Dev Sec Ops

• GitHub Actions Disable Security Workflow :
  network GitHub risk_score:27 2024-09-30 version:3
  The following analytic detects the disabling of a security workflow in GitHub Actions. It leverages GitHub logs to identify when a workflow, excluding those named *security-testing*, is disabled following a push or pull request event. This activity is significant as it may indicate an attempt by an attacker to conceal malicious code by disabling security checks. If confirmed malicious, this could allow the attacker to introduce and persist undetected malicious code within the repository, potentially compromising the integrity and security of the codebase.


• GitHub Dependabot Alert :
  network GitHub risk_score:27 2024-09-30 version:3
  The following analytic identifies the creation of GitHub Dependabot alerts, which indicate potential vulnerabilities in the codebase. It detects this activity by searching for logs with the "create" action and analyzing fields such as affected package, severity, and fixed version. This detection is significant for a SOC because it helps identify and address security risks in the codebase proactively. If confirmed malicious, these vulnerabilities could be exploited by attackers to gain unauthorized access or cause breaches, leading to potential data loss or system compromise.


• Gsuite Suspicious Shared File Name :
  endpoint GSuite risk_score:21 2024-09-30 version:3
  The following analytic detects shared files in Google Drive with suspicious filenames commonly used in spear phishing campaigns. It leverages GSuite Drive logs to identify documents with titles that include keywords like "dhl," "ups," "invoice," and "shipment." This activity is significant because such filenames are often used to lure users into opening malicious documents or clicking harmful links. If confirmed malicious, this activity could lead to unauthorized access, data theft, or further compromise of the user's system.


• AWS ECR Container Scanning Findings Medium :
  network AWS Account risk_score:21 2024-09-30 version:4
  The following analytic identifies medium-severity findings from AWS Elastic Container Registry (ECR) image scans. It leverages AWS CloudTrail logs, specifically the DescribeImageScanFindings event, to detect vulnerabilities in container images. This activity is significant for a SOC as it highlights potential security risks in containerized applications, which could be exploited if not addressed. If confirmed malicious, these vulnerabilities could lead to unauthorized access, data breaches, or further exploitation within the container environment, compromising the overall security posture.


• Kubernetes Nginx Ingress LFI :
  network Kubernetes risk_score:49 2024-09-30 version:5
  The following analytic detects local file inclusion (LFI) attacks targeting Kubernetes Nginx ingress controllers. It leverages Kubernetes logs, parsing fields such as `request` and `status` to identify suspicious patterns indicative of LFI attempts. This activity is significant because LFI attacks can allow attackers to read sensitive files from the server, potentially exposing critical information. If confirmed malicious, this could lead to unauthorized access to sensitive data, further exploitation, and potential compromise of the Kubernetes environment.


• Risk Rule for Dev Sec Ops by Repository :
  threat Amazon Elastic Container Registry risk_score:70 2024-10-22 version:4
  The following analytic identifies high-risk activities within repositories by correlating repository data with risk scores. It leverages risk events from the Dev Sec Ops analytic stories, summing risk scores and capturing source and user information. The detection focuses on high-risk scores above 100 and sources with more than three occurrences. This activity is significant as it highlights repositories frequently targeted by threats, providing insights into potential vulnerabilities. If confirmed malicious, attackers could exploit these repositories, leading to data breaches or infrastructure compromise.


• AWS ECR Container Upload Unknown User :
  network AWS Account risk_score:49 2024-09-30 version:3
  The following analytic detects the upload of a new container image to AWS Elastic Container Registry (ECR) by an unknown user. It leverages AWS CloudTrail logs to identify `PutImage` events from the ECR service, filtering out known users. This activity is significant because container uploads should typically be performed by a limited set of authorized users. If confirmed malicious, this could indicate unauthorized access, potentially leading to the deployment of malicious containers, data exfiltration, or further compromise of the AWS environment.


• AWS ECR Container Scanning Findings High :
  network AWS Account risk_score:70 2024-09-30 version:4
  The following analytic identifies high-severity findings from AWS Elastic Container Registry (ECR) image scans. It detects these activities by analyzing AWS CloudTrail logs for the DescribeImageScanFindings event, specifically filtering for findings with a high severity level. This activity is significant for a SOC because high-severity vulnerabilities in container images can lead to potential exploitation if not addressed. If confirmed malicious, attackers could exploit these vulnerabilities to gain unauthorized access, execute arbitrary code, or escalate privileges within the container environment, posing a significant risk to the overall security posture.


• Kubernetes Scanner Image Pulling :
  network Kubernetes risk_score:81 2024-09-30 version:3
  The following analytic detects the pulling of known Kubernetes security scanner images such as kube-hunter, kube-bench, and kube-recon. It leverages Kubernetes logs ingested through Splunk Connect for Kubernetes, specifically monitoring for messages indicating the pulling of these images. This activity is significant because the use of security scanners can indicate an attempt to identify vulnerabilities within the Kubernetes environment. If confirmed malicious, this could lead to the discovery and exploitation of security weaknesses, potentially compromising the entire Kubernetes cluster.


• Circle CI Disable Security Job :
  network CircleCI risk_score:72 2024-09-30 version:3
  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.


• Correlation by User and Risk :
  network AWS Account risk_score:70 2024-10-17 version:2
  The following analytic detects the correlation between the user and risk score and identifies users with a high risk score that pose a significant security risk such as unauthorized access attempts, suspicious behavior, or potential insider threats. Next, the analytic calculates the sum of the risk scores and groups the results by user, the corresponding signals, and the repository. The results are sorted in descending order based on the risk score and filtered to include records with a risk score greater than 80. Finally, the results are passed through a correlation filter specific to the user and risk. This detection is important because it identifies users who have a high risk score and helps to prioritize investigations and allocate resources. False positives might occur but the impact of such an attack can vary depending on the specific scenario such as data exfiltration, system compromise, or the disruption of critical services. Please investigate this notable event.


• GSuite Email Suspicious Attachment :
  endpoint GSuite risk_score:49 2024-09-30 version:3
  The following analytic detects suspicious attachment file extensions in GSuite emails, potentially indicating a spear-phishing attack. It leverages GSuite Gmail logs to identify emails with attachments having file extensions commonly associated with malware, such as .exe, .bat, and .js. This activity is significant as these file types are often used to deliver malicious payloads, posing a risk of compromising targeted machines. If confirmed malicious, this could lead to unauthorized code execution, data breaches, or further network infiltration.


• Circle CI Disable Security Step :
  network CircleCI risk_score:72 2024-10-17 version:3
  The following analytic detects the disablement of security steps in a CircleCI pipeline. It leverages CircleCI logs, using field renaming, joining, and statistical analysis to identify instances where mandatory security steps are not executed. 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. Investigate by reviewing job names, commit details, and user information associated with the disablement, and examine any relevant artifacts and concurrent processes.


• ASL AWS ECR Container Upload Outside Business Hours :
  network AWS Account risk_score:49 2024-09-30 version:5
  The following analytic detects the upload of new containers to AWS Elastic Container Service (ECR) outside of standard business hours through AWS CloudTrail events. It identifies this behavior by monitoring for `PutImage` events occurring before 8 AM or after 8 PM, as well as any uploads on weekends. This activity is significant for a SOC to investigate as it may indicate unauthorized access or malicious deployments, potentially leading to compromised services or data breaches. Identifying and addressing such uploads promptly can mitigate the risk of security incidents and their associated impacts.


• Gsuite Email With Known Abuse Web Service Link :
  endpoint GSuite risk_score:25 2024-09-30 version:3
  The following analytic detects emails in Gsuite containing links to known abuse web services such as Pastebin, Telegram, and Discord. It leverages Gsuite Gmail logs to identify emails with these specific domains in their links. This activity is significant because these services are commonly used by attackers to deliver malicious payloads. If confirmed malicious, this could lead to the delivery of malware, phishing attacks, or other harmful activities, potentially compromising sensitive information or systems within the organization.


• ASL AWS ECR Container Upload Unknown User :
  network AWS Account risk_score:49 2024-09-30 version:4
  The following 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.


• Correlation by Repository and Risk :
  network AWS Account risk_score:70 2024-10-17 version:2
  This search has been deprecated and updated with Risk Rule for Dev Sec Ops by Repository detection. The following analytic detects by correlating repository and risk score to identify patterns and trends in the data based on the level of risk associated. The analytic adds any null values and calculates the sum of the risk scores for each detection. Then, the analytic captures the source and user information for each detection and sorts the results in ascending order based on the risk score. Finally, the analytic filters the detections with a risk score below 80 and focuses only on high-risk detections.This detection is important because it provides valuable insights into the distribution of high-risk activities across different repositories. It also identifies the most vulnerable repositories that are frequently targeted by potential threats. Additionally, it proactively detects and responds to potential threats, thereby minimizing the impact of attacks and safeguarding critical assets. Finally, it provides a comprehensive view of the risk landscape and helps to make informed decisions to protect the organization's data and infrastructure. False positives might occur so it is important to identify the impact of the attack and prioritize response and mitigation efforts.


• Gsuite Email Suspicious Subject With Attachment :
  endpoint GSuite risk_score:25 2024-09-30 version:3
  The following analytic identifies Gsuite emails with suspicious subjects and attachments commonly used in spear phishing attacks. It leverages Gsuite email logs, focusing on specific keywords in the subject line and known malicious file types in attachments. This activity is significant for a SOC as spear phishing is a prevalent method for initial compromise, often leading to further malicious actions. If confirmed malicious, this activity could result in unauthorized access, data exfiltration, or further malware deployment, posing a significant risk to the organization's security.


• GitHub Pull Request from Unknown User :
  network GitHub risk_score:27 2024-09-30 version:3
  The following analytic detects pull requests from unknown users on GitHub. It uses a Splunk query to identify pull requests where the user ID is not specified and cross-references these with a known users lookup table. This activity is significant because pull requests from unknown users can introduce malicious code or unauthorized changes to repositories. If confirmed malicious, this could lead to unauthorized code changes, data breaches, or other security incidents. Immediate steps include reviewing the author's name, repository, head reference, and commit message, and investigating any related artifacts and processes.


• Github Commit Changes In Master :
  endpoint GitHub risk_score:9 2024-09-30 version:3
  The following analytic detects direct commits or pushes to the master or main branch in a GitHub repository. It leverages GitHub logs to identify events where changes are made directly to these critical branches. This activity is significant because direct modifications to the master or main branch bypass the standard review process, potentially introducing unreviewed and harmful changes. If confirmed malicious, this could lead to unauthorized code execution, security vulnerabilities, or compromised project integrity.


• AWS ECR Container Scanning Findings Low Informational Unknown :
  network AWS Account risk_score:5 2024-09-30 version:4
  The following analytic identifies low, informational, or unknown severity findings from AWS Elastic Container Registry (ECR) image scans. It leverages AWS CloudTrail logs, specifically the DescribeImageScanFindings event, to detect these findings. This activity is significant for a SOC as it helps in early identification of potential vulnerabilities or misconfigurations in container images, which could be exploited if left unaddressed. If confirmed malicious, these findings could lead to unauthorized access, data breaches, or further exploitation within the containerized environment.


• AWS ECR Container Upload Outside Business Hours :
  network AWS Account risk_score:49 2024-09-30 version:4
  The following analytic detects the upload of a new container image to AWS Elastic Container Registry (ECR) outside of standard business hours. It leverages AWS CloudTrail logs to identify `PutImage` events occurring between 8 PM and 8 AM or on weekends. This activity is significant because container uploads outside business hours can indicate unauthorized or suspicious activity, potentially pointing to a compromised account or insider threat. If confirmed malicious, this could allow an attacker to deploy unauthorized or malicious containers, leading to potential data breaches or service disruptions.


• Gsuite Outbound Email With Attachment To External Domain :
  endpoint GSuite risk_score:9 2024-10-17 version:4
  The following analytic detects outbound emails with attachments sent from an internal email domain to an external domain. It leverages Gsuite Gmail logs, parsing the source and destination email domains, and flags emails with fewer than 20 outbound instances. This activity is significant as it may indicate potential data exfiltration or insider threats. If confirmed malicious, an attacker could use this method to exfiltrate sensitive information, leading to data breaches and compliance violations.


• Github Commit In Develop :
  endpoint GitHub risk_score:9 2024-09-30 version:3
  The following analytic detects commits pushed directly to the 'develop' or 'main' branches in a GitHub repository. It leverages GitHub logs, focusing on commit metadata such as author details, commit messages, and timestamps. This activity is significant as direct commits to these branches can bypass the review process, potentially introducing unvetted changes. If confirmed malicious, this could lead to unauthorized code modifications, introducing vulnerabilities or backdoors into the codebase, and compromising the integrity of the development lifecycle.


• Gsuite Drive Share In External Email :
  endpoint GSuite risk_score:72 2024-10-17 version:3
  The following analytic detects Google Drive or Google Docs files shared externally from an internal domain. It leverages GSuite Drive logs, extracting and comparing the source and destination email domains to identify external sharing. This activity is significant as it may indicate potential data exfiltration by an attacker or insider. If confirmed malicious, this could lead to unauthorized access to sensitive information, data leakage, and potential compliance violations. Monitoring this behavior helps in early detection and mitigation of data breaches.


• Kubernetes Nginx Ingress RFI :
  network Kubernetes risk_score:49 2024-09-30 version:5
  The following analytic detects remote file inclusion (RFI) attacks targeting Kubernetes Nginx ingress controllers. It leverages Kubernetes logs from the Nginx ingress controller, parsing fields such as `remote_addr`, `request`, and `url` to identify suspicious activity. This activity is significant because RFI attacks can allow attackers to execute arbitrary code or access sensitive files on the server. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or further compromise of the Kubernetes environment.