Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects credential stuffing in Entra ID sign-in logs: one source IP failing against many distinct accounts within an hour, then succeeding on a small number of them.
Detects credential stuffing in Entra ID sign-in logs: one source IP failing against many distinct accounts within an hour, then succeeding on a small number of them.
Detects credential stuffing in Entra ID sign-in logs: one source IP failing against many distinct accounts within an hour, then succeeding on a small number of them.
Detects credential stuffing in Entra ID sign-in logs: one source IP failing against many distinct accounts within an hour, then succeeding on a small number of them.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
Detects credential stuffing in Entra ID sign-in logs: one source IP failing against many distinct accounts within an hour, then succeeding on a small number of them.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
This rule detects potential credential stuffing attacks by monitoring high-volume authentication attempts against web application login endpoints. It specifically flags scenarios where a high number of unique source IP addresses interact with a login endpoint (e.g., /login, /signin) within a short window, which is characteristic of automated, distributed credential stuffing tools using proxy networks to rotate IPs.
Detects a sequence of authentication activity indicative of a credential stuffing attack. The rule identifies a burst of failed password-only authentication attempts followed by a successful authentication for the same account. It requires that the IP address used for the successful login overlaps with the set of IPs that initiated the failed attempts, effectively filtering out typical user noise and highlighting potentially malicious activity where an attacker has identified a valid credential.
Detects a high volume of HTTP POST requests to common login endpoints (e.g., /login or /wp-login.php) from a single source IP address within a short time frame, which is indicative of a credential stuffing or automated brute-force attack.
Detects potential credential stuffing activity by monitoring for a high volume of HTTP 401 (Unauthorized) or 403 (Forbidden) responses originating from a single source IP address within a 60-second window, specifically targeting URIs containing the path 'login'.
Detects credential-stuffing campaigns that employ AI/ML-tuned inter-request timing jitter to bypass traditional rate-limiting and fixed-interval bot detection, specifically flagging interactive or network logon failures on Windows hosts.
Detects a credential stuffing attack characterized by a high volume of failed authentication attempts from a small set of source IP addresses followed by a successful authentication within a short timeframe. This behavior is indicative of an attacker attempting to use valid credentials obtained from infostealer logs or credential leaks to gain unauthorized access to accounts.
This rule detects potential RDP brute force and password spraying attacks by correlating Windows Event ID 4625 (failed logins) and 4624 (successful logins) via RDP (Logon Type 10). It monitors for high volumes of failed attempts across multiple accounts or high volume of failed attempts from a single source, followed by successful authentication from the same source.
The following analytic identifies instances where CrushFTP has blocked access due to exceeding the maximum number of simultaneous connections from a single IP address. This activity may indicate brute force attempts, credential stuffing, or automated attacks against the CrushFTP server. This detection is particularly relevant following the discovery of CVE-2025-31161, an authentication bypass vulnerability in CrushFTP versions 10.0.0 through 10.8.3 and 11.0.0 through 11.3.0.
Detects high-volume credential brute-forcing activity targeting Dahua IP camera administrative interfaces (Ports 80/37777). The rule identifies a pattern of multiple connection failures across multiple distinct targets followed by a successful connection, which is highly characteristic of automated credential stuffing or password spraying attacks against embedded IoT devices.
Detects high-volume authentication failures originating from a single source IP targeting multiple unique user accounts, indicative of password spraying or credential stuffing attacks against cloud identity providers.
Detects coordinated credential stuffing campaigns originating from shared IP infrastructure. The rule identifies patterns where multiple distinct accounts are targeted with failed sign-in attempts, characterized by rapidly rotating user-agent/device fingerprints while remaining under standard per-account and per-IP throttling limits. It focuses on the combination of high unique account counts, rotating user-agents, and sustained activity over a specific time window.
Detects credential-stuffing campaigns that employ AI/ML-tuned inter-request timing jitter to bypass traditional rate-limiting and fixed-interval bot detection, specifically flagging interactive or network logon failures on Windows hosts.
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