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Yogesh OjhaandClaude Opus 5
2375f1f1e4
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
91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
from shared.definitions.tools import SCAN_TOOLS
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from shared.enums.target import TargetType
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from shared.models.scan_engine import (
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EngineCatalog,
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EnginePreset,
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StageCatalogEntry,
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StageField,
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ToolOption,
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)
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from stages.presets import PRESETS, preset_stages
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from stages.registry import phases, rate_tools, stages
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def _resolve(prop: dict, defs: dict) -> dict:
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"""Flatten a $ref/allOf property (an enum field) onto its definition."""
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ref = prop.get("$ref") or next(
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(m.get("$ref") for m in prop.get("allOf") or [] if isinstance(m, dict)), None
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)
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if not ref or not ref.startswith("#/$defs/"):
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return prop
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target = defs.get(ref.rsplit("/", 1)[-1])
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return {**target, **prop} if isinstance(target, dict) else prop
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def _field_specs(spec) -> list[StageField]:
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schema = spec.schema
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defs = schema.get("$defs") or {}
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defaults = spec.defaults
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out: list[StageField] = []
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for name, raw in (schema.get("properties") or {}).items():
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prop = _resolve(raw, defs)
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options = prop.get("enum") or prop.get("options")
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out.append(
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StageField(
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name=name,
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title=prop.get("title") or name.replace("_", " ").capitalize(),
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description=prop.get("description") or None,
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type=_JSON_TYPES.get(prop.get("type"), prop.get("type") or "string"),
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default=defaults.get(name, prop.get("default")),
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options=list(options) if options else None,
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option_labels=prop.get("option_labels") or None,
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minimum=prop.get("minimum"),
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maximum=prop.get("maximum"),
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scale=prop.get("scale"),
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)
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)
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return out
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def build_catalog() -> EngineCatalog:
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return EngineCatalog(
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phases=[phase for phase, _ in phases()],
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stages=[
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StageCatalogEntry(
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name=spec.name,
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title=spec.title,
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description=spec.description,
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phase=spec.phase,
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level=spec.level,
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applies_to=sorted(spec.applies_to),
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tools=list(spec.tools),
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api_keys=list(spec.api_keys),
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requires_api_keys=spec.requires_api_keys,
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touches_target=spec.touches_target,
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defaults=spec.defaults,
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fields=_field_specs(spec),
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)
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for spec in stages()
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],
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rate_tools=list(rate_tools()),
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tool_options=[ToolOption(**t.model_dump()) for t in SCAN_TOOLS],
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presets=[
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EnginePreset(
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name=p.name,
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title=p.title,
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description=p.description,
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stages=preset_stages(p.name),
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)
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for p in PRESETS
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],
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target_types=[t.value for t in TargetType],
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)
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_JSON_TYPES = {
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"integer": "integer",
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"number": "number",
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"boolean": "boolean",
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"string": "string",
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}
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