GCP Detect gcploit framework
THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
Description
This search provides detection of GCPloit exploitation framework. This framework can be used to escalate privileges and move laterally from compromised high privilege accounts.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Email
- Last Updated: 2020-10-08
- Author: Rod Soto, Splunk
- ID: a1c5a85e-a162-410c-a5d9-99ff639e5a52
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
- Installation
- Delivery
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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3
`google_gcp_pubsub_message` data.protoPayload.request.function.timeout=539s
| table src src_user data.resource.labels.project_id data.protoPayload.request.function.serviceAccountEmail data.protoPayload.authorizationInfo{}.permission data.protoPayload.request.location http_user_agent
| `gcp_detect_gcploit_framework_filter`
Macros
The SPL above uses the following Macros:
gcp_detect_gcploit_framework_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- data.protoPayload.request.function.timeout
- src
- src_user
- data.resource.labels.project_id
- data.protoPayload.request.function.serviceAccountEmail
- data.protoPayload.authorizationInfo{}.permission
- data.protoPayload.request.location
- http_user_agent
How To Implement
You must install splunk GCP add-on. This search works with gcp:pubsub:message logs
Known False Positives
Payload.request.function.timeout value can possibly be match with other functions or requests however the source user and target request account may indicate an attempt to move laterally accross acounts or projects
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | tbd |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1