Facial recognition database built by untargeted scraping

Admit images to a face-recognition gallery or embedding index only through consented enrolment or a targeted, recorded lawful basis, never from crawlers or bulk CCTV.

Put the gate on the single write path into the face gallery or face-embedding index: each insert must reference an enrolment record (consented enrolment of that person, or a targeted request naming the subject with its recorded lawful basis), and the ingestion code refuses items without one. Web crawlers, image scrapers, bulk dataset downloads and CCTV archives are not wired to face encoding plus indexing; if CCTV frames are processed for another purpose, no face templates from them are stored in a reusable recognition database. Store the source and enrolment id with every template so the gallery can be audited.

Where it goes: 1 application source code, 2 data models, 6 API calls and integrations.

What reviewers look for: no pipeline from a web crawler, image scraper or cctv_feed to face_encodings or a face-embedding call followed by an index or gallery insert; every gallery row carries an enrolment or lawful-basis reference checked at insert time; scraped image datasets are not used to build or expand a recognition database.

for url in crawler.image_urls(seed_sites):
    img = face_recognition.load_image_file(download(url))
    for enc in face_recognition.face_encodings(img):
        face_index.add(enc, meta={'source': url})

def enroll(enrolment_id: str, image_path: str):
    rec = db.enrolments.get(enrolment_id)   # consented enrolment or targeted lawful basis
    if rec is None or rec.basis not in ('consented_enrolment', 'targeted_lawful_basis'):
        raise PermissionError('no enrolment record for this subject')
    encs = face_recognition.face_encodings(face_recognition.load_image_file(image_path))
    if len(encs) != 1:
        raise ValueError('expected exactly one face')
    face_index.add(encs[0], meta={'enrolment_id': rec.id, 'subject_id': rec.subject_id})
# the crawler no longer calls face_encodings or face_index.add

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.