Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
483 detections
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This rule detects the presence of Olymp Loader malware by identifying known malicious file hashes (SHA256) and network communication with associated distribution domains. It looks for these indicators across various data sources, normalizing fields for consistent output. The rule aims to identify systems infected with or communicating with Olymp Loader infrastructure.
Detects potential Cloudflare Under Attack Mode (UAM) bypass activity, characteristic of the ShadowV2 botnet. This involves the execution of a headless browser followed by network requests using a Cloudflare clearance cookie.
This rule detects the potentially malicious installation of VMware Installation Bundles (VIBs) on an ESXi host using the `--force` flag. The `--force` option bypasses critical signature and compatibility checks, which is uncommon in normal administrative operations. This behavior is often observed in post-compromise scenarios where adversaries install backdoored or unauthorized kernel modules, drivers, or monitoring tools to establish persistence or gain deeper control of the hypervisor.
This analytic detects the configuration of TFTP services on Cisco IOS devices that could be used to exfiltrate sensitive configuration files. Threat actors like Static Tundra have been observed configuring TFTP servers to make device configuration files accessible for exfiltration after gaining initial access. The detection specifically looks for commands that expose critical configuration files such as startup-config, running-config, and other sensitive system information through TFTP. This activity is particularly concerning as it may represent an attempt to steal credentials, network topology information, and other sensitive data stored in device configurations.
This analytic identifies the use of Chromium-based browsers (like Microsoft Edge) running in headless mode with the `--dump-dom` argument. This behavior has been observed in attack campaigns such as DUCKTAIL, where browsers are automated to stealthily download content from the internet using direct URLs or suspicious hosting platforms. The detection focuses on identifying connections to known file-sharing domains or direct IPs extracted from command-line arguments and cross-checks those against the destination of the flow. Since it leverages Cisco Network Visibility Module telemetry, the rule triggers only if a network connection is made.
Detects Salesforce Object Query Language (SOQL) queries that may be attempting to access or exfiltrate sensitive credentials like passwords, API keys, or tokens stored within Salesforce objects. This activity was observed in the UNC6395 campaign where attackers targeted AWS keys, Snowflake tokens, and passwords.
Detects potential DLL side-loading of the CANONSTAGER malware, which is used to deploy the SOGU.SEC backdoor. This rule identifies when the legitimate, signed Canon IJ Printer Assistant Tool (cnmpaui.exe) loads an unsigned DLL with a similar name (cnmpaui.dll) and subsequently reads a .dat file (cnmplog.dat), consistent with the TTPs of the PRC-nexus actor UNC6384.
This analytic detects activity associated with "Static Tundra" threat actor abuse of the Cisco Smart Install (SMI) protocol using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify occurrences of Smart Install exploitation and protocol abuse, including denial-of-service and buffer overflow attempts. The detection triggers when multiple Cisco Smart Install-related Snort signatures are observed in a short period from the same source, which is indicative of active exploitation or reconnaissance against Cisco devices that expose SMI.
The analytic detects when a Windows RDP client attempts to execute an RDP file from a temporary directory, downloads directory, or Outlook directories. This detection is significant as it can indicate an attempt for an adversary to deliver a .rdp file, which may be leveraged by attackers to control or exfiltrate data. If confirmed malicious, this activity could lead to unauthorized access, data theft, or further lateral movement within the network.
This analytic leverages alerts from Splunk AppDynamics SecureApp to identify and monitor exploit attempts targeting business applications. It specifically looks for vulnerabilities in web applications, including injection attacks (SQL, API abuse), deserialization vulnerabilities, remote code execution attempts, LOG4J, and zero-day attacks. These attacks typically aim to gain unauthorized access, exfiltrate sensitive data, or disrupt application functionality. Splunk AppDynamics SecureApp provides real-time detection by analyzing application-layer events and correlating attack behavior with known vulnerability signatures, categorizing attack severity, providing visibility into attacker tactics, and generating risk-based scoring and contextual alerts.
The analytic identifies the execution of the native mimikatz.exe binary on Windows systems, including instances where the binary is renamed. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names. This activity is significant because Mimikatz is a widely used tool for extracting authentication credentials, posing a severe security risk. If confirmed malicious, this activity could allow attackers to obtain sensitive credentials, escalate privileges, and move laterally within the network, leading to potential data breaches and system compromise.
This analytic detects the presence of a registry key associated with the Remcos RAT agent on a host. It leverages data from the Endpoint.Registry data model, focusing on instances where the "Software\Remcos" path is found. This behavior indicates potential compromise by the Remcos RAT, a remote access Trojan used for unauthorized access and data exfiltration. If confirmed malicious, the attacker could gain control over the system, steal sensitive information, or use the compromised host for further attacks. Immediate investigation and remediation are required.
This rule detects potential SQL injection attempts by looking for specific keywords and patterns within the 'cs_uri_query' field of Cloudflare WAF logs. These patterns, such as 'UNION SELECT', '' OR 1=1', 'information_schema', and '--', are commonly used in SQL injection attacks to extract information, bypass authentication, or comment out parts of SQL queries. The rule aims to identify malicious requests targeting web applications that could lead to unauthorized database access or manipulation.
Detects emails delivered to user inboxes that contain both a PDF attachment and a URL identified as a phishing link. This rule is designed to identify modern QR code phishing (quishing) campaigns where the malicious URL is embedded within the PDF to bypass traditional email security scanning. The detection relies on the email security solution's ability to extract and flag URLs from attachments, including those embedded in QR codes.
This detection rule identifies processes that call the 'GlobalMemoryStatusEx' Windows API. This behavior is a known sandbox evasion technique used by malware, including SLOW#TEMPEST, to check the system's physical memory size before executing a malicious payload. The rule is tuned to focus on unsigned processes or those running from non-standard locations and with low host prevalence.
This analytic detects exploitation activity of CVE-2025-5777 using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where Snort signature 65118 (Citrix NetScaler memory overread attempt) is triggered. If confirmed malicious, this behavior is highly indicative of a potential exploitation of CVE-2025-5777.
This detection identifies the use of the `esxcli system auditrecords` commands, which can be used to tamper with logging on an ESXi host. This action may indicate an attempt to evade detection or hinder forensic analysis by preventing the recording of system-level audit events. The rule specifically looks for the use of these commands with 'remote' or 'local' arguments, excluding commands executed within a shell.
This detection identifies when the ESXi Shell is enabled on a host, which may indicate that a malicious actor is preparing to execute commands locally or establish persistent access. Enabling the shell outside of approved maintenance windows can be a sign of compromise or unauthorized administrative activity.
KQL Query from file: glibc critical vulnerability (CVSS 9.8)
The analytic identifies anomalous inbound network traffic volumes from processes within containerized workloads. It leverages Network Performance Monitoring metrics collected via an OTEL collector and pulled from Splunk Observability Cloud. The detection compares recent metrics (tcp.bytes, tcp.new_sockets, tcp.packets, udp.bytes, udp.packets) over the last hour with the average over the past 30 days. This activity is significant as it may indicate unauthorized data reception, potential breaches, vulnerability exploitation, or malware propagation. If confirmed malicious, it could lead to command and control installation, data integrity damage, container escape, and further environment compromise.
This analytic detects new UDP communication between a source and destination workload pair within a Kubernetes cluster. It uses Network Performance Monitoring (NPM) metrics from an OTEL collector via Splunk Observability Cloud. The detection compares network activity over the last hour with the past 30 days to identify new inter-workload communication. Such changes in network behavior can indicate potential security threats or anomalies, including unauthorized connections that may lead to data breaches, privilege escalation, lateral movement, or disruption of critical services.
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