Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects network connections to known JeetBot infrastructure domains and IP addresses. The rule specifically identifies potential exfiltration of Twitch OAuth tokens via URL parameters or interaction with known token-collection proxy endpoints, which are associated with the JeetBot/Twitch Enhanced Viewer credential harvesting campaign.
No description available.
Detects potential N0va-style phishing or token-exchange abuse where a user completes a device-code authentication flow, followed immediately by an access token usage from a different IP address or device. This sequence indicates an adversary has captured the resulting token/session and is attempting to bypass multi-factor authentication (MFA) to gain unauthorized access to cloud resources.
This rule detects potential keystroke logging activities on Android devices by monitoring the 'UniversalInputMonitor' accessibility service. This service is abused by the RatHat malware family and similar threats to capture user input, including passwords, PINs, and text entered into masked fields, by intercepting accessibility text events.
Detects Kerberos TGT or TGS requests that either exhibit a suspicious combination of ticket flags (Forwardable + Proxiable + Renewable) when associated with high-value targets, unusual accounts, or off-hours activity, or utilize the weak RC4-HMAC encryption type, both of which are indicative of ticket manipulation and credential theft.
Detects access to Gitea secrets and configuration (app.ini, JWT secrets, SSH host keys, deploy keys) via file writes/renames or process command lines referencing those paths alongside Gitea, matching the secret-extraction tradecraft observed in the Red Heron campaign.
Detects access to Gitea secrets and configuration (app.ini, JWT secrets, SSH host keys, deploy keys) via file writes/renames or process command lines referencing those paths alongside Gitea, matching the secret-extraction tradecraft observed in the Red Heron campaign.
This rule monitors for suspicious OAuth Device Code flow authentication attempts in Azure AD sign-in logs. It detects activity involving the device code protocol combined with specific error flags or indicators of potentially compromised or non-compliant devices (such as missing device IDs, non-compliant status, or empty trust types), which are indicative of Adversary-in-the-Middle (AiTM) phishing or token interception attacks.
Detects signs of Adversary-in-the-Middle (AiTM) phishing attacks targeting cloud authentication. The rule monitors for access to suspicious domain patterns often used in AiTM phishing kits, specific MFA interruption errors (50074/50140) characteristic of proxy-based flows, and rapid successful logins from different IP addresses within a 15-minute window, suggesting session token theft and replay.
Detects network traffic (TLS SNI or HTTP Host) to known domains associated with Adversary-in-the-Middle (AiTM) phishing campaigns. These domains mimic passkey, SSO, or account security portals to steal credentials and session cookies.
This rule detects a suspicious Azure sign-in sequence, identified by error code 50074 (User failed MFA) followed by 50140 (This error occurred due to 'Keep me signed in' interrupt when the user was authenticating). This pattern is indicative of an Adversary-in-the-Middle (AiTM) phishing attack where the attacker is attempting to bypass MFA or manipulate session persistence after capturing initial credentials.
Detects outbound network traffic from internal devices interacting with Dahua Easy4IP cloud relay services, specifically identifying device resolution requests, probe actions, and the submission of WSSE authentication headers (UsernameToken and PasswordDigest) to the cloud relay host.
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 rapid, sequential identity-validation API calls (such as GetCallerIdentity, GetSessionToken, or AssumeRole) performed across a large number of distinct AWS access keys from a single source within a short time window. This pattern is indicative of automated tooling validating a harvested corpus of AWS access keys to identify active credentials.
Detects rapid, sequential identity-validation API calls (such as GetCallerIdentity, GetSessionToken, or AssumeRole) performed across a large number of distinct AWS access keys from a single source within a short time window. This pattern is indicative of automated tooling validating a harvested corpus of AWS access keys to identify active credentials.
Detects the use of command-line tools like find and grep to recursively search the filesystem for files containing sensitive information, such as configuration files, environment variables, database credentials, and digital wallet keys. This behavior is indicative of an attacker performing automated discovery of credentials and secrets.
Detects the use of the Rubeus tool for Kerberos-based credential attacks, specifically Kerberoasting, TGT delegation abuse, and Pass the Ticket, by monitoring process command line arguments for characteristic flags associated with the Rubeus binary.
Detects instances where browser processes or related credential files are accessed or targeted by process termination (e.g., taskkill.exe) followed by attempts to access sensitive files like Login Data, logins.json, or key4.db. This pattern is indicative of credential theft from web browsers.
Detects instances where browser processes or related credential files are accessed or targeted by process termination (e.g., taskkill.exe) followed by attempts to access sensitive files like Login Data, logins.json, or key4.db. This pattern is indicative of credential theft from web browsers.
This rule detects high-frequency account and email address enumeration attempts. It monitors syslog data for SMTP commands such as VRFY, EXPN, or RCPT TO, and analyzes Microsoft Entra ID (SigninLogs) for authentication failures specifically associated with error code 50034 (user not found). Both behaviors are indicative of an adversary attempting to validate user identities within an environment, often as a precursor to targeted phishing or brute-force attacks.
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