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feat(mcp_server): add tools related with attack paths (#10145)
This commit is contained in:
Rubén De la Torre Vico
committed by
GitHub
GitHub
parent
2115344de8
commit
a8e504887b
@@ -2,6 +2,10 @@
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All notable changes to the **Prowler MCP Server** are documented in this file.
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## [0.4.0] (Prowler UNRELEASED)
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- Add new MCP Server tools for Prowler Attack Paths [(#10145)](https://github.com/prowler-cloud/prowler/pull/10145)
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## [0.3.0] (Prowler v5.16.0)
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### Added
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338
mcp_server/prowler_mcp_server/prowler_app/models/attack_paths.py
Normal file
338
mcp_server/prowler_mcp_server/prowler_app/models/attack_paths.py
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@@ -0,0 +1,338 @@
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"""Data models for Attack Paths scans and queries.
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This module provides Pydantic models for representing Attack Paths data
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with two-tier complexity:
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- AttackPathScan: For list operations with essential fields
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- AttackPathQuery: Query definition with parameters
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- AttackPathQueryResult: Graph result with nodes, relationships, and summary
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All models inherit from MinimalSerializerMixin to exclude None/empty values
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for optimal LLM token usage.
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"""
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from typing import Any, Literal
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from prowler_mcp_server.prowler_app.models.base import MinimalSerializerMixin
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from pydantic import BaseModel, ConfigDict, Field
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class AttackPathScan(MinimalSerializerMixin, BaseModel):
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"""Simplified attack paths scan representation for list operations.
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Includes core fields for efficient overview.
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Used by list_attack_paths_scans() tool.
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"""
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model_config = ConfigDict(frozen=True)
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id: str = Field(description="Unique UUIDv4 identifier for this attack paths scan")
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state: Literal[
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"available", "scheduled", "executing", "completed", "failed", "cancelled"
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] = Field(
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description="Current state of the scan: available, scheduled, executing, completed, failed, or cancelled"
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)
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progress: int = Field(
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default=0, description="Scan completion progress as percentage (0-100)"
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)
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provider_id: str = Field(
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description="UUIDv4 identifier of the provider this scan is associated with"
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)
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provider_alias: str | None = Field(
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default=None,
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description="Human-friendly alias for the provider",
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)
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provider_type: str | None = Field(
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default=None,
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description="Cloud provider type (aws, azure, gcp, etc.)",
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)
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provider_uid: str | None = Field(
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default=None,
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description="Provider's external identifier (e.g., AWS Account ID)",
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)
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@classmethod
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def from_api_response(cls, data: dict[str, Any]) -> "AttackPathScan":
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"""Transform JSON:API attack paths scan response to simplified model.
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Args:
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data: Scan data from API response['data'] (single item or list item)
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Returns:
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AttackPathScan instance
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"""
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attributes = data["attributes"]
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relationships = data.get("relationships", {})
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provider_id = relationships.get("provider", {}).get("data", {}).get("id")
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return cls(
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id=data["id"],
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state=attributes["state"],
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progress=attributes.get("progress", 0),
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provider_id=provider_id,
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provider_alias=attributes.get("provider_alias"),
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provider_type=attributes.get("provider_type"),
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provider_uid=attributes.get("provider_uid"),
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)
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class AttackPathScansListResponse(BaseModel):
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"""Response model for list_attack_paths_scans() with pagination metadata.
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Follows established pattern from ScansListResponse.
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"""
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scans: list[AttackPathScan]
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total_num_scans: int
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total_num_pages: int
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current_page: int
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@classmethod
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def from_api_response(
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cls, response: dict[str, Any]
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) -> "AttackPathScansListResponse":
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"""Transform JSON:API list response to scans list with pagination.
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Args:
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response: Full API response with data and meta
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Returns:
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AttackPathScansListResponse with simplified scans and pagination metadata
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"""
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pagination = response.get("meta", {}).get("pagination", None)
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if pagination is None:
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raise ValueError("Missing pagination metadata in API response")
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else:
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# Transform each scan
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scans = [
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AttackPathScan.from_api_response(item)
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for item in response.get("data", [])
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]
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return cls(
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scans=scans,
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total_num_scans=pagination.get("count"),
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total_num_pages=pagination.get("pages"),
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current_page=pagination.get("page"),
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)
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class AttackPathQueryParameter(MinimalSerializerMixin, BaseModel):
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"""Parameter definition for an attack paths query.
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Describes a parameter that must be provided when running a query.
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"""
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model_config = ConfigDict(frozen=True)
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name: str = Field(description="Parameter name used in the query")
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label: str = Field(description="Human-readable label for the parameter")
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data_type: str = Field(
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default="string", description="Data type of the parameter (e.g., 'string')"
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)
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description: str | None = Field(
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default=None, description="Detailed description of what the parameter is for"
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)
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placeholder: str | None = Field(
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default=None, description="Example value for the parameter"
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)
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@classmethod
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def from_api_response(cls, data: dict[str, Any]) -> "AttackPathQueryParameter":
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"""Transform parameter data to model.
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Args:
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data: Parameter data from API response
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Returns:
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AttackPathQueryParameter instance
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"""
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return cls(
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name=data["name"],
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label=data["label"],
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data_type=data.get("data_type", "string"),
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description=data.get("description"),
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placeholder=data.get("placeholder"),
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)
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class AttackPathQuery(MinimalSerializerMixin, BaseModel):
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"""Attack paths query definition.
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Describes a query that can be executed against the attack paths graph.
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"""
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model_config = ConfigDict(frozen=True)
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id: str = Field(description="Unique identifier for the query")
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name: str = Field(description="Human-readable name for the query")
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description: str = Field(description="Detailed description of what the query finds")
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provider: str = Field(description="Cloud provider type this query applies to")
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parameters: list[AttackPathQueryParameter] = Field(
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default_factory=list, description="Parameters required to execute the query"
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)
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@classmethod
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def from_api_response(cls, data: dict[str, Any]) -> "AttackPathQuery":
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"""Transform query data to model.
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Handles JSON:API format where fields are nested under 'attributes'.
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Args:
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data: Query data from API response (JSON:API format)
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Returns:
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AttackPathQuery instance
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"""
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# JSON:API format has attributes nested
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attributes = data.get("attributes", {})
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parameters = [
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AttackPathQueryParameter.from_api_response(p)
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for p in attributes.get("parameters", [])
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]
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return cls(
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id=data["id"],
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name=attributes["name"],
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description=attributes["description"],
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provider=attributes["provider"],
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parameters=parameters,
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)
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class AttackPathsGraphNode(MinimalSerializerMixin, BaseModel):
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"""A node in the attack paths graph.
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Represents a cloud resource, finding, or virtual node in the graph.
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"""
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model_config = ConfigDict(frozen=True)
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resource_id: str = Field(description="ID of the resource represented by this node")
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labels: list[str] = Field(
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description="Node labels (e.g., 'EC2Instance', 'S3Bucket', 'ProwlerFinding')"
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)
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properties: dict[str, Any] = Field(
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default_factory=dict, description="Node properties"
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)
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# Extracted security-relevant fields for easier access
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severity: str | None = Field(
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default=None, description="Severity level for ProwlerFinding nodes"
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)
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status: str | None = Field(
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default=None, description="Status for ProwlerFinding nodes (FAIL/PASS)"
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)
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status_extended: str | None = Field(
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default=None, description="Extended status for ProwlerFinding nodes"
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)
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@classmethod
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def from_api_response(cls, data: dict[str, Any]) -> "AttackPathsGraphNode":
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"""Transform node data to model.
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Args:
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data: Node data from API response
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Returns:
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AttackPathsGraphNode instance with extracted fields
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"""
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properties = data.get("properties", {})
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labels = data.get("labels", [])
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# Extract security-relevant fields from properties
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if "ProwlerFinding" in labels:
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severity = properties.get("severity", None)
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status = properties.get("status", None)
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status_extended = properties.get("status_extended", None)
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else:
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severity = None
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status = None
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status_extended = None
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return cls(
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resource_id=properties.get("id", ""),
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labels=labels,
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properties=properties,
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severity=severity,
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status=status,
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status_extended=status_extended,
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)
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class AttackPathsGraphRelationship(MinimalSerializerMixin, BaseModel):
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"""A relationship (edge) in the attack paths graph.
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Represents a connection between two nodes.
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"""
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model_config = ConfigDict(frozen=True)
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id: str = Field(description="Unique identifier for the relationship")
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label: str = Field(
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description="Relationship type (e.g., 'CAN_ACCESS', 'STS_ASSUMEROLE_ALLOW')"
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)
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source: str = Field(description="ID of the source node")
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target: str = Field(description="ID of the target node")
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@classmethod
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def from_api_response(cls, data: dict[str, Any]) -> "AttackPathsGraphRelationship":
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"""Transform relationship data to model.
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Args:
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data: Relationship data from API response
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Returns:
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AttackPathsGraphRelationship instance
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"""
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return cls(
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id=data["id"],
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label=data["label"],
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source=data["source"],
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target=data["target"],
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)
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class AttackPathQueryResult(MinimalSerializerMixin, BaseModel):
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"""Result of executing an attack paths query.
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Contains the graph data (nodes and relationships) plus a summary.
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"""
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model_config = ConfigDict(frozen=True)
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nodes: list[AttackPathsGraphNode] = Field(
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default_factory=list, description="Nodes in the attack path graph"
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)
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relationships: list[AttackPathsGraphRelationship] = Field(
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default_factory=list, description="Relationships connecting the nodes"
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)
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@classmethod
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def from_api_response(
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cls,
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response: dict[str, Any],
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) -> "AttackPathQueryResult":
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"""Transform API response to query result.
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Args:
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response: API response with nodes and relationships
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Returns:
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AttackPathQueryResult with parsed data and summary
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"""
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attributes = response.get("data", {}).get("attributes")
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nodes_data = attributes.get("nodes", [])
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relationships_data = attributes.get("relationships", [])
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nodes = [AttackPathsGraphNode.from_api_response(n) for n in nodes_data]
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relationships = [
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AttackPathsGraphRelationship.from_api_response(r)
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for r in relationships_data
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]
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return cls(
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nodes=nodes,
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relationships=relationships,
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)
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227
mcp_server/prowler_mcp_server/prowler_app/tools/attack_paths.py
Normal file
227
mcp_server/prowler_mcp_server/prowler_app/tools/attack_paths.py
Normal file
@@ -0,0 +1,227 @@
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"""Attack Paths tools for Prowler App MCP Server.
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This module provides tools for analyzing Attack Paths data from Neo4j graph database.
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Attack Paths help identify security risks by tracing potential attack vectors
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through cloud infrastructure relationships.
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"""
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from typing import Any, Literal
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from prowler_mcp_server.prowler_app.models.attack_paths import (
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AttackPathQuery,
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AttackPathQueryResult,
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AttackPathScansListResponse,
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)
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from prowler_mcp_server.prowler_app.tools.base import BaseTool
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from pydantic import Field
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class AttackPathsTools(BaseTool):
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"""Tools for Attack Paths analysis.
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Provides tools for:
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- prowler_app_list_attack_paths_scans: Find completed scans ready for analysis
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- prowler_app_list_attack_paths_queries: Discover available queries for a scan
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- prowler_app_run_attack_paths_query: Execute query and analyze attack paths
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"""
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async def list_attack_paths_scans(
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self,
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provider_id: list[str] = Field(
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default=[],
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description="Filter by Prowler's internal UUID(s) (v4) for specific provider(s). Use `prowler_app_search_providers` tool to find provider IDs",
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),
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provider_type: list[str] = Field(
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default=[],
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description="Filter by cloud provider type (aws, azure, gcp, etc.). Use `prowler_hub_list_providers` to see supported provider types",
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),
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state: list[
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Literal[
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"available",
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"scheduled",
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"executing",
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"completed",
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"failed",
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"cancelled",
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]
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] = Field(
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default=["completed"],
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description="Filter by scan execution state. Default: ['completed'] to show scans ready for analysis",
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),
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page_size: int = Field(
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default=50,
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description="Number of results to return per page",
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),
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page_number: int = Field(
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default=1,
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description="Page number to retrieve (1-indexed)",
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),
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) -> dict[str, Any]:
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"""List Attack Paths scans with filtering capabilities.
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Default behavior:
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- Returns COMPLETED scans (ready for attack paths analysis)
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- Returns 50 scans per page
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- Shows the latest scan per provider
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Each scan includes:
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- Core identification: id (UUID for get/query operations)
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- Execution context: state, progress
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- Provider info: provider_id, provider_alias, provider_type, provider_uid
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Workflow:
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1. Use this tool to find completed attack paths scans
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2. Use prowler_app_list_attack_paths_queries to see available queries for a scan
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3. Use prowler_app_run_attack_paths_query to execute analysis
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"""
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try:
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# Validate pagination
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self.api_client.validate_page_size(page_size)
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# Build query parameters
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params: dict[str, Any] = {
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"page[size]": page_size,
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"page[number]": page_number,
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}
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# Apply provider filters
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if provider_id:
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params["filter[provider__in]"] = provider_id
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if provider_type:
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params["filter[provider_type__in]"] = provider_type
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# Apply state filter
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if state:
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params["filter[state__in]"] = state
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clean_params = self.api_client.build_filter_params(params)
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api_response = await self.api_client.get(
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"/attack-paths-scans", params=clean_params
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)
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simplified_response = AttackPathScansListResponse.from_api_response(
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api_response
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)
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return simplified_response.model_dump()
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except Exception as e:
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self.logger.error(f"Failed to list attack paths scans: {e}")
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return {"error": f"Failed to list attack paths scans: {str(e)}"}
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async def list_attack_paths_queries(
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self,
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scan_id: str = Field(
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description="UUID of a COMPLETED attack paths scan. Use `prowler_app_list_attack_paths_scans` with state=['completed'] to find scan IDs"
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),
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) -> list[dict[str, Any]]:
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"""Discover available Attack Paths queries for a completed scan.
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IMPORTANT: The scan must be in 'completed' state to list queries.
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Queries are provider-specific
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Each query includes:
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- id: Query identifier to use with run_attack_paths_query
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- name: Human-readable name describing what the query finds
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- description: Detailed explanation of the security analysis
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- parameters: List of required parameters (if any)
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Example queries (AWS):
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- aws-internet-exposed-ec2-sensitive-s3-access: Find EC2 instances exposed to internet with access to sensitive S3 buckets
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- aws-iam-privesc-passrole-ec2: Detect privilege escalation via PassRole + EC2
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- aws-ec2-instances-internet-exposed: Find internet-exposed EC2 instances
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Workflow:
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1. Use prowler_app_list_attack_paths_scans to find a completed scan
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2. Use this tool to discover available queries
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3. Use prowler_app_run_attack_paths_query with query_id and any required parameters
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"""
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try:
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api_response = await self.api_client.get(
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f"/attack-paths-scans/{scan_id}/queries"
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)
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return [
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AttackPathQuery.from_api_response(query).model_dump()
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for query in api_response.get("data", [])
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]
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except Exception as e:
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self.logger.error(
|
||||
f"Failed to list attack paths queries for scan {scan_id}: {e}"
|
||||
)
|
||||
return [{"error": f"Failed to list attack paths queries: {str(e)}"}]
|
||||
|
||||
async def run_attack_paths_query(
|
||||
self,
|
||||
scan_id: str = Field(
|
||||
description="UUID of a COMPLETED attack paths scan. The scan must be in 'completed' state"
|
||||
),
|
||||
query_id: str = Field(
|
||||
description="Query ID to execute (e.g., 'aws-internet-exposed-ec2-sensitive-s3-access'). Use `prowler_app_list_attack_paths_queries` to discover available queries"
|
||||
),
|
||||
parameters: dict[str, str] = Field(
|
||||
default_factory=dict,
|
||||
description="Query parameters as key-value pairs. Check query definition for required parameters. Example: {'tag_key': 'DataClassification', 'tag_value': 'Sensitive'}",
|
||||
),
|
||||
) -> dict[str, Any]:
|
||||
"""Execute an Attack Paths query and analyze the results.
|
||||
|
||||
IMPORTANT: This is the PRIMARY tool for attack paths analysis.
|
||||
It executes a Cypher query against the Neo4j graph database and returns
|
||||
the attack path graph with security findings.
|
||||
|
||||
Prerequisites:
|
||||
- Scan must be in 'completed' state
|
||||
- query_id must be valid for the scan's provider type
|
||||
- All required parameters must be provided
|
||||
|
||||
Returns:
|
||||
- nodes: Cloud resources, findings, and virtual nodes in the attack path
|
||||
- relationships: Connections between nodes (CAN_ACCESS, STS_ASSUMEROLE_ALLOW, etc.)
|
||||
|
||||
Node types you may see:
|
||||
- EC2Instance, S3Bucket, RDSInstance, LoadBalancer, etc. (cloud resources)
|
||||
- ProwlerFinding (security issues with severity and status)
|
||||
- Internet (virtual node representing external access)
|
||||
- PrivilegeEscalation (virtual node for escalation outcomes)
|
||||
|
||||
Relationship types:
|
||||
- CAN_ACCESS: Network access path (often from Internet)
|
||||
- STS_ASSUMEROLE_ALLOW: IAM role assumption
|
||||
- MEMBER_OF_EC2_SECURITY_GROUP: Security group membership
|
||||
- And many more cloud-specific relationships
|
||||
|
||||
Workflow:
|
||||
1. Ensure scan is completed
|
||||
2. List available queries (use prowler_app_list_attack_paths_queries)
|
||||
3. Execute this tool with appropriate parameters
|
||||
4. Analyze the returned graph for security insights
|
||||
"""
|
||||
try:
|
||||
# Build the request payload following JSON:API format
|
||||
request_data: dict[str, Any] = {
|
||||
"data": {
|
||||
"type": "attack-paths-query-run-requests",
|
||||
"attributes": {
|
||||
"id": query_id,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
# Add parameters if provided
|
||||
if parameters:
|
||||
request_data["data"]["attributes"]["parameters"] = parameters
|
||||
|
||||
api_response = await self.api_client.post(
|
||||
f"/attack-paths-scans/{scan_id}/queries/run",
|
||||
json_data=request_data,
|
||||
)
|
||||
|
||||
# Parse the response
|
||||
query_result = AttackPathQueryResult.from_api_response(api_response)
|
||||
|
||||
return query_result.model_dump()
|
||||
except Exception as e:
|
||||
self.logger.error(
|
||||
f"Failed to run attack paths query '{query_id}' on scan {scan_id}: {e}"
|
||||
)
|
||||
return {"error": f"Failed to run attack paths query '{query_id}': {str(e)}"}
|
||||
224
mcp_server/uv.lock
generated
224
mcp_server/uv.lock
generated
@@ -184,6 +184,15 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/db/d3/9dcc0f5797f070ec8edf30fbadfb200e71d9db6b84d211e3b2085a7589a0/click-8.3.0-py3-none-any.whl", hash = "sha256:9b9f285302c6e3064f4330c05f05b81945b2a39544279343e6e7c5f27a9baddc", size = 107295, upload-time = "2025-09-18T17:32:22.42Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "cloudpickle"
|
||||
version = "3.1.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/27/fb/576f067976d320f5f0114a8d9fa1215425441bb35627b1993e5afd8111e5/cloudpickle-3.1.2.tar.gz", hash = "sha256:7fda9eb655c9c230dab534f1983763de5835249750e85fbcef43aaa30a9a2414", size = 22330, upload-time = "2025-11-03T09:25:26.604Z" }
|
||||
wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/88/39/799be3f2f0f38cc727ee3b4f1445fe6d5e4133064ec2e4115069418a5bb6/cloudpickle-3.1.2-py3-none-any.whl", hash = "sha256:9acb47f6afd73f60dc1df93bb801b472f05ff42fa6c84167d25cb206be1fbf4a", size = 22228, upload-time = "2025-11-03T09:25:25.534Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
version = "0.4.6"
|
||||
@@ -325,9 +334,27 @@ wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/36/f4/c6e662dade71f56cd2f3735141b265c3c79293c109549c1e6933b0651ffc/exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10", size = 16674, upload-time = "2025-05-10T17:42:49.33Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "fakeredis"
|
||||
version = "2.33.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "redis" },
|
||||
{ name = "sortedcontainers" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5f/f9/57464119936414d60697fcbd32f38909bb5688b616ae13de6e98384433e0/fakeredis-2.33.0.tar.gz", hash = "sha256:d7bc9a69d21df108a6451bbffee23b3eba432c21a654afc7ff2d295428ec5770", size = 175187, upload-time = "2025-12-16T19:45:52.269Z" }
|
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wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/6e/78/a850fed8aeef96d4a99043c90b818b2ed5419cd5b24a4049fd7cfb9f1471/fakeredis-2.33.0-py3-none-any.whl", hash = "sha256:de535f3f9ccde1c56672ab2fdd6a8efbc4f2619fc2f1acc87b8737177d71c965", size = 119605, upload-time = "2025-12-16T19:45:51.08Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
lua = [
|
||||
{ name = "lupa" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "fastmcp"
|
||||
version = "2.13.1"
|
||||
version = "2.14.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "authlib" },
|
||||
@@ -340,15 +367,16 @@ dependencies = [
|
||||
{ name = "platformdirs" },
|
||||
{ name = "py-key-value-aio", extra = ["disk", "keyring", "memory"] },
|
||||
{ name = "pydantic", extra = ["email"] },
|
||||
{ name = "pydocket" },
|
||||
{ name = "pyperclip" },
|
||||
{ name = "python-dotenv" },
|
||||
{ name = "rich" },
|
||||
{ name = "uvicorn" },
|
||||
{ name = "websockets" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d4/a3/c9eb28b5f0b979b0dd8aa9ba56e69298cdb2d72c15592165d042ccb20194/fastmcp-2.13.1.tar.gz", hash = "sha256:b9c664c51f1ff47c698225e7304267ae29a51913f681bd49e442b8682f9a5f90", size = 8170226, upload-time = "2025-11-15T19:02:17.693Z" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/35/50/9bb042a2d290ccadb35db3580ac507f192e1a39c489eb8faa167cd5e3b57/fastmcp-2.14.0.tar.gz", hash = "sha256:c1f487b36a3e4b043dbf3330e588830047df2e06f8ef0920d62dfb34d0905727", size = 8232562, upload-time = "2025-12-11T23:04:27.134Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9b/4b/7e36db0a90044be181319ff025be7cc57089ddb6ba8f3712dea543b9cf97/fastmcp-2.13.1-py3-none-any.whl", hash = "sha256:7a78b19785c4ec04a758d920c312769a497e3f6ab4c80feed504df1ed7de9f3c", size = 376750, upload-time = "2025-11-15T19:02:15.748Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/54/73/b5656172a6beb2eacec95f04403ddea1928e4b22066700fd14780f8f45d1/fastmcp-2.14.0-py3-none-any.whl", hash = "sha256:7b374c0bcaf1ef1ef46b9255ea84c607f354291eaf647ff56a47c69f5ec0c204", size = 398965, upload-time = "2025-12-11T23:04:25.587Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -406,6 +434,18 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442, upload-time = "2024-09-15T18:07:37.964Z" },
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||||
]
|
||||
|
||||
[[package]]
|
||||
name = "importlib-metadata"
|
||||
version = "8.7.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "zipp" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/f3/49/3b30cad09e7771a4982d9975a8cbf64f00d4a1ececb53297f1d9a7be1b10/importlib_metadata-8.7.1.tar.gz", hash = "sha256:49fef1ae6440c182052f407c8d34a68f72efc36db9ca90dc0113398f2fdde8bb", size = 57107, upload-time = "2025-12-21T10:00:19.278Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/fa/5e/f8e9a1d23b9c20a551a8a02ea3637b4642e22c2626e3a13a9a29cdea99eb/importlib_metadata-8.7.1-py3-none-any.whl", hash = "sha256:5a1f80bf1daa489495071efbb095d75a634cf28a8bc299581244063b53176151", size = 27865, upload-time = "2025-12-21T10:00:18.329Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jaraco-classes"
|
||||
version = "3.4.0"
|
||||
@@ -507,6 +547,58 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/81/db/e655086b7f3a705df045bf0933bdd9c2f79bb3c97bfef1384598bb79a217/keyring-25.7.0-py3-none-any.whl", hash = "sha256:be4a0b195f149690c166e850609a477c532ddbfbaed96a404d4e43f8d5e2689f", size = 39160, upload-time = "2025-11-16T16:26:08.402Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "lupa"
|
||||
version = "2.6"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/b8/1c/191c3e6ec6502e3dbe25a53e27f69a5daeac3e56de1f73c0138224171ead/lupa-2.6.tar.gz", hash = "sha256:9a770a6e89576be3447668d7ced312cd6fd41d3c13c2462c9dc2c2ab570e45d9", size = 7240282, upload-time = "2025-10-24T07:20:29.738Z" }
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||||
wheels = [
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{ url = "https://files.pythonhosted.org/packages/94/86/ce243390535c39d53ea17ccf0240815e6e457e413e40428a658ea4ee4b8d/lupa-2.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:47ce718817ef1cc0c40d87c3d5ae56a800d61af00fbc0fad1ca9be12df2f3b56", size = 951707, upload-time = "2025-10-24T07:18:03.884Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/86/85/cedea5e6cbeb54396fdcc55f6b741696f3f036d23cfaf986d50d680446da/lupa-2.6-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:7aba985b15b101495aa4b07112cdc08baa0c545390d560ad5cfde2e9e34f4d58", size = 1916703, upload-time = "2025-10-24T07:18:05.6Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/24/be/3d6b5f9a8588c01a4d88129284c726017b2089f3a3fd3ba8bd977292fea0/lupa-2.6-cp312-cp312-macosx_11_0_x86_64.whl", hash = "sha256:b766f62f95b2739f2248977d29b0722e589dcf4f0ccfa827ccbd29f0148bd2e5", size = 985152, upload-time = "2025-10-24T07:18:08.561Z" },
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{ url = "https://files.pythonhosted.org/packages/eb/23/9f9a05beee5d5dce9deca4cb07c91c40a90541fc0a8e09db4ee670da550f/lupa-2.6-cp312-cp312-manylinux2010_i686.manylinux_2_12_i686.manylinux_2_28_i686.whl", hash = "sha256:00a934c23331f94cb51760097ebfab14b005d55a6b30a2b480e3c53dd2fa290d", size = 1159599, upload-time = "2025-10-24T07:18:10.346Z" },
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{ url = "https://files.pythonhosted.org/packages/40/4e/e7c0583083db9d7f1fd023800a9767d8e4391e8330d56c2373d890ac971b/lupa-2.6-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:21de9f38bd475303e34a042b7081aabdf50bd9bafd36ce4faea2f90fd9f15c31", size = 1038686, upload-time = "2025-10-24T07:18:12.112Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/1c/9f/5a4f7d959d4feba5e203ff0c31889e74d1ca3153122be4a46dca7d92bf7c/lupa-2.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:cf3bda96d3fc41237e964a69c23647d50d4e28421111360274d4799832c560e9", size = 2071956, upload-time = "2025-10-24T07:18:14.572Z" },
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||||
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Reference in New Issue
Block a user