Splunk Security
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This analytic leverages alerts from Microsoft Defender O365 Incidents. It aggregates and summarizes these alerts, extracting details such as destination, file name, severity, process command line, IP address, registry key, signature, description, and timestamps. The detection filters out alerts with a verdict of 'Clean' from Microsoft. It dynamically maps MITRE techniques from the alert data and assigns a risk score based on the alert's severity. This rule is designed to correlate Microsoft-provided alerts with other data for risk-based alerting, rather than detecting new activity from raw data.
The following analytic detects modifications to undocumented registry keys that allow a DLL to load into lsass.exe, potentially capturing credentials. It leverages the Endpoint.Registry data model to identify changes to \CurrentControlSet\Services\NTDS\DirectoryServiceExtPt or \CurrentControlSet\Services\NTDS\LsaDbExtPt. This activity is significant as it indicates a possible attempt to inject malicious code into the Local Security Authority Subsystem Service (LSASS), which can lead to credential theft. If confirmed malicious, this could allow attackers to gain unauthorized access to sensitive information and escalate privileges within the environment.
The following analytic identifies the execution of `net.exe` with command line arguments aimed at obtaining the computer or domain password policy. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant as it indicates potential reconnaissance efforts by adversaries to gather information about Active Directory password policies. If confirmed malicious, this behavior could allow attackers to understand password complexity requirements, aiding in brute-force or password-guessing attacks, ultimately compromising user accounts and gaining unauthorized access to the network.
The analytic detects ARP Poisoning attacks by monitoring for Dynamic ARP Inspection (DAI) errors on Cisco network devices. It leverages logs from Cisco devices, specifically looking for events where the ARP inspection feature has disabled an interface due to suspicious activity. This activity is significant because ARP Poisoning can allow attackers to intercept, modify, or disrupt network traffic, leading to potential data breaches or denial of service. If confirmed malicious, this could enable attackers to perform man-in-the-middle attacks, compromising the integrity and confidentiality of network communications.
The analytic identifies potential exploit attempts involving command and script interpreters that are blocked by Zscaler. It uses web proxy logs to detect incidents where actions are blocked due to exploit references. The detection compiles statistics by user, threat name, URL, hostname, file class, and filename. This activity is significant as it helps identify and mitigate exploit attempts, which are critical for maintaining security. If confirmed malicious, such activity could lead to unauthorized code execution, privilege escalation, or persistent access within the environment, posing a severe threat to organizational security.
The analytic identifies a significant increase in data transfers from an email server to client hosts. It uses statistical analysis on network traffic to detect anomalies based on average and standard deviation of outbound bytes. This activity is significant as it may indicate a malicious actor exfiltrating data via the email server, potentially leading to unauthorized data access and breaches.
The analytic detects unauthorized container uploads to AWS Elastic Container Service (ECR) by monitoring AWS CloudTrail events. It identifies instances where a new container is uploaded by a user not previously recognized as authorized. This detection is crucial for a SOC as it can indicate a potential compromise or misuse of AWS ECR, which could lead to unauthorized access to sensitive data or the deployment of malicious containers. By identifying and investigating these events, organizations can mitigate the risk of data breaches or other security incidents resulting from unauthorized container uploads. The impact of such an attack could be significant, compromising the integrity and security of the organization's cloud environment.
The analytic identifies an AWS IAM account with concurrent sessions originating from more than one unique IP address within a 5-minute window. It leverages AWS CloudTrail logs, specifically the `DescribeEventAggregates` event, to detect this behavior. This activity is significant as it may indicate a session hijacking attack, where an adversary uses stolen session cookies to access AWS resources from a different location. If confirmed malicious, this could allow unauthorized access to sensitive corporate resources, leading to potential data breaches or further exploitation within the AWS environment.
The following analytic identifies unsuccessful login attempts to the AWS Management Console using a specific user identity. It leverages AWS CloudTrail logs to detect failed authentication events associated with the AWS ConsoleLogin action. This activity is significant for a SOC because repeated failed login attempts may indicate a brute force attack or unauthorized access attempts. If confirmed malicious, an attacker could potentially gain access to AWS account services and resources, leading to data breaches, resource manipulation, or further exploitation within the AWS environment.
This analytic identifies an unusual number of failed authentication attempts to the AWS Console originating from a single source IP address, targeting multiple valid user accounts. It leverages AWS CloudTrail logs and statistical analysis (3-sigma rule) to detect anomalies in failed login attempts. This behavior is indicative of a password spraying attack, where an adversary attempts to gain initial access or elevate privileges by trying a single password against many accounts. Successful exploitation could lead to unauthorized access, data breaches, or further compromise of the AWS environment.
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