updated deperecated functions

capa/features/freeze/__init__.py

@@ -45,7 +45,7 @@ class AddressType(str, Enum):
 
 class Address(HashableModel):
     type: AddressType
-    value: Union[int, Tuple[int, int], None]
+    value: Union[int, Tuple[int, int], None] = None
 
     @classmethod
     def from_capa(cls, a: capa.features.address.Address) -> "Address":

capa/features/freeze/features.py

@@ -211,141 +211,141 @@ def feature_from_capa(f: capa.features.common.Feature) -> "Feature":
 class OSFeature(FeatureModel):
     type: str = "os"
     os: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class ArchFeature(FeatureModel):
     type: str = "arch"
     arch: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class FormatFeature(FeatureModel):
     type: str = "format"
     format: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class MatchFeature(FeatureModel):
     type: str = "match"
     match: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class CharacteristicFeature(FeatureModel):
     type: str = "characteristic"
     characteristic: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class ExportFeature(FeatureModel):
     type: str = "export"
     export: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class ImportFeature(FeatureModel):
     type: str = "import"
     import_: str = Field(alias="import")
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class SectionFeature(FeatureModel):
     type: str = "section"
     section: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class FunctionNameFeature(FeatureModel):
     type: str = "function name"
     function_name: str = Field(alias="function name")
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class SubstringFeature(FeatureModel):
     type: str = "substring"
     substring: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class RegexFeature(FeatureModel):
     type: str = "regex"
     regex: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class StringFeature(FeatureModel):
     type: str = "string"
     string: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class ClassFeature(FeatureModel):
     type: str = "class"
     class_: str = Field(alias="class")
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class NamespaceFeature(FeatureModel):
     type: str = "namespace"
     namespace: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class BasicBlockFeature(FeatureModel):
     type: str = "basic block"
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class APIFeature(FeatureModel):
     type: str = "api"
     api: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class PropertyFeature(FeatureModel):
     type: str = "property"
-    access: Optional[str]
+    access: Optional[str] = None
     property: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class NumberFeature(FeatureModel):
     type: str = "number"
     number: Union[int, float]
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class BytesFeature(FeatureModel):
     type: str = "bytes"
     bytes: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class OffsetFeature(FeatureModel):
     type: str = "offset"
     offset: int
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class MnemonicFeature(FeatureModel):
     type: str = "mnemonic"
     mnemonic: str
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class OperandNumberFeature(FeatureModel):
     type: str = "operand number"
     index: int
     operand_number: int = Field(alias="operand number")
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 class OperandOffsetFeature(FeatureModel):
     type: str = "operand offset"
     index: int
     operand_offset: int = Field(alias="operand offset")
-    description: Optional[str]
+    description: Optional[str] = None
 
 
 Feature = Union[

capa/render/proto/__init__.py

@@ -126,7 +126,7 @@ def metadata_to_pb2(meta: rd.Metadata) -> capa_pb2.Metadata:
         timestamp=str(meta.timestamp),
         version=meta.version,
         argv=meta.argv,
-        sample=google.protobuf.json_format.ParseDict(meta.sample.dict(), capa_pb2.Sample()),
+        sample=google.protobuf.json_format.ParseDict(meta.sample.model_dump(), capa_pb2.Sample()),
         analysis=capa_pb2.Analysis(
             format=meta.analysis.format,
             arch=meta.analysis.arch,
@@ -393,7 +393,7 @@ def match_to_pb2(match: rd.Match) -> capa_pb2.Match:
 def rule_metadata_to_pb2(rule_metadata: rd.RuleMetadata) -> capa_pb2.RuleMetadata:
     # after manual type conversions to the RuleMetadata, we can rely on the protobuf json parser
     # conversions include tuple -> list and rd.Enum -> proto.enum
-    meta = dict_tuple_to_list_values(rule_metadata.dict())
+    meta = dict_tuple_to_list_values(rule_metadata.model_dump())
     meta["scope"] = scope_to_pb2(meta["scope"])
     meta["attack"] = list(map(dict_tuple_to_list_values, meta.get("attack", [])))
     meta["mbc"] = list(map(dict_tuple_to_list_values, meta.get("mbc", [])))

capa/render/result_document.py

@@ -7,7 +7,7 @@
 # See the License for the specific language governing permissions and limitations under the License.
 import datetime
 import collections
-from typing import Dict, List, Tuple, Union, Optional
+from typing import Dict, List, Tuple, Union, Literal, Optional
 
 from pydantic import Field, BaseModel, ConfigDict
 
@@ -80,7 +80,7 @@ class Analysis(Model):
 class Metadata(Model):
     timestamp: datetime.datetime
     version: str
-    argv: Optional[Tuple[str, ...]]
+    argv: Optional[Tuple[str, ...]] = None
     sample: Sample
     analysis: Analysis
 
@@ -102,13 +102,13 @@ class CompoundStatement(StatementModel):
 
 
 class SomeStatement(StatementModel):
-    type: str = "some"
+    type: Literal["some"] = "some"
     description: Optional[str] = None
     count: int
 
 
 class RangeStatement(StatementModel):
-    type: str = "range"
+    type: Literal["range"] = "range"
     description: Optional[str] = None
     min: int
     max: int
@@ -116,7 +116,7 @@ class RangeStatement(StatementModel):
 
 
 class SubscopeStatement(StatementModel):
-    type: str = "subscope"
+    type: Literal["subscope"] = "subscope"
     description: Optional[str] = None
     scope: capa.rules.Scope
 
@@ -131,7 +131,7 @@ Statement = Union[
 
 
 class StatementNode(FrozenModel):
-    type: str = "statement"
+    type: Literal["statement"] = "statement"
     statement: Statement
 
 
@@ -168,7 +168,7 @@ def statement_from_capa(node: capa.engine.Statement) -> Statement:
 
 
 class FeatureNode(FrozenModel):
-    type: str = "feature"
+    type: Literal["feature"] = "feature"
     feature: frz.Feature
 
 
@@ -502,7 +502,7 @@ class MaecMetadata(FrozenModel):
 
 class RuleMetadata(FrozenModel):
     name: str
-    namespace: Optional[str]
+    namespace: Optional[str] = None
     authors: Tuple[str, ...]
     scope: capa.rules.Scope
     attack: Tuple[AttackSpec, ...] = Field(alias="att&ck")

capa/render/vverbose.py

@@ -88,7 +88,7 @@ def render_statement(ostream, match: rd.Match, statement: rd.Statement, indent=0
         # so, we have to inline some of the feature rendering here.
 
         child = statement.child
-        value = child.dict(by_alias=True).get(child.type)
+        value = child.model_dump(by_alias=True).get(child.type)
 
         if value:
             if isinstance(child, frzf.StringFeature):
@@ -141,7 +141,7 @@ def render_feature(ostream, match: rd.Match, feature: frzf.Feature, indent=0):
         value = feature.class_
     else:
         # convert attributes to dictionary using aliased names, if applicable
-        value = feature.dict(by_alias=True).get(key)
+        value = feature.model_dump(by_alias=True).get(key)
 
     if value is None:
         raise ValueError(f"{key} contains None")