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The unit of exposure is now a service — (ip, port) — not a bare open port. Pipeline (EXPANSION): L0 produce hosts, L1 cdn_check + passive_ports, L2 port_scan, L3 http_probe, L4 screenshot/waf_detect/service_fingerprint. - cdn_check applies to every target type and records cdn_type, so a domain scan finally knows which addresses are CDN-fronted. cdn/waf is an edge you do not own (edge ports only); cloud is your own machine (scanned in full). - port_scan decides and records a per-address scan_policy (full/web/skip) honouring the scan context's excluded_ips, and offers port profiles, exclusions, scan type, a tarpit threshold and an address budget. - passive_ports reads Shodan internetdb through naabu -passive: keyless, touches_target=False, so a passive-intensity scan still gets exposure data. - http_probe seeds its host x port matrix from open ports and folds every live response back onto the port (is_http, tls, product). - service_fingerprint names the software behind non-web ports with a pure Python banner prober (tools/banner/), including a SOCKS5 CONNECT so it honours the context proxy. naabu -sV is unimplemented. - shared/definitions/ports.py is the one vocabulary; ip_inventory and port_inventory are the only writers of ip_addresses/ports. - open_ports_found is measured from the table (DERIVED_COUNTS): four stages write ports, so summing stage results double-counted. - naabu failures no longer report zero open ports as success. Surfaces: a Services tab (SERVICE_QUERY grammar, 16 fields, 18 counted leads, 9 group dimensions, detail sheet) built on the shared results shell, and an outlier-first Exposure panel on the Overview. Every count is a promise — leads, groups and panel pivots were verified to equal the row count they land on. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01BnC2xMMzV6WQnpDp5zcXoU
164 lines
5.0 KiB
Python
164 lines
5.0 KiB
Python
import uuid
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from datetime import datetime
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from pydantic import BaseModel
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from pydantic import Field as PydanticField
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from sqlalchemy import Column
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from sqlalchemy.types import JSON, Text
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from sqlmodel import Field, SQLModel
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from shared.models.scan_context import ScanContextCreate
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from shared.utils.datetime import utc_now
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class ScanEngine(SQLModel, table=True):
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__tablename__ = "scan_engines"
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id: uuid.UUID = Field(default_factory=uuid.uuid4, primary_key=True, index=True)
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project_id: uuid.UUID = Field(foreign_key="projects.id", index=True)
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created_by: uuid.UUID = Field(foreign_key="users.id")
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name: str = Field(max_length=200)
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description: str | None = Field(default=None, max_length=1000)
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intensity: str = Field(default="normal")
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global_threads: int = Field(default=30)
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global_http_crawl: bool = Field(default=True)
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global_headers: list = Field(
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default_factory=list, sa_column=Column(JSON, nullable=False)
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)
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stages: dict = Field(default_factory=dict, sa_column=Column(JSON, nullable=False))
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yaml_source: str | None = Field(default=None, sa_column=Column(Text, nullable=True))
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tool_options: dict = Field(
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default_factory=dict, sa_column=Column(JSON, nullable=False)
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)
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created_at: datetime = Field(default_factory=utc_now)
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updated_at: datetime = Field(default_factory=utc_now)
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last_used_at: datetime | None = Field(default=None)
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class ScanEngineCreate(BaseModel):
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name: str
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description: str | None = None
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intensity: str = "normal"
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global_threads: int = 30
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global_http_crawl: bool = True
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global_headers: list[str] = PydanticField(default_factory=list)
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stages: dict[str, dict] = PydanticField(default_factory=dict)
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yaml_source: str | None = None
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tool_options: dict[str, str] = PydanticField(default_factory=dict)
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class ScanEngineUpdate(BaseModel):
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name: str | None = None
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description: str | None = None
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intensity: str | None = None
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global_threads: int | None = None
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global_http_crawl: bool | None = None
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global_headers: list[str] | None = None
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stages: dict[str, dict] | None = None
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yaml_source: str | None = None
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tool_options: dict[str, str] | None = None
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class EngineUsage(BaseModel):
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schedules: int = 0
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scans: int = 0
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class ScanEngineRead(BaseModel):
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id: uuid.UUID
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project_id: uuid.UUID
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created_by: uuid.UUID
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name: str
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description: str | None
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intensity: str
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global_threads: int
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global_http_crawl: bool
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global_headers: list[str]
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stages: dict[str, dict]
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yaml_source: str | None
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tool_options: dict[str, str] = PydanticField(default_factory=dict)
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usage: EngineUsage = PydanticField(default_factory=EngineUsage)
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created_at: datetime
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updated_at: datetime
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last_used_at: datetime | None
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class StageField(BaseModel):
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name: str
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title: str
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description: str | None = None
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type: str
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default: object = None
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options: list[str] | None = None
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option_labels: dict[str, str] | None = None
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minimum: int | None = None
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maximum: int | None = None
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scale: str | None = None
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class StageCatalogEntry(BaseModel):
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name: str
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title: str
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description: str
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phase: str
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level: int
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applies_to: list[str]
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tools: list[str]
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api_keys: list[str]
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requires_api_keys: bool = False
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touches_target: bool = True
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defaults: dict
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fields: list[StageField] = PydanticField(default_factory=list)
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class ToolOption(BaseModel):
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name: str
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label: str
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phase: str
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example: str
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class EnginePreset(BaseModel):
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name: str
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title: str
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description: str
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stages: dict[str, dict]
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class EngineCatalog(BaseModel):
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phases: list[str]
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stages: list[StageCatalogEntry]
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rate_tools: list[str]
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tool_options: list[ToolOption]
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presets: list[EnginePreset]
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target_types: list[str]
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class PreviewResolved(BaseModel):
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header_names: list[str] = PydanticField(default_factory=list)
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global_threads: int = 30
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global_rate_limit_ceiling: int | None = None
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per_tool_rate_limits: dict[str, int] = PydanticField(default_factory=dict)
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excluded_subdomains: list[str] = PydanticField(default_factory=list)
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excluded_paths: list[str] = PydanticField(default_factory=list)
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excluded_ips: list[str] = PydanticField(default_factory=list)
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included_subdomains: list[str] = PydanticField(default_factory=list)
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follow_redirects: bool | None = None
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http_protocol: str = "both"
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class EnginePreviewResult(BaseModel):
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phases: list = PydanticField(default_factory=list)
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resolved_stages: dict[str, dict] = PydanticField(default_factory=dict)
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resolved: PreviewResolved = PydanticField(default_factory=PreviewResolved)
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warnings: list[str] = PydanticField(default_factory=list)
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class EnginePreviewRequest(BaseModel):
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target_type: str
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context_id: uuid.UUID | None = None
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context: ScanContextCreate | None = None
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intensity: str = "normal"
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global_threads: int = 30
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stages: dict[str, dict] = PydanticField(default_factory=dict)
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