Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
289 detections
Filters
Last updated
All Time
Detection languages
82
73
38
36
26
Contributors
85
49
34
33
30
Categories
216
120
57
34
27
Platforms
260
70
64
37
11
Products / Services
10,650
9,755
6,688
4,418
3,745
289
MITRE Techniques
111
81
43
42
42
CVEs
1
1
1
1
IDS Classtypes
3
2
1
1
IDS Protocols
7
Detects when a firewall rule is modified or deleted in Google Cloud Platform (GCP).
Detects the deployment of workloads that are deployed by using the break-glass flag to override Binary Authorization controls.
Identifies when an admission controller is executed in GCP Kubernetes.
A Kubernetes Admission controller intercepts, and possibly modifies, requests to the Kubernetes API server.
The behavior of this admission controller is determined by an admission webhook (MutatingAdmissionWebhook or ValidatingAdmissionWebhook) that the user deploys in the cluster.
An adversary can use such webhooks as the MutatingAdmissionWebhook for obtaining persistence in the cluster.
For example, attackers can intercept and modify the pod creation operations in the cluster and add their malicious container to every created pod. An adversary can use the webhook ValidatingAdmissionWebhook, which could be used to obtain access credentials.
An adversary could use the webhook to intercept the requests to the API server, record secrets, and other sensitive information.
A Kubernetes Admission controller intercepts, and possibly modifies, requests to the Kubernetes API server.
The behavior of this admission controller is determined by an admission webhook (MutatingAdmissionWebhook or ValidatingAdmissionWebhook) that the user deploys in the cluster.
An adversary can use such webhooks as the MutatingAdmissionWebhook for obtaining persistence in the cluster.
For example, attackers can intercept and modify the pod creation operations in the cluster and add their malicious container to every created pod. An adversary can use the webhook ValidatingAdmissionWebhook, which could be used to obtain access credentials.
An adversary could use the webhook to intercept the requests to the API server, record secrets, and other sensitive information.
This rule detects activity associated with TruffleHog, an open-source tool used for finding credentials and sensitive data, within cloud audit logs. It specifically looks for the 'trufflehog' string in the user_agent field, indicating that the tool was used to interact with cloud resources.
Detects BigQuery queries using CONCAT with CHR functions to dynamically build cross-project paths, bypassing dot filters. High-fidelity indicator of LeakyLooker-style SQL injection.
Detects attempts to exploit a vulnerability in Google Looker (CVE-2025-12743) by using error-based SQL injection within LookML dimension definitions. Attackers can use this to exfiltrate the internal Looker database.
Identifies when an admission controller is executed in GCP Kubernetes. A Kubernetes Admission controller intercepts, and possibly modifies, requests to the Kubernetes API server. The behavior of this admission controller is determined by an admission webhook (MutatingAdmissionWebhook or ValidatingAdmissionWebhook) that the user deploys in the cluster. An adversary can use such webhooks as the MutatingAdmissionWebhook for obtaining persistence in the cluster. For example, attackers can intercept and modify the pod creation operations in the cluster and add their malicious container to every created pod. An adversary can use the webhook ValidatingAdmissionWebhook, which could be used to obtain access credentials. An adversary could use the webhook to intercept the requests to the API server, record secrets, and other sensitive information.
Detects the deployment of container workloads in Google Cloud Platform (GCP) that utilize the 'break-glass' flag to bypass Binary Authorization controls. This indicates an intentional override of security policies designed to ensure only trusted images are deployed, potentially allowing unauthorized or malicious container images to run.
Detects when a Google Workspace user is granted administrative privileges. This could indicate a legitimate administrative action or a malicious attempt to escalate privileges within the Google Workspace environment.
The following analytic detects the use of default or publicly known named pipes associated with Cobalt Strike. It leverages Sysmon EventID 17 and 18 to identify specific named pipes commonly used by Cobalt Strike's Artifact Kit and Malleable C2 Profiles. This activity is significant because Cobalt Strike is a popular tool for adversaries to conduct post-exploitation tasks, and identifying its named pipes can reveal potential malicious activity. If confirmed malicious, this could indicate an active Cobalt Strike beacon, leading to unauthorized access, data exfiltration, or further lateral movement within the network.
This analytic detects suspicious data transfer activities involving the use of the `split` syscall with the `-b` option, which specifies the size of each output file. This technique can be used by attackers to evade detection by breaking large files into smaller parts, bypassing size-based security controls, and facilitating covert exfiltration of sensitive data. By monitoring for unusual or unauthorized use of the `split` syscall with a specified block size, this analytic helps identify potential data exfiltration attempts.
This analytic identifies the bulk creation of ransomware notes (e.g., .txt, .html, .hta files) on an infected machine. It leverages Sysmon EventCode 11 to detect multiple instances of these file types being created within a short time frame (10 seconds). A detection is triggered if 15 or more unique readme paths are observed. This activity is a strong indicator of an active ransomware attack, where the attacker is notifying the victim of the encryption. If confirmed malicious, this behavior could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
The following analytic detects suspicious attempts to find credentials stored in password stores, indicating a potential attacker's effort to access sensitive login information. Password stores are critical repositories that contain valuable credentials, and unauthorized access to them can lead to significant security breaches. By monitoring for unusual or unauthorized activities related to password store access, this analytic helps identify potential credential theft attempts, allowing security teams to respond promptly and prevent unauthorized access to critical systems and data.
Detects the creation or modification of a GitHub Actions workflow file that attempts to exfiltrate secrets. This pattern is associated with the Shai-Hulud worm, which injects malicious workflows to steal credentials using `toJSON(secrets)` and exfiltrate them using tools like `curl` and `base64`.
This analytic detects the configuration of TFTP services on Cisco IOS devices that could be used to exfiltrate sensitive configuration files. Threat actors like Static Tundra have been observed configuring TFTP servers to make device configuration files accessible for exfiltration after gaining initial access. The detection specifically looks for commands that expose critical configuration files such as startup-config, running-config, and other sensitive system information through TFTP. This activity is particularly concerning as it may represent an attempt to steal credentials, network topology information, and other sensitive data stored in device configurations.
Detects potential data exfiltration from cloud storage or SaaS platforms based on a large volume of data transferred or a high number of distinct files accessed by a single user or application within a one-hour window. This is a common TTP for threat actors like ShinyHunters who aim to steal large datasets.
This rule detects the creation of a Kubernetes pod with a privileged container. Privileged containers have full root capabilities on the host and can bypass many security mechanisms, making them a significant security risk. The rule specifically excludes system service accounts from the 'kube-system' namespace to reduce false positives from legitimate system operations.
This rule detects the creation of Kubernetes pods by non-system service accounts within namespaces that start with 'kube'. This could indicate an attempt to establish persistence or escalate privileges within the Kubernetes cluster by creating malicious pods in critical system namespaces.
SPL Query from file: Enumeration of GCP Infrastructure
'This detection identifies high-severity alerts across various Microsoft security products, including Microsoft Defender XDR and Microsoft Entra ID, and correlates them with instances of Google Cloud VM creation. It focuses on instances where VMs were created within a short timeframe of high-severity alerts, potentially indicating suspicious activity.'
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
Page 9 of 14