an attempt to perform offline credential theft.
Detects unauthorized processes, excluding standard web browsers, accessing sensitive browser files such as Login Data, Cookies, Web Data, and Local State. This activity is indicative of credential harvesting malware attempting to steal authentication cookies, saved passwords, or browser profiles.
Detection of network traffic patterns associated with the NovaCookies Adversary-in-the-Middle (AiTM) phishing kit. The rules monitor for DNS queries for .vu domains, HTTP requests to lookalike Microsoft 365 login pages hosted on .vu domains, POST requests containing credential data, and the receipt of specific session cookies (ESTSAUTH) indicative of successful AiTM session interception.
This rule detects HTTP POST requests to the 'wp-login.php' endpoint of a WordPress installation where the 'log' (username) and 'pwd' (password) fields are both set to 'admin'. This is a common signature for automated brute-force or credential-stuffing attacks targeting default administrator credentials.
Detects anomalous network polling patterns consistent with 'EvilTokens' or similar adversary-in-the-middle (AiTM) OAuth phishing kits. The rule identifies web browsers performing high-frequency, low-interval polling (3-6s) against non-reputable/unseen domains (the attacker-controlled status endpoint) immediately preceding or following successful Microsoft OAuth device-code authentication sequences.
Detects PamStealer-style browser credential theft on macOS. The detection logic identifies the forced termination of browser helper processes using 'pkill' (which releases SQLite file locks) followed by the execution of a 'KcHelper' binary that uses specific environment markers (e.g., KC_PASS) to bypass keychain authorization prompts and steal stored browser credentials.
Detects unauthorized processes requesting memory access to lsass.exe with read permissions commonly associated with credential dumping techniques like Mimikatz. It identifies remote handle requests to lsass.exe, which are frequently used by tools deployed via network services or remote execution methods to extract credentials from memory.
Detects OAuth application consent events in Entra ID where the application display name mimics legitimate services like Salesforce or Data Loader while requesting high-risk API scopes (full_access, offline_access, api). This behavior is characteristic of phishing-driven OAuth grant campaigns, such as those observed by the ShinyHunters group.
Detects the execution of TruffleHog, an automated secret-scanning CLI tool, often utilized by threat actors to harvest sensitive credentials from local filesystems, repositories, environment variables, or CI/CD configuration files following unauthorized access.
Detects unauthorized access to CRM platforms (Salesforce) using Salesloft or Drift OAuth tokens, where the source IP address does not match the known legitimate service provider IP ranges. This behavior is indicative of potential token theft or misuse, particularly relevant to supply-chain campaign activities.
Detects a pattern associated with ShinyHunters/UNC6040, where a user authorizes a new or rarely-used OAuth connected application shortly after performing a help-desk initiated password reset or MFA re-enrollment, originating from a different geographic location.
Detects anomalous engineering account activity associated with supply-chain compromise, specifically identifying the generation of access tokens or retrieval of secrets followed by unauthorized changes to CI/CD pipeline configurations or secret stores in platforms like GitHub, JFrog Artifactory, or BrowserStack.
Detects unauthorized abuse of the OAuth 2.0 device authorization grant flow in Salesforce environments, commonly used by threat actors like ShinyHunters (UNC6240) to gain programmatic access. Attackers register malicious connected apps to impersonate legitimate tools, then use social engineering (vishing) to trick victims into approving device codes. This rule flags token issuance from non-allowlisted connected apps using the device_code grant type.
Detects anomalous engineering account activity associated with supply-chain compromise, specifically identifying the generation of access tokens or retrieval of secrets followed by unauthorized changes to CI/CD pipeline configurations or secret stores in platforms like GitHub, JFrog Artifactory, or BrowserStack.
Detects OAuth application consent requests that combine broad API access scopes with persistence-enabling scopes (e.g., offline_access or refresh_token). This pattern is consistent with OAuth consent phishing attacks, where adversaries attempt to gain non-interactive, long-term access to an organization's cloud environment via malicious connected applications.
Detects a burst of Kerberos TGS-REQ (Ticket-Granting Service Request) messages using RC4 encryption (etype 0x17) over UDP or TCP port 88. A high volume of these requests from a single source within a short timeframe is indicative of Kerberoasting, a technique where an attacker requests service tickets to perform offline password cracking of service account credentials.
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