feat(cra): hardware path — derive cyber findings from networked components

For hardware CE projects (no repo) each networked component (controller/hmi/
gateway/drive/remote_access/sensor) yields typical ICS vulnerability CLASSES
(real CWE + "CISA-ICS — product-specific check" framing, NO fabricated CVEs);
they flow through the same CRA engine. /assess accepts components[]. MappedFinding
now echoes title/location/cwe so the response is self-contained for any finding
source. Live CISA-ICS/NVD per-product CVE lookup is the later enrichment.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-06-14 12:37:22 +02:00
parent 398eaf3c36
commit 437c2c8fa1
4 changed files with 115 additions and 3 deletions
@@ -17,6 +17,7 @@ from pydantic import BaseModel
from compliance.services.cra_finding_mapper import assess_findings_payload
from compliance.services.cra_snapshot_store import save_snapshot, list_snapshots, get_snapshot
from compliance.services.cra_use_case_controls import enrich_findings_with_breadth
from compliance.services.cra_component_findings import findings_from_components
from database import SessionLocal
from .tenant_utils import get_tenant_id
@@ -44,18 +45,31 @@ class SafetyFunctionIn(BaseModel):
vulnerable_to: Optional[List[str]] = None
class ComponentIn(BaseModel):
name: str
component_class: Optional[str] = "" # controller | hmi | gateway | drive | remote_access | sensor
networked: Optional[bool] = False
vendor: Optional[str] = ""
product: Optional[str] = ""
class AssessRequest(BaseModel):
findings: List[FindingIn]
findings: List[FindingIn] = []
# customer priorities for the discretionary tier: {objective: high|medium|low}.
# objectives: access | data | network_api | supply_updates | monitoring.
weights: Optional[Dict[str, str]] = None
# CE-risk-assessment safety functions for the cyber-meets-safety bridge.
safety_functions: Optional[List[SafetyFunctionIn]] = None
# hardware path: networked components -> derived cyber findings (no repo).
components: Optional[List[ComponentIn]] = None
def _payload(body: AssessRequest) -> dict:
findings = [f.model_dump() for f in body.findings]
if body.components:
findings = findings + findings_from_components([c.model_dump() for c in body.components])
return {
"findings": [f.model_dump() for f in body.findings],
"findings": findings,
"weights": body.weights,
"safety_functions": [s.model_dump() for s in body.safety_functions] if body.safety_functions else None,
}