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Neural Defend

Image Screening Integration Recipe

Build image screening as an evidence workflow, not a binary authenticity switch. Confirm upload authority, accept only documented image inputs, submit one face image through an official client or POST /detect/image, and branch on status. Use risk_level only after success. Ask for a corrected image after a rejection, route medium and high results to review according to your policy, and preserve the transaction identifier and decision context.

Maintained byNeural Defend
Updated August 7, 2026
Siva Shankar, Co-founder and CTO of Neural Defend.
Siva ShankarCo-founder & CTO
An article-specific diagram for Image Screening Integration Recipe organizes key sections including 1. authorize and validate intake, 2. analyze through one contract, 3. decide and record.

1. Authorize and validate intake

Tell the uploader what analysis will occur and confirm that the organization is authorized to send the image. Apply your privacy notice and retention policy before collection, not after the response.

Check the documented extension, size, minimum dimensions, and single-face expectation. Client-side checks improve recovery but do not replace server validation.

2. Analyze through one contract

Use detect_image or detectImage when an official SDK fits the runtime. Otherwise send a multipart file to /detect/image with x-api-key. Do not hand-build a multipart boundary when the HTTP library can create it safely.

Keep one retry owner. The SDK may already retry selected rate-limit and server failures. Treat timeout and network interruption as ambiguous before attempting another potentially billable transaction.

An article-specific topic map for Image Screening Integration Recipe organizes key sections including 2. analyze through one contract, 3. decide and record, 1. authorize and validate intake.

3. Decide and record

On success, evaluate risk_level under a documented policy. Low remains non-definitive, medium calls for additional evidence, and high calls for human review rather than automatic rejection from this signal alone.

On rejected, show a specific recovery action without implying authenticity. On error or unknown, withhold a risk decision. Store unique_trx_id, status, billable state, risk band when present, policy version, and review outcome while minimizing filenames and raw payloads.

Evidence boundary

Limitations

  • This recipe does not define a legal basis for processing, a universal risk threshold, or approval to use face analysis for identity documents.

Source record

Sources and references

  1. Neural DefendUnified Face Authenticity ScoreVerified August 7, 2026.
  2. Neural DefendUnified Image Face AuthenticityVerified August 7, 2026.

Verify the contract

Review every image result state

Confirm success, face-policy rejection, validation failure, service error, and nullable score handling.

Read the results guide