Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential credential stuffing attempts against a Fortinet FortiGate SSL VPN portal. It triggers when an external source performs multiple HTTP POST requests to the /remote/login endpoint within a short period, accompanied by the FortiGate-specific header, which is indicative of automated brute-force or credential stuffing activity associated with the 'FortiBleed' campaign pattern.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
This rule detects potential credential stuffing or brute force attacks against a SonicWall VPN device. It identifies scenarios where a single source IP experiences multiple failed authentication attempts within a 15-minute window, followed by at least one successful authentication on the same destination host.
Detects high-frequency failed sign-in attempts (10+ failures in 15 minutes) targeting the Okta Admin Console. The rule filters out common expected failure modes such as password expiration, account lockouts, and known helpdesk account activity to prioritize potential brute-force or credential-stuffing attacks against privileged administrative accounts.
This rule detects potential credential stuffing or brute force attacks against a SonicWall VPN device. It identifies scenarios where a single source IP experiences multiple failed authentication attempts within a 15-minute window, followed by at least one successful authentication on the same destination host.
Detects high volumes of authentication failures within Okta, characterized by a single source IP address targeting a large number of distinct user accounts. This behavior is indicative of automated credential attacks, such as password spraying or credential stuffing, designed to discover valid credentials or exploit reused passwords while attempting to evade account lockout thresholds.
This rule detects potential brute-force or credential stuffing attempts against web application authentication endpoints by monitoring patterns of success and failure. It aggregates requests over 5-minute intervals, calculating a risk score based on high volumes of authentication failures relative to successful requests from individual source IPs targeting sensitive API paths (e.g., auth, session, login, token).
This rule monitors outbound network connections from internal hosts to specific ports associated with database management (MySQL: 3306) and service orchestration/discovery (Nacos: 8848, 9848). It aggregates connection counts and distinct target IP addresses by source host and initiating process. High volumes of connections to these specific service ports from unexpected processes may indicate unauthorized discovery, brute-force attempts, or lateral movement.
This rule detects potentially malicious authentication patterns by correlating multiple failed login attempts across geographically diverse source IPs followed by a successful login from a source IP that has not been seen in the previous 90 days. This pattern is indicative of automated credential stuffing or brute force attacks targeting user accounts.
This rule detects potential brute-force or credential stuffing attempts against web application authentication endpoints by monitoring patterns of success and failure. It aggregates requests over 5-minute intervals, calculating a risk score based on high volumes of authentication failures relative to successful requests from individual source IPs targeting sensitive API paths (e.g., auth, session, login, token).
This rule detects potential brute-force or credential stuffing attempts against web application authentication endpoints by monitoring patterns of success and failure. It aggregates requests over 5-minute intervals, calculating a risk score based on high volumes of authentication failures relative to successful requests from individual source IPs targeting sensitive API paths (e.g., auth, session, login, token).
This rule detects potential brute force or credential stuffing attacks against Azure AD by identifying multiple failed sign-in attempts followed by a successful sign-in from the same user and IP address within a short time frame (1 minute). It specifically looks for scenarios where the successful sign-in occurs after the failed attempts and involves different applications, excluding common Office 365 services to reduce noise.
Detects high-frequency authentication failure events targeting multiple unique user accounts from the same source IP address within a 10-minute window. This behavior is indicative of password spraying or credential stuffing attacks against Azure Active Directory (Microsoft Entra ID). The rule specifically monitors for common error codes related to incorrect passwords or account lockout conditions.
This rule detects and summarizes Kerberos authentication ticket requests (EventID 4765) and Kerberos authentication ticket request failures (EventID 4766) by subject username on an hourly basis. A high volume of these events for a single user could indicate credential stuffing, brute-force attempts, or other authentication-related anomalies.
Detects an unusually high volume (100 or more within an hour) of API calls (POST, DELETE, PUT methods to URIs containing 'api') originating from a single IP address. This activity could indicate various malicious behaviors such as brute-force attacks, credential stuffing, web application attacks, or a denial-of-service attempt against the API endpoint.
This rule detects potential automated credential stuffing attempts followed by successful authentication and subsequent access to sensitive/privileged APIs within Azure/Entra ID environments. It correlates multiple failed login attempts for service-oriented account names (e.g., svc, api, bot) with a successful login from the same user shortly thereafter, followed by privileged API operations (e.g., KeyVault secret access, user management) within a short time window.
This rule detects potential brute force or credential stuffing attacks against Azure AD by identifying multiple failed sign-in attempts followed by a successful sign-in from the same user and IP address within a short time frame (1 minute). It specifically looks for scenarios where the successful sign-in occurs after the failed attempts and involves different applications, excluding common Office 365 services to reduce noise.
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