Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Zscaler ZIA logs identified as Advanced Threat Protection events, specifically targeting URL categories like Phishing and WebSpam, or traffic classified as Advanced Security Risk. The rule aggregates these events by user to identify potential malicious activity, flagging sessions where threats were allowed as higher severity.
This rule detects high-frequency security alerts from Zscaler ZIA indicating that a single source IP has encountered three or more distinct threat signatures within a 15-minute window. This behavior is indicative of a host engaging in malicious activity, such as automated scanning, malware communication attempts, or accessing infrastructure associated with multiple malicious categories.
KQL Query
Detects a significant increase in Zscaler Risk360 risk scores or the emergence of new high-impact security insights. This rule monitors for category-specific risk spikes (External Attack Surface, Compromise, Lateral Propagation, or Data Loss) that exceed a defined delta threshold or are flagged as Critical/High severity, serving as a posture-based alert for security investigation.
Detects instances where Netskope Advanced Threat Protection (ATP) identifies a malicious file during a user-initiated upload or download operation.
Detects instances where Netskope Advanced Threat Protection (ATP) identifies a malicious file during a user-initiated upload or download operation.
This rule detects suspicious Microsoft Graph API activity involving the enumeration of user accounts within an organization. It specifically monitors for queries targeting personnel in sensitive roles such as payroll, finance, HR, and administration, as well as bulk enumeration attempts. The detection logic also flags usage of the axios HTTP library, a common tool in such reconnaissance campaigns, and aggregates results by source IP/ASN to identify coordinated efforts, such as those associated with the Storm-2755 threat actor.
Detects potentially unauthorized or suspicious file activities such as bulk downloads, external file sharing, or CASB policy violations monitored by Zscaler ZIA, which may indicate data exfiltration or policy non-compliance.
Detects potentially unauthorized or suspicious file activities such as bulk downloads, external file sharing, or CASB policy violations monitored by Zscaler ZIA, which may indicate data exfiltration or policy non-compliance.
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 Adversary-in-the-Middle (AiTM) activity by correlating network events indicating a connection to a known phishing domain with subsequent suspicious authentication behavior. Specifically, it identifies sessions associated with non-corporate IP addresses that show evidence of token reuse (e.g., multiple distinct IP addresses for the same session identifier) occurring within a short window after accessing a phishing portal.
Summarizes Zscaler NSSWeblog transactions where DeviceAction was Allowed but Zscaler still recorded a malware/threat verdict (ClickFix, MalURL, Trojan.Gen families), broken down by user, threat name, and malware category for triage.
This rule detects anomalous activity involving the legacy Microsoft Azure AD Graph API (graph.windows.net) originating from users who lack corresponding entries in standard Entra ID (AuditLogs) sign-in or management activity logs. A high frequency of these undocumented API calls (more than 5 in an hour) from a specific user and IP address indicates potential unauthorized reconnaissance or access attempts attempting to bypass standard audit logging.
This rule detects anomalous activity involving the legacy Microsoft Azure AD Graph API (graph.windows.net) originating from users who lack corresponding entries in standard Entra ID (AuditLogs) sign-in or management activity logs. A high frequency of these undocumented API calls (more than 5 in an hour) from a specific user and IP address indicates potential unauthorized reconnaissance or access attempts attempting to bypass standard audit logging.
Summarizes Zscaler NSSWeblog transactions where DeviceAction was Allowed but Zscaler still recorded a malware/threat verdict (ClickFix, MalURL, Trojan.Gen families), broken down by user, threat name, and malware category for triage.
This rule detects non-interactive sign-in events involving the 'Microsoft Authentication Broker' where the authentication was performed using only single-factor authentication and originated from a device that is not recognized or lacks trust information (unmanaged/unknown device). This pattern is consistent with token replay attacks or session hijacking, where an adversary uses stolen authentication artifacts to access resources without undergoing standard multi-factor authentication.
Detects repeated sign-in attempts using unrecognized, malformed, or blank Application IDs (AppId). This often indicates automated reconnaissance or brute-force attempts targeting applications or service principals within the Azure Active Directory environment.
Detects potentially malicious use of the device code authentication flow in Entra ID sign-in logs. The rule correlates device code usage with indicators of suspicious activity, such as rare User-Agent strings (e.g., 'python-requests') often used in phishing/relay toolkits, or sign-ins flagged by Azure AD Identity Protection as risky. It includes exclusions for known first-party Azure CLI and PowerShell clients to minimize noise from legitimate administrative activity.
This rule detects a correlation between an unauthorized IAM user access event and the subsequent execution of cryptocurrency mining tools within the same AWS account within a one-hour window. This is a strong indicator of an adversary leveraging compromised cloud credentials to perform resource hijacking.
Detects Microsoft 365 sign-in patterns indicative of an adversary bypassing Conditional Access device compliance requirements using an edge appliance proxy. The rule identifies successful authentication sessions from non-compliant or unmanaged devices that satisfy Conditional Access, often involving impossible travel or multiple source IPs, suggesting the use of an intermediary infrastructure to masquerade as a trusted location.
This rule monitors for security alerts related to Azure AI services, specifically detecting credential theft attempts and LLM jailbreak attempts that have been blocked or detected by Azure's built-in content filtering mechanisms.
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