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pyth0n1c
2022-04-11 10:23:33 -07:00
committed by GitHub
parent 0ee6e97727 8a75b7ee7c
commit cc4c80a7e9
11 changed files with 25 additions and 364 deletions
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.github/workflows/build-and-validate.yml
-10
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@@ -426,16 +426,6 @@ jobs:
source venv/bin/activate
python3 contentctl.py -p . docgen -o docs
# this step is creating some TOKEN issues while tagging a build, commenting this out for now
# - name: Enrich detections with TAs
# env:
# GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# run: |
# source venv/bin/activate
# python3 -m pip install -r security_content_automation/requirements.txt
# python3 security_content_automation/enrich_detections.py
- name: Update github with new docs and package bits
run: |
rm -rf dist
detections/deprecated/suspicious_rundll32_rename.yml
+3 -3
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@@ -1,7 +1,7 @@
name: Suspicious Rundll32 Rename
id: 7360137f-abad-473e-8189-acbdaa34d114
version: 4
date: '2022-02-01'
version: 5
date: '2022-04-07'
author: Michael Haag, Splunk
type: Hunting
datamodel:
@@ -13,7 +13,7 @@ description: The following hunting analytic identifies renamed instances of rund
name from the PE meta data. Expand the query as needed by looking for specific command
line arguments outlined in other analytics.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_rundll32` by Processes.dest
as lastTime from datamodel=Endpoint.Processes where Processes.original_file_name=RUNDLL32.exe AND Processes.process_name!=rundll32.exe by Processes.dest
Processes.user Processes.parent_process_name Processes.process_name Processes.process
Processes.process_id Processes.parent_process_id Processes.original_file_name |
`drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
detections/endpoint/any_powershell_downloadfile.yml
+3 -2
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@@ -1,7 +1,7 @@
name: Any Powershell DownloadFile
id: 1a93b7ea-7af7-11eb-adb5-acde48001122
version: 2
date: '2021-03-01'
version: 3
date: '2022-04-07'
author: Michael Haag, Splunk
type: TTP
datamodel:
@@ -52,6 +52,7 @@ tags:
mitre_attack_id:
- T1059
- T1059.001
- T1105
observable:
- name: user
type: User
detections/endpoint/any_powershell_downloadstring.yml
+3 -2
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@@ -1,7 +1,7 @@
name: Any Powershell DownloadString
id: 4d015ef2-7adf-11eb-95da-acde48001122
version: 2
date: '2021-03-01'
version: 3
date: '2022-04-07'
author: Michael Haag, Splunk
type: TTP
datamodel:
@@ -49,6 +49,7 @@ tags:
mitre_attack_id:
- T1059
- T1059.001
- T1105
observable:
- name: user
type: User
detections/endpoint/detect_html_help_renamed.yml
+3 -3
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@@ -1,7 +1,7 @@
name: Detect HTML Help Renamed
id: 62fed254-513b-460e-953d-79771493a9f3
version: 3
date: '2021-09-16'
version: 4
date: '2022-04-07'
author: Michael Haag, Splunk
type: Hunting
datamodel:
@@ -18,7 +18,7 @@ description: The following analytic identifies a renamed instance of hh.exe (HTM
it is the legitimate version of hh.exe by reviewing the PE metadata. hh.exe is natively
found in C:\Windows\system32 and C:\Windows\syswow64.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_hh` by Processes.dest
as lastTime from datamodel=Endpoint.Processes where Processes.process_name!=hh.exe AND Processes.original_file_name=HH.EXE by Processes.dest
Processes.user Processes.parent_process_name Processes.original_file_name Processes.process_name
Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_html_help_renamed_filter`'
detections/endpoint/detect_mshta_renamed.yml
+3 -3
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@@ -1,7 +1,7 @@
name: Detect mshta renamed
id: 8f45fcf0-5b68-11eb-ae93-0242ac130002
version: 2
date: '2021-09-16'
version: 3
date: '2022-04-07'
author: Michael Haag, Splunk
type: Hunting
datamodel:
@@ -12,7 +12,7 @@ description: The following analytic identifies renamed instances of mshta.exe ex
binary. Further analysis should be performed to review the executed content and
validation it is the real mshta.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_mshta` by Processes.dest
as lastTime from datamodel=Endpoint.Processes where Processes.process_name!=mshta.exe AND Processes.original_file_name=MSHTA.EXE by Processes.dest
Processes.user Processes.parent_process_name Processes.process_name Processes.process
Processes.process_id Processes.parent_process_id Processes.original_file_name |
`drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
detections/endpoint/detect_renamed_psexec.yml
+3 -3
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@@ -1,7 +1,7 @@
name: Detect Renamed PSExec
id: 683e6196-b8e8-11eb-9a79-acde48001122
version: 3
date: '2021-09-16'
version: 4
date: '2022-04-07'
author: Michael Haag, Splunk
type: Hunting
datamodel:
@@ -12,7 +12,7 @@ description: The following analytic identifies renamed instances of `PsExec.exe`
During triage, validate this is the legitimate version of `PsExec` by reviewing
the PE metadata. In addition, review parallel processes for further suspicious behavior.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_psexec` by Processes.dest
as lastTime from datamodel=Endpoint.Processes where (Processes.process_name!=psexec.exe OR Processes.process_name!=psexec64.exe) AND Processes.original_file_name=psexec.c by Processes.dest
Processes.user Processes.parent_process_name Processes.process_name Processes.process
Processes.process_id Processes.parent_process_id Processes.original_file_name |
`drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
detections/endpoint/suspicious_microsoft_workflow_compiler_rename.yml
+3 -3
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@@ -1,7 +1,7 @@
name: Suspicious microsoft workflow compiler rename
id: f0db4464-55d9-11eb-ae93-0242ac130002
version: 3
date: '2021-09-20'
version: 4
date: '2022-04-07'
author: Michael Haag, Splunk
type: Hunting
datamodel:
@@ -13,7 +13,7 @@ description: The following analytic identifies a renamed instance of microsoft.w
In any instance, microsoft.workflow.compiler.exe spawning from an Office product
or any living off the land binary is highly suspect.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_microsoftworkflowcompiler`
as lastTime from datamodel=Endpoint.Processes where Processes.process_name!=microsoft.workflow.compiler.exe AND Processes.original_file_name=Microsoft.Workflow.Compiler.exe
by Processes.dest Processes.user Processes.parent_process_name Processes.process_name
Processes.process Processes.process_id Processes.parent_process_id Processes.original_file_name
| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
detections/endpoint/suspicious_msbuild_rename.yml
+4 -4
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@@ -1,9 +1,9 @@
name: Suspicious MSBuild Rename
id: 4006adac-5937-11eb-ae93-0242ac130002
version: 2
date: '2021-01-12'
version: 3
date: '2022-04-07'
author: Michael Haag, Splunk
type: TTP
type: Hunting
datamodel:
- Endpoint
description: The following analytic identifies renamed instances of msbuild.exe executing.
@@ -11,7 +11,7 @@ description: The following analytic identifies renamed instances of msbuild.exe
C:\Windows\Microsoft.NET\Framework64\v4.0.30319. During investigation, identify
the code executed and what is executing a renamed instance of MSBuild.
search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)
as lastTime from datamodel=Endpoint.Processes where `process_msbuild` by Processes.dest
as lastTime from datamodel=Endpoint.Processes where Processes.process_name!=msbuild.exe AND Processes.original_file_name=MSBuild.exe by Processes.dest
Processes.user Processes.parent_process_name Processes.process_name Processes.process
Processes.process_id Processes.parent_process_id Processes.original_file_name |
`drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
security_content_automation/enrich_detections.py
-328
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@@ -1,328 +0,0 @@
import base64
import csv
import io
import json
import logging
import os
import re
import shutil
import sys
import time
from pathlib import Path
import git
import yaml
from github import Github
TIMESTAMP_FORMAT = '%(asctime)s %(levelname)s - %(message)s'
def fetch_ta_cim_mapping_report(file_name):
try:
with open(file_name) as file_content:
cim_field_report = json.load(file_content)
return cim_field_report
except Exception as error:
error_message = f"Unexpected error occurred while reading file. {error}"
logging.error(error_message)
def load_file(file_path):
try:
with open(file_path, "r", encoding="utf-8") as stream:
file = list(yaml.safe_load_all(stream))[0]
return file
except yaml.YAMLError as exc:
sys.exit("ERROR: reading {0}".format(file_path))
def map_required_fields(cim_summary, datamodel, required_fields):
datasets_fields = {}
add_addon = False
flag = 0
for item in required_fields:
# Only required field with valid format will be mapped
if re.match("^[A-Za-z0-9_.]*$", item):
if item == "_time" or item == "_times":
continue
else:
dataset_field = item.split(".")
length = len(dataset_field)
if length == 1:
dataset = datamodel[0]
field = dataset_field[0]
else:
dataset = dataset_field[length - 2]
field = dataset_field[length - 1]
if dataset not in datasets_fields:
datasets_fields[dataset] = []
datasets_fields[dataset].append(field)
for dataset in datasets_fields:
add_addon = False
mapping_set = datamodel[0] + ":" + dataset
for item in cim_summary:
if mapping_set in item:
for eventtype in cim_summary[item].values():
for e_type in eventtype:
cim_fields = e_type.get("fields", [])
if set(datasets_fields[dataset]).issubset(set(cim_fields)):
add_addon = True
if add_addon == False:
return add_addon
return add_addon
def is_valid_detection_file(filepath):
detection_analytic_type = ["ttp", "anomaly"]
detection_with_valid_analytic_type = False
detection_with_valid_datamodel = False
detection_file_path = load_file(filepath)
if detection_file_path.get("type", "").lower() in detection_analytic_type:
detection_with_valid_analytic_type = True
if detection_file_path.get("datamodel", []):
detection_with_valid_datamodel = True
return detection_with_valid_analytic_type & detection_with_valid_datamodel
def enrich_detection_file(file, ta_list, keyname):
detection_obj = load_file(file)
detection_obj["tags"][keyname] = ta_list
with open(file, "w") as f:
yaml.dump(detection_obj, f, sort_keys=False, allow_unicode=True)
def main():
security_content_repo = "splunk/security_content"
security_content_branch = "develop"
ta_cim_field_reports_repo = "splunk/ta-cim-field-reports"
ta_cim_field_reports_branch = "main"
# Decodin GITHUB_ACCESS_TOKEN from base64
git_token_base64_bytes = os.environ.get("GITHUB_ACCESS_TOKEN").encode('ascii')
git_token_bytes = base64.b64decode(git_token_base64_bytes)
github_token = git_token_bytes.decode('ascii')
git_token = Github(github_token)
detection_types = ["cloud", "endpoint", "network"]
cim_report_path = (
"ta_cim_mapping_reports/ta_cim_mapping/cim_mapping_reports/latest/"
)
detection_ta_mapping = {}
try:
# clone security content repository
security_content_repo_obj = git.Repo.clone_from(
"https://"
+ github_token
+ ":x-oauth-basic@github.com/"
+ security_content_repo,
"security_content",
branch=security_content_branch,
)
message = "Successfully cloned security_content."
logging.info(message)
except Exception as error:
error_message = f"Unexpected error occurred while Cloning security_content, {error}"
logging.error(error_message)
try:
# clone ta cim field reports repository
ta_cim_field_reports_obj = git.Repo.clone_from(
"https://"
+ github_token
+ ":x-oauth-basic@github.com/"
+ ta_cim_field_reports_repo,
"ta_cim_mapping_reports",
branch=ta_cim_field_reports_branch,
)
message = "Successfully cloned ta_cim_mapping_reports."
logging.info(message)
except Exception as error:
error_message = f"Unexpected error occurred while Cloning ta-cim-field-reports repo, {error}"
logging.error(error_message)
# iterate for every detection types
for detection_type in detection_types:
for subdir, _, files in os.walk(f"security_content/tests/{detection_type}"):
for file in files:
filepath = subdir + os.sep + file
tas_with_cim_mapping_list = []
supported_tas_list = []
detection_obj = load_file(filepath)
source_types = []
for data in detection_obj.get("tests")[0].get("attack_data"):
source_types.append(data.get("sourcetype"))
detection_file_name_path = (
detection_obj.get("tests")[0]
.get("file")
.rsplit("/", 1)[1]
)
detection_file_name = Path(detection_file_name_path).stem
filepath = "security_content/detections/" + detection_obj.get("tests")[
0
].get("file")
if not os.path.isfile(filepath):
continue
if is_valid_detection_file(filepath):
for ta_cim_mapping_file in os.listdir(cim_report_path):
ta_cim_map = fetch_ta_cim_mapping_report(
cim_report_path + ta_cim_mapping_file
)
detection_obj = load_file(filepath)
required_fields = detection_obj.get("tags", {}).get(
"required_fields"
)
datamodel = detection_obj.get("datamodel", [])
result = map_required_fields(
ta_cim_map["cimsummary"], datamodel, required_fields
)
cim_version = ta_cim_map["cim_version"]
if result:
tas_with_cim_mapping_list.append(
ta_cim_map.get("ta_name").get("name")
)
ta_sourcetype = ta_cim_map["sourcetypes"]
for source_type in source_types:
if (
source_type in ta_sourcetype
and ta_cim_map.get("ta_name").get("name")
not in supported_tas_list
):
supported_tas_list.append(
ta_cim_map.get("ta_name").get("name")
)
detection_ta_mapping[detection_file_name] = {}
if tas_with_cim_mapping_list:
keyname = "tas_with_cim_mapping"
detection_ta_mapping[detection_file_name][
"cim_version"
] = cim_version
detection_ta_mapping[detection_file_name][
keyname
] = tas_with_cim_mapping_list
if supported_tas_list:
keyname = "supported_tas"
enrich_detection_file(filepath, supported_tas_list, keyname)
detection_ta_mapping[detection_file_name][
keyname
] = supported_tas_list
logging.info(f"Enriched {detection_file_name} with supported TAs : {supported_tas_list}")
security_content_repo_obj.index.add(
[filepath.strip("security_content/")]
)
# Generating detection_ta_mapping yml file
try:
with io.open(
r"./security_content/security_content_automation/detection_ta_mapping.yml",
"w",
encoding="utf8",
) as outfile:
yaml.safe_dump(
detection_ta_mapping, outfile, default_flow_style=False, allow_unicode=True
)
security_content_repo_obj.index.add(
["security_content_automation/detection_ta_mapping.yml"]
)
message = "Created detection_ta_mapping.yml file"
logging.info(message)
except Exception as error:
error_message = f"Unexpected error occurred while generating detection_ta_mapping.yml file, {error}"
logging.error(error_message)
# Generating detection_ta_mapping CSV report
try:
with open(r"./security_content/security_content_automation/detection_ta_mapping.csv", 'w+', newline='') as csv_file:
fieldnames = ['detection_name', 'cim_version', 'supported_tas', 'tas_with_cim_mapping']
writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
writer.writeheader()
for detection_name, detection_content in detection_ta_mapping.items():
detection_content.update({
'tas_with_cim_mapping': ', '.join(detection_content["tas_with_cim_mapping"]) if detection_content.get(
'tas_with_cim_mapping') else '',
'supported_tas': ', '.join(detection_content["supported_tas"]) if detection_content.get(
'supported_tas') else '',
'detection_name': detection_name
})
writer.writerow(detection_content)
security_content_repo_obj.index.add(
["security_content_automation/detection_ta_mapping.csv"]
)
message = "Created detection_ta_mapping.csv file"
logging.info(message)
except Exception as error:
error_message = f"Unexpected error occurred while generating detection_ta_mapping CSV report, {error}"
logging.error(error_message)
try:
security_content_repo_obj.index.commit(
"Updated detection files with recommended TA list."
)
epoch_time = str(int(time.time()))
branch_name = "security_content_automation_" + epoch_time
security_content_repo_obj.git.checkout("-b", branch_name)
security_content_repo_obj.git.push("--set-upstream", "origin", branch_name)
repo = git_token.get_repo("splunk/security_content")
pr = repo.create_pull(
title="Enrich Detection PR " + branch_name,
body="Enriched the detections with supported TAs",
head=branch_name,
base="develop",
)
message = "Created pull request"
logging.info(message)
except Exception as error:
error_message = f"Unexpected error occurred while creating pull request, {error}"
logging.error(error_message)
try:
shutil.rmtree("./security_content")
shutil.rmtree("./ta_cim_mapping_reports")
message = "Cleaned up the environment"
logging.info(message)
except OSError as e:
error_message = f"Unexpected error occurred while deleting files, {error}"
logging.error(error_message)
if __name__ == "__main__":
log_level=logging.INFO
handlers = [logging.StreamHandler()]
logging.basicConfig(level=log_level, format=TIMESTAMP_FORMAT, handlers=handlers)
main()
security_content_automation/requirements.txt
-3
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@@ -1,3 +0,0 @@
GitPython==3.1.24
PyYAML==6.0
PyGithub==1.55