Cisco AI Defense Security Alerts by Application Name: endpointWeb Application2025-03-21version:2
The search surfaces alerts from the Cisco AI Defense product for potential attacks against the AI models running in your environment. This analytic identifies security events within Cisco AI Defense by examining event messages, actions, and policy names. It focuses on connections and applications associated with specific guardrail entities and ruleset types. By aggregating and analyzing these elements, the search helps detect potential policy violations and security threats, enabling proactive defense measures and ensuring network integrity.
Microsoft Defender Incident Alerts: endpointEndpoint2025-01-20version:3
The following analytic is to leverage alerts from Microsoft Defender O365 Incidents. This query aggregates and summarizes all alerts from Microsoft Defender O365 Incidents, providing details such as the destination, file name, severity, process command line, ip address, registry key, signature, description, unique id, and timestamps. This detection is not intended to detect new activity from raw data, but leverages Microsoft provided alerts to be correlated with other data as part of risk based alerting. The data contained in the alert is mapped not only to the risk obejct, but also the threat object. This detection filters out evidence that has a verdict of clean from Microsoft. It dynamically maps the MITRE technique at search time to auto populate the annotation field with the value provided in the alert. It also uses a static mapping to set the risk score based on the severity of the alert.
Detect Spike in AWS Security Hub Alerts for User: networkAWS Instance2024-11-14version:6
The following analytic identifies a spike in the number of AWS Security Hub alerts for an AWS IAM User within a 4-hour interval. It leverages AWS Security Hub findings data, calculating the average and standard deviation of alerts to detect significant deviations. This activity is significant as a sudden increase in alerts for a specific user may indicate suspicious behavior or a potential security incident. If confirmed malicious, this could signify an ongoing attack, unauthorized access, or misuse of IAM credentials, potentially leading to data breaches or further exploitation.
Detect Spike in AWS Security Hub Alerts for EC2 Instance: endpointAWS Instance2024-11-14version:6
The following analytic identifies a spike in the number of AWS Security Hub alerts for an EC2 instance within a 4-hour interval. It leverages AWS Security Hub findings data, calculating the average and standard deviation of alerts to detect anomalies. This activity is significant for a SOC as a sudden increase in alerts may indicate potential security incidents or misconfigurations requiring immediate attention. If confirmed malicious, this could signify an ongoing attack, leading to unauthorized access, data exfiltration, or disruption of services on the affected EC2 instance.
Microsoft Defender ATP Alerts: endpointEndpoint2025-01-20version:3
The following analytic is to leverage alerts from Microsoft Defender ATP Alerts. This query aggregates and summarizes all alerts from Microsoft Defender ATP Alerts, providing details such as the source, file name, severity, process command line, ip address, registry key, signature, description, unique id, and timestamps. This detection is not intended to detect new activity from raw data, but leverages Microsoft provided alerts to be correlated with other data as part of risk based alerting. The data contained in the alert is mapped not only to the risk obejct, but also the threat object. This detection filters out evidence that has a verdict of clean from Microsoft. It dynamically maps the MITRE technique at search time to auto populate the annotation field with the value provided in the alert. It also uses a dynamic mapping to set the risk score in Enterprise Security based on the severity of the alert.
Detect Critical Alerts from Security Tools: endpointEndpoint2025-01-13version:2
The following analytic has been deprecated in favour of specific and dedicated product analytics such as "Microsoft Defender ATP Alerts". The following analytic is to detect high and critical alerts from endpoint security tools such as Microsoft Defender, Carbon Black, and Crowdstrike. This query aggregates and summarizes critical severity alerts from the Alerts data model, providing details such as the alert signature, application, description, source, destination, and timestamps, while applying custom filters and formatting for enhanced analysis in a SIEM environment.This capability allows security teams to efficiently allocate resources and maintain a strong security posture, while also supporting compliance with regulatory requirements by providing a clear record of critical security events. We tested these detections with logs from Microsoft Defender, however this detection should work for any security alerts that are ingested into the alerts data model. **Note** - We are dynamically creating the risk_score field based on the severity of the alert in the SPL and that supersedes the risk score set in the detection.
Cisco Secure Application Alerts: threatWeb Application2025-02-04version:1
The following analytic is to leverage alerts from Cisco SecureApp, which identifies and monitors exploit attempts targeting business applications. The primary attack observed involves exploiting vulnerabilities in web applications, including injection attacks (SQL, API abuse), deserialization vulnerabilities, remote code execution attempts, LOG4J and zero day attacks. These attacks are typically aimed at gaining unauthorized access, exfiltrating sensitive data, or disrupting application functionality.
Cisco SecureApp provides real-time detection of these threats by analyzing application-layer events and correlating attack behavior with known vulnerability signatures. This detection methodology helps the Security Operations Center (SOC) by:
* Identifying active exploitation attempts in real-time, allowing for quicker incident response.
* Categorizing attack severity to prioritize remediation efforts based on risk level.
* Providing visibility into attacker tactics, including source IP, attack techniques, and affected applications.
* Generating risk-based scoring and contextual alerts to enhance decision-making within SOC workflows.
* Helping analysts determine whether an attack was merely an attempt or if it successfully exploited a vulnerability.
By leveraging this information, SOC teams can proactively mitigate security threats, patch vulnerable applications, and enforce security controls to prevent further exploitation.
