diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..c56f4dc
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,5 @@
+repos:
+  - repo: https://github.com/psf/black
+    rev: 23.3.0
+    hooks:
+      - id: black
diff --git a/poetry.lock b/poetry.lock
index fcea35c..a1b435c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,533 +1,557 @@
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+    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
+]
+
+[[package]]
+name = "requests"
+version = "2.31.0"
+description = "Python HTTP for Humans."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
+    {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
+]
+
+[package.dependencies]
+certifi = ">=2017.4.17"
+charset-normalizer = ">=2,<4"
+idna = ">=2.5,<4"
+urllib3 = ">=1.21.1,<3"
+
+[package.extras]
+socks = ["PySocks (>=1.5.6,!=1.5.7)"]
+use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
+
+[[package]]
+name = "toml"
+version = "0.10.2"
+description = "Python Library for Tom's Obvious, Minimal Language"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
+    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
+]
+
+[[package]]
+name = "urllib3"
+version = "2.1.0"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
+    {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "f31c46d4d99084e2d62155da577baf537a5ddf4b35024725acaf2c21a9ff03cd"
diff --git a/print-coverage.py b/print-coverage.py
index f9799f6..be0dcdb 100644
--- a/print-coverage.py
+++ b/print-coverage.py
@@ -1,7 +1,7 @@
 # Prints code testing coverage as percentage for badge generation.
-import xml.etree.ElementTree as et
+from defusedxml.ElementTree import parse
 
-tree = et.parse("cov.xml")
+tree = parse("cov.xml")
 root = tree.getroot()
 coverage = float(root.attrib["line-rate"]) * 100
 print(f"COVERAGE={coverage:3.4}%")
@@ -12,4 +12,4 @@
 elif coverage >= 85.0:
     print("COVERAGE_COLOR=orange")
 else:
-    print("COVERAGE_COLOR=red")
\ No newline at end of file
+    print("COVERAGE_COLOR=red")
diff --git a/pyproject.toml b/pyproject.toml
index 428a752..6f573af 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,6 +17,7 @@ pysigma = "^0.10.2"
 [tool.poetry.dev-dependencies]
 pytest = "^6.2.2"
 pytest-cov = "^2.11.1"
+defusedxml = "^0.7.1"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/sigma/backends/splunk/splunk.py b/sigma/backends/splunk/splunk.py
index f591d0a..5f7f7ab 100644
--- a/sigma/backends/splunk/splunk.py
+++ b/sigma/backends/splunk/splunk.py
@@ -3,13 +3,24 @@
 from sigma.rule import SigmaRule
 from sigma.conversion.base import TextQueryBackend
 from sigma.conversion.deferred import DeferredTextQueryExpression
-from sigma.conditions import ConditionFieldEqualsValueExpression, ConditionOR, ConditionAND, ConditionNOT, ConditionItem
+from sigma.conditions import (
+    ConditionFieldEqualsValueExpression,
+    ConditionOR,
+    ConditionAND,
+    ConditionNOT,
+    ConditionItem,
+)
 from sigma.types import SigmaCompareExpression
 from sigma.exceptions import SigmaFeatureNotSupportedByBackendError
-from sigma.pipelines.splunk.splunk import splunk_sysmon_process_creation_cim_mapping, splunk_windows_registry_cim_mapping, splunk_windows_file_event_cim_mapping
+from sigma.pipelines.splunk.splunk import (
+    splunk_sysmon_process_creation_cim_mapping,
+    splunk_windows_registry_cim_mapping,
+    splunk_windows_file_event_cim_mapping,
+)
 import sigma
 from typing import Callable, ClassVar, Dict, List, Optional, Pattern, Tuple
 
+
 class SplunkDeferredRegularExpression(DeferredTextQueryExpression):
     template = 'regex {field}{op}"{value}"'
     operators = {
@@ -18,6 +29,7 @@ class SplunkDeferredRegularExpression(DeferredTextQueryExpression):
     }
     default_field = "_raw"
 
+
 class SplunkDeferredCIDRExpression(DeferredTextQueryExpression):
     template = 'where {op}cidrmatch("{value}", {field})'
     operators = {
@@ -26,68 +38,94 @@ class SplunkDeferredCIDRExpression(DeferredTextQueryExpression):
     }
     default_field = "_raw"
 
+
 class SplunkBackend(TextQueryBackend):
     """Splunk SPL backend."""
-    name : ClassVar[str] = "Splunk SPL & tstats data model queries"               # A descriptive name of the backend
-    formats : ClassVar[Dict[str, str]] = {                # Output formats provided by the backend as name -> description mapping. The name should match to finalize_output_<name>.
+
+    name: ClassVar[
+        str
+    ] = "Splunk SPL & tstats data model queries"  # A descriptive name of the backend
+    formats: ClassVar[
+        Dict[str, str]
+    ] = {  # Output formats provided by the backend as name -> description mapping. The name should match to finalize_output_<name>.
         "default": "Plain SPL queries",
         "savedsearches": "Plain SPL in a savedsearches.conf file",
-        "data_model": "Data model queries with tstats"
+        "data_model": "Data model queries with tstats",
     }
-    requires_pipeline : ClassVar[bool] = True             # Does the backend requires that a processing pipeline is provided?
+    requires_pipeline: ClassVar[
+        bool
+    ] = True  # Does the backend requires that a processing pipeline is provided?
 
-    precedence: ClassVar[Tuple[ConditionItem, ConditionItem, ConditionItem]] = (ConditionNOT, ConditionOR, ConditionAND)
-    group_expression : ClassVar[str] = "({expr})"
+    precedence: ClassVar[Tuple[ConditionItem, ConditionItem, ConditionItem]] = (
+        ConditionNOT,
+        ConditionOR,
+        ConditionAND,
+    )
+    group_expression: ClassVar[str] = "({expr})"
 
-    or_token : ClassVar[str] = "OR"
-    and_token : ClassVar[str] = " "
-    not_token : ClassVar[str] = "NOT"
-    eq_token : ClassVar[str] = "="
+    or_token: ClassVar[str] = "OR"
+    and_token: ClassVar[str] = " "
+    not_token: ClassVar[str] = "NOT"
+    eq_token: ClassVar[str] = "="
 
     field_quote: ClassVar[str] = '"'
-    field_quote_pattern: ClassVar[Pattern] = re.compile("^[\w.]+$")
-
-    str_quote : ClassVar[str] = '"'
-    escape_char : ClassVar[str] = "\\"
-    wildcard_multi : ClassVar[str] = "*"
-    wildcard_single : ClassVar[str] = "*"
-    add_escaped : ClassVar[str] = "\\"
-
-    re_expression : ClassVar[str] = "{regex}"
-    re_escape_char : ClassVar[str] = "\\"
-    re_escape : ClassVar[Tuple[str]] = ('"',)
-
-    cidr_expression : ClassVar[str] = "{value}"
-
-    compare_op_expression : ClassVar[str] = "{field}{operator}{value}"
-    compare_operators : ClassVar[Dict[SigmaCompareExpression.CompareOperators, str]] = {
-        SigmaCompareExpression.CompareOperators.LT  : "<",
-        SigmaCompareExpression.CompareOperators.LTE : "<=",
-        SigmaCompareExpression.CompareOperators.GT  : ">",
-        SigmaCompareExpression.CompareOperators.GTE : ">=",
+    field_quote_pattern: ClassVar[Pattern] = re.compile(r"^[\w.]+$")
+
+    str_quote: ClassVar[str] = '"'
+    escape_char: ClassVar[str] = "\\"
+    wildcard_multi: ClassVar[str] = "*"
+    wildcard_single: ClassVar[str] = "*"
+    add_escaped: ClassVar[str] = "\\"
+
+    re_expression: ClassVar[str] = "{regex}"
+    re_escape_char: ClassVar[str] = "\\"
+    re_escape: ClassVar[Tuple[str]] = ('"',)
+
+    cidr_expression: ClassVar[str] = "{value}"
+
+    compare_op_expression: ClassVar[str] = "{field}{operator}{value}"
+    compare_operators: ClassVar[Dict[SigmaCompareExpression.CompareOperators, str]] = {
+        SigmaCompareExpression.CompareOperators.LT: "<",
+        SigmaCompareExpression.CompareOperators.LTE: "<=",
+        SigmaCompareExpression.CompareOperators.GT: ">",
+        SigmaCompareExpression.CompareOperators.GTE: ">=",
     }
 
-    field_null_expression : ClassVar[str] = "{field}!=*"
+    field_null_expression: ClassVar[str] = "{field}!=*"
 
-    convert_or_as_in : ClassVar[bool] = True
-    convert_and_as_in : ClassVar[bool] = False
-    in_expressions_allow_wildcards : ClassVar[bool] = True
-    field_in_list_expression : ClassVar[str] = "{field} {op} ({list})"
-    or_in_operator : ClassVar[Optional[str]] = "IN"
-    list_separator : ClassVar[str] = ", "
+    convert_or_as_in: ClassVar[bool] = True
+    convert_and_as_in: ClassVar[bool] = False
+    in_expressions_allow_wildcards: ClassVar[bool] = True
+    field_in_list_expression: ClassVar[str] = "{field} {op} ({list})"
+    or_in_operator: ClassVar[Optional[str]] = "IN"
+    list_separator: ClassVar[str] = ", "
 
-    unbound_value_str_expression : ClassVar[str] = '{value}'
-    unbound_value_num_expression : ClassVar[str] = '{value}'
-    unbound_value_re_expression : ClassVar[str] = '{value}'
+    unbound_value_str_expression: ClassVar[str] = "{value}"
+    unbound_value_num_expression: ClassVar[str] = "{value}"
+    unbound_value_re_expression: ClassVar[str] = "{value}"
 
-    deferred_start : ClassVar[str] = "\n| "
-    deferred_separator : ClassVar[str] = "\n| "
-    deferred_only_query : ClassVar[str] = "*"
+    deferred_start: ClassVar[str] = "\n| "
+    deferred_separator: ClassVar[str] = "\n| "
+    deferred_only_query: ClassVar[str] = "*"
 
-    def __init__(self, processing_pipeline: Optional["sigma.processing.pipeline.ProcessingPipeline"] = None, collect_errors: bool = False, min_time : str = "-30d", max_time : str = "now", query_settings : Callable[[SigmaRule], Dict[str, str]] = lambda x: {}, output_settings : Dict = {}, **kwargs):
+    def __init__(
+        self,
+        processing_pipeline: Optional[
+            "sigma.processing.pipeline.ProcessingPipeline"
+        ] = None,
+        collect_errors: bool = False,
+        min_time: str = "-30d",
+        max_time: str = "now",
+        query_settings: Callable[[SigmaRule], Dict[str, str]] = lambda x: {},
+        output_settings: Dict = {},
+        **kwargs,
+    ):
         super().__init__(processing_pipeline, collect_errors, **kwargs)
         self.query_settings = query_settings
-        self.output_settings = {"dispatch.earliest_time": min_time, "dispatch.latest_time": max_time}
+        self.output_settings = {
+            "dispatch.earliest_time": min_time,
+            "dispatch.latest_time": max_time,
+        }
         self.output_settings.update(output_settings)
 
     @staticmethod
@@ -95,80 +133,136 @@ def _generate_settings(settings):
         """Format a settings dict into newline separated k=v string. Escape multi-line values."""
         output = ""
         for k, v in settings.items():
-            output += f"\n{k} = " + " \\\n".join(v.split("\n"))  # cannot use \ in f-strings
+            output += f"\n{k} = " + " \\\n".join(
+                v.split("\n")
+            )  # cannot use \ in f-strings
         return output
 
-    def convert_condition_field_eq_val_re(self, cond : ConditionFieldEqualsValueExpression, state : "sigma.conversion.state.ConversionState") -> SplunkDeferredRegularExpression:
+    def convert_condition_field_eq_val_re(
+        self,
+        cond: ConditionFieldEqualsValueExpression,
+        state: "sigma.conversion.state.ConversionState",
+    ) -> SplunkDeferredRegularExpression:
         """Defer regular expression matching to pipelined regex command after main search expression."""
         if cond.parent_condition_chain_contains(ConditionOR):
-            raise SigmaFeatureNotSupportedByBackendError("ORing regular expressions is not yet supported by Splunk backend", source=cond.source)
-        return SplunkDeferredRegularExpression(state, cond.field, super().convert_condition_field_eq_val_re(cond, state)).postprocess(None, cond)
+            raise SigmaFeatureNotSupportedByBackendError(
+                "ORing regular expressions is not yet supported by Splunk backend",
+                source=cond.source,
+            )
+        return SplunkDeferredRegularExpression(
+            state, cond.field, super().convert_condition_field_eq_val_re(cond, state)
+        ).postprocess(None, cond)
 
-    def convert_condition_field_eq_val_cidr(self, cond : ConditionFieldEqualsValueExpression, state : "sigma.conversion.state.ConversionState") -> SplunkDeferredCIDRExpression:
+    def convert_condition_field_eq_val_cidr(
+        self,
+        cond: ConditionFieldEqualsValueExpression,
+        state: "sigma.conversion.state.ConversionState",
+    ) -> SplunkDeferredCIDRExpression:
         """Defer CIDR network range matching to pipelined where cidrmatch command after main search expression."""
         if cond.parent_condition_chain_contains(ConditionOR):
-            raise SigmaFeatureNotSupportedByBackendError("ORing CIDR matching is not yet supported by Splunk backend", source=cond.source)
-        return SplunkDeferredCIDRExpression(state, cond.field, super().convert_condition_field_eq_val_cidr(cond, state)).postprocess(None, cond)
+            raise SigmaFeatureNotSupportedByBackendError(
+                "ORing CIDR matching is not yet supported by Splunk backend",
+                source=cond.source,
+            )
+        return SplunkDeferredCIDRExpression(
+            state, cond.field, super().convert_condition_field_eq_val_cidr(cond, state)
+        ).postprocess(None, cond)
 
-    def finalize_query_default(self, rule : SigmaRule, query : str, index : int, state : ConversionState) -> str:
+    def finalize_query_default(
+        self, rule: SigmaRule, query: str, index: int, state: ConversionState
+    ) -> str:
         table_fields = " | table " + ",".join(rule.fields) if rule.fields else ""
         return query + table_fields
 
-    def finalize_query_savedsearches(self, rule: SigmaRule, query: str, index: int, state: ConversionState) -> str:
-        clean_title = rule.title.translate({ord(c): None for c in "[]"})      # remove brackets from title
+    def finalize_query_savedsearches(
+        self, rule: SigmaRule, query: str, index: int, state: ConversionState
+    ) -> str:
+        clean_title = rule.title.translate(
+            {ord(c): None for c in "[]"}
+        )  # remove brackets from title
         query_settings = self.query_settings(rule)
-        query_settings["description"] = rule.description.strip() if rule.description else ""
-        query_settings["search"] = query + ("\n| table " + ",".join(rule.fields) if rule.fields else "")
+        query_settings["description"] = (
+            rule.description.strip() if rule.description else ""
+        )
+        query_settings["search"] = query + (
+            "\n| table " + ",".join(rule.fields) if rule.fields else ""
+        )
 
         return f"\n[{clean_title}]" + self._generate_settings(query_settings)
 
     def finalize_output_savedsearches(self, queries: List[str]) -> str:
-        return f"\n[default]" + self._generate_settings(self.output_settings) + "\n" + "\n".join(queries)
+        return (
+            f"\n[default]"
+            + self._generate_settings(self.output_settings)
+            + "\n"
+            + "\n".join(queries)
+        )
 
-    def finalize_query_data_model(self, rule: SigmaRule, query: str, index: int, state: ConversionState) -> str:
+    def finalize_query_data_model(
+        self, rule: SigmaRule, query: str, index: int, state: ConversionState
+    ) -> str:
         data_model = None
         data_set = None
         cim_fields = None
         if rule.logsource.product and rule.logsource.category:
             if rule.logsource.product == "windows":
                 if rule.logsource.category == "process_creation":
-                    data_model = 'Endpoint'
-                    data_set = 'Processes'
-                    cim_fields = " ".join(splunk_sysmon_process_creation_cim_mapping.values())
-                elif rule.logsource.category in ["registry_add", "registry_delete", "registry_event", "registry_set"]:
-                    data_model = 'Endpoint'
-                    data_set = 'Registry'
+                    data_model = "Endpoint"
+                    data_set = "Processes"
+                    cim_fields = " ".join(
+                        splunk_sysmon_process_creation_cim_mapping.values()
+                    )
+                elif rule.logsource.category in [
+                    "registry_add",
+                    "registry_delete",
+                    "registry_event",
+                    "registry_set",
+                ]:
+                    data_model = "Endpoint"
+                    data_set = "Registry"
                     cim_fields = " ".join(splunk_windows_registry_cim_mapping.values())
                 elif rule.logsource.category == "file_event":
-                    data_model = 'Endpoint'
-                    data_set = 'Filesystem'
-                    cim_fields = " ".join(splunk_windows_file_event_cim_mapping.values())
+                    data_model = "Endpoint"
+                    data_set = "Filesystem"
+                    cim_fields = " ".join(
+                        splunk_windows_file_event_cim_mapping.values()
+                    )
             elif rule.logsource.product == "linux":
                 if rule.logsource.category == "process_creation":
-                    data_model = 'Endpoint'
-                    data_set = 'Processes'
-                    cim_fields = " ".join(splunk_sysmon_process_creation_cim_mapping.values())
+                    data_model = "Endpoint"
+                    data_set = "Processes"
+                    cim_fields = " ".join(
+                        splunk_sysmon_process_creation_cim_mapping.values()
+                    )
 
         try:
             data_model_set = state.processing_state["data_model_set"]
         except KeyError:
-            raise SigmaFeatureNotSupportedByBackendError("No data model specified by processing pipeline")
+            raise SigmaFeatureNotSupportedByBackendError(
+                "No data model specified by processing pipeline"
+            )
 
         try:
             data_set = data_model_set.split(".")[1]
         except IndexError:
-            raise SigmaFeatureNotSupportedByBackendError("No data set specified by processing pipeline")
+            raise SigmaFeatureNotSupportedByBackendError(
+                "No data set specified by processing pipeline"
+            )
 
         try:
             fields = " ".join(state.processing_state["fields"])
         except KeyError:
-            raise SigmaFeatureNotSupportedByBackendError("No fields specified by processing pipeline")
+            raise SigmaFeatureNotSupportedByBackendError(
+                "No fields specified by processing pipeline"
+            )
 
         return f"""| tstats summariesonly=false allow_old_summaries=true fillnull_value="null" count min(_time) as firstTime max(_time) as lastTime from datamodel={data_model_set} where {query} by {fields}
 | `drop_dm_object_name({data_set})`
 | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime(firstTime)
 | convert timeformat="%Y-%m-%dT%H:%M:%S" ctime(lastTime)
-""".replace("\n", " ")
+""".replace(
+            "\n", " "
+        )
 
     def finalize_output_data_model(self, queries: List[str]) -> List[str]:
-        return queries
\ No newline at end of file
+        return queries