Add missing security headers to next config#883
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❌ PR Rejected — Issue Assignment Check FailedHi @saurabhhhcodes! This PR has been closed because you are not assigned to the issue(s) it references:
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Caution Review failedThe pull request is closed. ℹ️ Recent review info⚙️ Run configurationConfiguration used: Path: .coderabbit.yaml Review profile: CHILL Plan: Pro Run ID: 📒 Files selected for processing (5)
WalkthroughThe PR adds multiple security headers to Next.js responses and validates video generation image URLs by inspecting fetched file signatures before the request proceeds to job creation. ChangesSecurity header configuration
Video image payload validation
Estimated code review effort: 3 (Moderate) | ~25 minutes Sequence Diagram(s)sequenceDiagram
participant Client
participant VideoGenerateRoute
participant validateVideoImageUrl
participant ImageURL
Client->>VideoGenerateRoute: POST imageUrl
VideoGenerateRoute->>validateVideoImageUrl: validate image URL
validateVideoImageUrl->>ImageURL: fetch image bytes
ImageURL-->>validateVideoImageUrl: response payload
validateVideoImageUrl-->>VideoGenerateRoute: validation result
VideoGenerateRoute-->>Client: 422 error or continue processing
Possibly related issues
Possibly related PRs
Suggested reviewers: ✨ Finishing Touches🧪 Generate unit tests (beta)
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| export async function validateVideoImageUrl(imageUrl: string): Promise<VideoImageValidationResult> { | ||
| try { | ||
| const response = await fetch(imageUrl, { cache: 'no-store' }); |
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Suggestion: This fetches a user-controlled URL directly from the server without any SSRF guardrails (no scheme restriction to HTTPS only, no private-network/localhost/IP blocking, no allowlist). An attacker can submit internal URLs and make the backend probe internal services/metadata endpoints. Add strict outbound URL validation (protocol + hostname/IP checks) before issuing the request. [ssrf]
Severity Level: Critical 🚨
❌ /api/video/generate can fetch attacker-chosen internal URLs.
❌ Backend may reach cloud metadata or admin services.
⚠️ Potential pivot to internal network reconnaissance.Steps of Reproduction ✅
1. Start the DoubtDesk Next.js app so that the API route handler in
`src/app/api/video/generate/route.ts:23-110` is active, exposing `POST
/api/video/generate`.
2. From a client, send `POST /api/video/generate` with JSON body `{ "content": null,
"imageUrl": "http://127.0.0.1:8080/internal-status" }`. The body is parsed and validated
by `parseAndValidateRequest` in `src/lib/validations/validate.ts:5-27` using
`generateVideoSchema` in `src/lib/validations/video.ts:4-7`, which applies `safeUrl` from
`src/lib/validations/common.ts:3-5` (only syntax + length checks, no SSRF filtering).
3. In `src/app/api/video/generate/route.ts:46-48`, the handler sees a non-null
`data.imageUrl` and calls `validateVideoImageUrl(data.imageUrl)`, passing the
attacker-controlled URL to `validateVideoImageUrl` implemented in
`src/lib/video/image-validation.ts:49-82`.
4. Inside `validateVideoImageUrl`, line `51 const response = await fetch(imageUrl, {
cache: 'no-store' });` issues a server-side `fetch` to
`http://127.0.0.1:8080/internal-status` (or any attacker-chosen internal/metadata
endpoint). There are no scheme, hostname, or private-network restrictions, so the backend
will attempt to reach internal services, demonstrating an SSRF capability even though only
a validation result (not the full response body) is returned to the client.
(Use Cmd/Ctrl + Click for best experience)
Prompt for AI Agent 🤖
This is a comment left during a code review.
**Path:** src/lib/video/image-validation.ts
**Line:** 51:51
**Comment:**
*Ssrf: This fetches a user-controlled URL directly from the server without any SSRF guardrails (no scheme restriction to HTTPS only, no private-network/localhost/IP blocking, no allowlist). An attacker can submit internal URLs and make the backend probe internal services/metadata endpoints. Add strict outbound URL validation (protocol + hostname/IP checks) before issuing the request.
Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise.
Once fix is implemented, also check other comments on the same PR, and ask user if the user wants to fix the rest of the comments as well. if said yes, then fetch all the comments validate the correctness and implement a minimal fix| }; | ||
| } | ||
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| const bytes = new Uint8Array(await response.arrayBuffer()); |
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Suggestion: This reads the entire remote response into memory with no size cap, so a large payload can cause excessive memory usage or process instability before validation completes. Enforce a strict maximum download size (via Content-Length checks plus streamed byte limits) and reject oversized payloads early. [performance]
Severity Level: Major ⚠️
❌ Large remote images can OOM Next.js video API.
⚠️ Video generation requests can stall under resource exhaustion.
⚠️ Resource spikes may degrade other API endpoints.Steps of Reproduction ✅
1. Run the DoubtDesk Next.js backend so that the video generation API handler in
`src/app/api/video/generate/route.ts:23-110` is exposed as `POST /api/video/generate`.
2. Host a very large file (e.g., >500MB) at an attacker-controlled URL such as
`https://attacker.example/huge.bin`, and send `POST /api/video/generate` with body `{
"content": null, "imageUrl": "https://attacker.example/huge.bin" }`. The request body is
accepted by `parseAndValidateRequest` (`src/lib/validations/validate.ts:5-27`) and
`generateVideoSchema` (`src/lib/validations/video.ts:4-7`) as long as the URL is
syntactically valid.
3. In `src/app/api/video/generate/route.ts:46-48`, the handler calls
`validateVideoImageUrl(data.imageUrl)`. Inside `validateVideoImageUrl`
(`src/lib/video/image-validation.ts:49-82`), line `51 const response = await
fetch(imageUrl, { cache: 'no-store' });` starts downloading the large file from the remote
server.
4. At `src/lib/video/image-validation.ts:61`, `const bytes = new Uint8Array(await
response.arrayBuffer());` reads the entire response body into an `ArrayBuffer` with no
`Content-Length` check and no byte-size cap, unlike the explicit `AI_IMAGE_MAX_BYTES`
limit enforced in `src/lib/ai/ai-image-validation.ts:1-3,102-110`. For very large
payloads, this can cause excessive memory usage or process instability (OOM or severe GC
thrashing) in the Next.js server handling `/api/video/generate`.
(Use Cmd/Ctrl + Click for best experience)
Prompt for AI Agent 🤖
This is a comment left during a code review.
**Path:** src/lib/video/image-validation.ts
**Line:** 61:61
**Comment:**
*Performance: This reads the entire remote response into memory with no size cap, so a large payload can cause excessive memory usage or process instability before validation completes. Enforce a strict maximum download size (via `Content-Length` checks plus streamed byte limits) and reject oversized payloads early.
Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise.
Once fix is implemented, also check other comments on the same PR, and ask user if the user wants to fix the rest of the comments as well. if said yes, then fetch all the comments validate the correctness and implement a minimal fix
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User description
Closes #874\n\nAdds the security headers called out in the issue to the global Next.js headers config: CSP, nosniff, referrer policy, permissions policy, and HSTS in production.\n\nValidation:\n- git diff --check\n- node --check next.config.mjs
CodeAnt-AI Description
Add security headers and reject invalid video image uploads
What Changed
Impact
✅ Safer page loading✅ Fewer failed video jobs from bad image uploads✅ Clearer upload errors💡 Usage Guide
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Summary by CodeRabbit
New Features
Bug Fixes