Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential unauthenticated access or unauthorized configuration modifications to an AI agent management backend. It monitors HTTP logs for requests targeting configuration endpoints that lack proper authentication, specifically identifying attempts to retrieve sensitive information like Dify or Coze keys, or attempts to inject new agent configurations via unauthenticated POST requests.
This rule monitors for modifications to the PostgreSQL configuration file 'pg_hba.conf', specifically looking for changes that would enable 'trust' authentication, followed by successful database logins using that method within one hour. This behavior is indicative of an attacker modifying authentication rules to gain unauthorized, passwordless access to a database.
This rule detects potential persistence mechanisms in a PostgreSQL database by identifying the creation of a new shared library file (e.g., .so or .dll) within PostgreSQL plugin directories, followed by a modification to the PostgreSQL configuration files (postgresql.conf or postgresql.auto.conf) within a short 30-minute window. This behavior is indicative of an attacker registering a malicious shared library to be loaded upon database startup, a technique associated with PostGREShell-style post-exploitation.
Detects a sequence of events starting with a device code OAuth sign-in, followed within two hours by the creation or modification of inbox rules and high-frequency enumeration of email items (contacts, folders, messages, threads, people) via Microsoft Graph API. This behavior is indicative of post-compromise activity where an adversary uses OAuth device code grants to maintain access and subsequently automates inbox analysis or data harvesting.
This rule detects potential unauthenticated access or unauthorized configuration modifications to an AI agent management backend. It monitors HTTP logs for requests targeting configuration endpoints that lack proper authentication, specifically identifying attempts to retrieve sensitive information like Dify or Coze keys, or attempts to inject new agent configurations via unauthenticated POST requests.
Detects instances where a user account performs a device configuration change (such as updating compliance policies) followed by a potentially destructive operation (Wipe, Retire, or Delete) on the same device or entity within a 6-hour window. This behavior often suggests unauthorized administrative activity or a malicious insider attempting to disable security controls before removing access or destroying data.
This rule detects potentially malicious modifications to PostgreSQL configuration files or the creation of new library files (.so or .dll) by the PostgreSQL service process. It also flags when the PostgreSQL service process is initiated with command-line arguments referencing 'shared_preload_libraries', which can be abused to load arbitrary code or malicious extensions into the database engine.
This rule detects potentially malicious modifications to PostgreSQL configuration files or the creation of new library files (.so or .dll) by the PostgreSQL service process. It also flags when the PostgreSQL service process is initiated with command-line arguments referencing 'shared_preload_libraries', which can be abused to load arbitrary code or malicious extensions into the database engine.
Detects modifications to the PostgreSQL configuration file 'pg_hba.conf' closely followed by a reload command (via pg_ctl or postgres processes). This behavior is indicative of an attacker attempting to modify authentication or connection access controls for a database.
Detects modifications to the PostgreSQL configuration file 'pg_hba.conf' closely followed by a reload command (via pg_ctl or postgres processes). This behavior is indicative of an attacker attempting to modify authentication or connection access controls for a database.
Detects modifications to the PostgreSQL configuration file 'pg_hba.conf' closely followed by a reload command (via pg_ctl or postgres processes). This behavior is indicative of an attacker attempting to modify authentication or connection access controls for a database.
This rule detects potential unauthenticated access or unauthorized configuration modifications to an AI agent management backend. It monitors HTTP logs for requests targeting configuration endpoints that lack proper authentication, specifically identifying attempts to retrieve sensitive information like Dify or Coze keys, or attempts to inject new agent configurations via unauthenticated POST requests.
This rule detects potentially malicious modifications to PostgreSQL configuration files or the creation of new library files (.so or .dll) by the PostgreSQL service process. It also flags when the PostgreSQL service process is initiated with command-line arguments referencing 'shared_preload_libraries', which can be abused to load arbitrary code or malicious extensions into the database engine.
This rule detects successful attempts by non-approved users or service accounts to delete, patch, or update Kubernetes PrometheusRule or AlertmanagerConfig resources. These resources control critical cluster monitoring and alerting; unauthorized changes could be used to disable security monitoring, modify alert notification channels to hide malicious activity, or tamper with detection capabilities.
Detects high CPU utilization (exceeding 80%) on VMware ESXi hosts during non-business hours (between 22:00 and 06:00). Such activity may indicate unauthorized resource hijacking, such as cryptocurrency mining, or performance degradation due to unexpected processes.
Detects the disabling of critical encryption enforcement settings on an ESXi host, such as secure boot or executable verification requirements, which may indicate an attempt to weaken hypervisor integrity or allow unauthorized code execution.
Identifies potentially suspicious email forwarding configurations, mailbox permission assignments, transport rule changes, and delegate access grants that could enable unauthorized email access or data exfiltration.
The query correlates multiple Microsoft 365 audit activities including:
Inbox forwarding rules
SMTP mailbox forwarding
Transport rule forwarding
Delegate mailbox access assignments
Removed or disabled forwarding configurations
This helps detect common Business Email Compromise (BEC) techniques where attackers establish persistence by forwarding mail to external addresses or granting unauthorized mailbox access.
The query correlates multiple Microsoft 365 audit activities including:
Inbox forwarding rules
SMTP mailbox forwarding
Transport rule forwarding
Delegate mailbox access assignments
Removed or disabled forwarding configurations
This helps detect common Business Email Compromise (BEC) techniques where attackers establish persistence by forwarding mail to external addresses or granting unauthorized mailbox access.
Identifies devices with missing or non-compliant Microsoft Defender security controls across Windows, Linux, and macOS endpoints.
The query reviews Microsoft Defender Vulnerability Management (TVM) secure configuration assessments and highlights devices where critical security capabilities are not functioning as expected, including:
Microsoft Defender Sensor
Sensor Data Collection
Defender Communications
Tamper Protection
Real-time Protection
PUA Protection
Cloud-delivered Protection
Security Definitions
Results are enriched with device exposure levels, machine groups, and sensor health status to assist security teams with remediation prioritization.
The query reviews Microsoft Defender Vulnerability Management (TVM) secure configuration assessments and highlights devices where critical security capabilities are not functioning as expected, including:
Microsoft Defender Sensor
Sensor Data Collection
Defender Communications
Tamper Protection
Real-time Protection
PUA Protection
Cloud-delivered Protection
Security Definitions
Results are enriched with device exposure levels, machine groups, and sensor health status to assist security teams with remediation prioritization.
This rule identifies active, high or critical severity regulatory compliance violations (e.g., GDPR, HIPAA, PCI-DSS, NIST) reported by Zscaler Data Security Posture Management (DSPM). It further highlights assets with repeat violations across multiple regulatory frameworks, facilitating prioritization of remediation efforts for critical compliance gaps.
Detects high-risk administrative actions within Netskope, including the deletion of security policies, modification of Data Loss Prevention (DLP) rules, disabling of threat protection features, or the creation of new API tokens and administrative accounts. The rule flags these activities as 'critical' or 'high' severity, particularly if they occur outside standard business hours.
Detects administrative changes to Zscaler location templates that disable critical security enforcement settings, specifically Firewall Control, IPS Control, or Acceptable Use Policy (AUP) enforcement. Such modifications may indicate an attempt to weaken an organization's perimeter defense posture.
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