Splunk Security
@SplunkSecurity35 followers31,507 downloads1,688 copies11 likes90,252 views
2,515 detections
Filters
Last updated
All Time
Detection languages
2,515
Categories
839
535
265
240
208
Platforms
1,613
264
203
142
100
Products / Services
1,234
902
796
217
212
MITRE Techniques
935
667
517
499
307
CVEs
18
13
12
12
9
The analytic identifies a single source IP failing to authenticate with multiple valid users, potentially indicating a Password Spraying attack against an Azure Active Directory tenant. It uses Azure SignInLogs data and calculates the standard deviation for source IPs, applying the 3-sigma rule to detect unusual numbers of failed authentication attempts. This activity is significant as it may signal an adversary attempting to gain initial access or elevate privileges. If confirmed malicious, this could lead to unauthorized access, privilege escalation, and potential compromise of sensitive information.
The following analytic detects the disabling of security jobs in CircleCI pipelines. It leverages CircleCI log data, renaming and extracting fields such as job names, workflow IDs, user information, commit messages, URLs, and branches. The detection identifies mandatory jobs for each workflow and checks if they were executed. This activity is significant because disabling security jobs can allow malicious code to bypass security checks, leading to potential data breaches, system downtime, and reputational damage. If confirmed malicious, this could result in unauthorized code execution and compromised pipeline integrity.
The analytic detects when branch rules are deleted in GitHub Enterprise. The detection monitors GitHub Enterprise audit logs for branch rule deletion events by tracking actor details, repository information, and associated metadata. For a SOC, identifying deleted branch rules is critical as it could indicate attempts to bypass code review requirements and security controls. Branch deletion rules are essential security controls that enforce code review, prevent force pushes, and maintain code quality. Disabling these protections could allow malicious actors to directly push unauthorized code changes or backdoors to protected branches. The impact of disabled branch protection includes potential code tampering, bypass of security reviews, introduction of vulnerabilities or malicious code, and compromise of software supply chain integrity. This activity could be part of a larger attack chain where an adversary first disables security controls before attempting to inject malicious code.
The analytic detects when a user disables Dependabot security features within a GitHub repository. Dependabot helps automatically identify and fix security vulnerabilities in dependencies. The detection monitors GitHub Enterprise logs for configuration changes that disable Dependabot functionality. This behavior could indicate an attacker attempting to prevent the automatic detection of vulnerable dependencies, which would allow them to exploit known vulnerabilities that would otherwise be patched. For a SOC, identifying the disabling of security features like Dependabot is critical as it may be a precursor to supply chain attacks where attackers exploit vulnerable dependencies. The impact could be severe if vulnerabilities remain unpatched, potentially leading to code execution, data theft, or other compromises through the software supply chain.
The following analytic detects suspicious image pulling in Kubernetes environments. It identifies this activity by monitoring Kubernetes audit logs for image pull requests that do not match a predefined list of allowed images. This behavior is significant for a SOC as it may indicate an attacker attempting to deploy malicious software or infiltrate the system. If confirmed malicious, the impact could be severe, potentially leading to unauthorized access to sensitive systems or data, and enabling further malicious activities within the cluster.
The following analytic detects when a content search is initiated within the Office 365 Security and Compliance Center. It leverages the SearchCreated operation from the o365_management_activity logs under the SecurityComplianceCenter workload. This activity is significant as it may indicate an attempt to access sensitive organizational data, including emails and documents. If confirmed malicious, this could lead to unauthorized data access, potential data exfiltration, and compliance violations. Monitoring this behavior helps ensure the integrity and security of organizational data.
This analytic detects when an email manually submitted to Microsoft through the Security & Compliance portal is found to be malicious. This capability is an enhanced protection feature that can be used within O365 tenants by administrative users to report potentially malicious emails. This correlation looks for any submission that returns a Phish or Malware verdict upon submission.
The following analytic detects the execution of a suspicious `bcdedit` command that configures a host to boot in safe mode with network support. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions involving `bcdedit.exe` with specific parameters. This activity is significant because it is a known technique used by BlackMatter ransomware to force a compromised host into safe mode for continued encryption. If confirmed malicious, this could allow attackers to bypass certain security controls, persist in the environment, and continue their malicious activities.
The analytic identifies the abuse of Regsvr32.exe to proxy execution of malicious code, specifically detecting the loading of "scrobj.dll" by Regsvr32.exe. This activity is significant because Regsvr32.exe is a trusted, signed Microsoft binary, often used in "Squiblydoo" attacks to bypass application control mechanisms. If confirmed malicious, this technique could allow an attacker to execute arbitrary code, potentially leading to system compromise and persistent access.
The following analytic detects the modification of the Windows registry to disable the Windows Defender BlockAtFirstSeen feature. It leverages data from the Endpoint.Registry data model, specifically monitoring changes to the registry path associated with Windows Defender SpyNet and the DisableBlockAtFirstSeen value. This activity is significant because disabling this feature can allow malicious files to bypass initial detection by Windows Defender, increasing the risk of malware infection. If confirmed malicious, this action could enable attackers to execute malicious code undetected, leading to potential system compromise and data breaches.
Page 215 of 252