Splunk Security
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This analytic detects suspicious processes accessing registry entries related to default internet browsers. It specifically looks for Windows Security Event Code 4663, which indicates an attempt to access registry paths associated with browser configurations. Adversaries often target these registry keys to gather information about installed browsers and their settings, which can lead to the theft of sensitive data like login credentials and browsing history. The rule filters out common legitimate processes to reduce false positives. If confirmed malicious, this activity could enable attackers to exfiltrate sensitive information and compromise user accounts.
This analytic detects a single source computer authenticating to 30 or more remote endpoints within a 5-minute timespan using Windows Event ID 4624 (successful logon). This behavior is identified by analyzing Windows Event Logs for LogonType 3 (network logon) events and counting unique target computers. Such activity is significant as it may indicate lateral movement or network share enumeration by an adversary. If confirmed malicious, this could lead to unauthorized access to multiple systems, potentially compromising sensitive data and escalating privileges within the network.
The analytic detects the abuse of SqlWriter and SQLDumper executables to sideload the vcruntime140.dll library. It leverages Sysmon EventCode 7 logs, focusing on instances where SQLDumper.exe or SQLWriter.exe load vcruntime140.dll, excluding legitimate loads from the System32 directory. This activity is significant as it indicates potential DLL sideloading, a technique used by adversaries to execute malicious code within trusted processes. If confirmed malicious, this could allow attackers to execute arbitrary code, maintain persistence, and evade detection by blending with legitimate processes.
This analytic detects DNS queries to common Ngrok domains, indicating potential use of the Ngrok reverse proxy tool. It leverages the Network Resolution datamodel to identify queries to domains such as "*.ngrok.com" and "*.ngrok.io". While Ngrok usage is not inherently malicious, it has been increasingly adopted by adversaries for covert communication and data exfiltration. If confirmed malicious, this activity could allow attackers to bypass network defenses, establish persistent connections, and exfiltrate sensitive data, posing a significant threat to the network's security.
The analytic identifies attempts to exploit the CVE-2023-46805 and CVE-2024-21887 vulnerabilities in Ivanti Connect Secure. It detects POST requests to specific URIs that leverage command injection to execute arbitrary commands. The detection uses the Web datamodel to monitor for these requests and checks for a 200 OK response, indicating a successful exploit attempt. This activity is significant as it can lead to unauthorized command execution on the server. If confirmed malicious, attackers could gain control over the system, leading to potential data breaches or further network compromise.
The analytic detects suspicious modifications to AWS AMI attributes, such as sharing an AMI with another AWS account or making it publicly accessible. It leverages AWS CloudTrail logs to identify these changes by monitoring specific API calls. This activity is significant because adversaries can exploit these modifications to exfiltrate sensitive data stored in AWS resources. If confirmed malicious, this could lead to unauthorized access and potential data breaches, compromising the confidentiality and integrity of organizational information.
The following analytic identifies a successful Console Login authentication event for an AWS IAM user account without Multi-Factor Authentication (MFA) enabled. It leverages AWS CloudTrail logs to detect instances where MFA was not used during login. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to the AWS environment, potentially leading to data exfiltration, resource manipulation, or further privilege escalation.
The following analytic identifies multiple failed multi-factor authentication (MFA) requests for a single user within an Azure AD tenant. It leverages Azure AD Sign-in Logs, specifically error code 500121, to detect more than 10 failed MFA attempts within 10 minutes. This behavior is significant as it may indicate an adversary attempting to bypass MFA by bombarding the user with repeated authentication prompts. If confirmed malicious, this activity could lead to unauthorized access, allowing attackers to compromise user accounts and potentially escalate their privileges within the environment.
The analytic detects the disablement of security steps in a CircleCI pipeline. This activity is significant because disabling security steps can introduce vulnerabilities, unauthorized changes, or malicious code into the pipeline. If confirmed malicious, this could lead to potential attacks, data breaches, or compromised infrastructure. The rule leverages CircleCI logs, using field renaming, joining, and statistical analysis to identify instances where mandatory security steps are not executed. Investigation should focus on reviewing job names, commit details, and user information associated with the disablement, and examining any relevant artifacts and concurrent processes.
The analytic detects failed authentication attempts during the Multi-Factor Authentication (MFA) challenge on a Google Cloud Platform (GCP) tenant. It uses Google Workspace login failure events to identify instances where MFA methods were challenged but not successfully completed. This activity is significant as it may indicate an adversary attempting to access an account with compromised credentials despite MFA protection. If confirmed malicious, this could lead to unauthorized access attempts, potentially compromising sensitive data and resources within the GCP environment.
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