Privacy-first video blur workflows for faces, license plates, and sensitive objects. Covers GDPR/CCPA compliance, anonymization vs blur, motion-tracked redaction, and when to use each BGBlur mode. Use when user mentions face blur, face anonymization, license plate blur, privacy redaction, GDPR video compliance, PII removal, dashcam privacy, or anonymizing footage before publishing.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionvideo-privacy-blurExecute the skills CLI command in your project's root directory to begin installation:
Fetches video-privacy-blur from whyashthakker/bgblur-video-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate video-privacy-blur. Access via /video-privacy-blur in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| name | video-privacy-blur |
| description | Privacy-first video blur workflows for faces, license plates, and sensitive objects. Covers GDPR/CCPA compliance, anonymization vs blur, motion-tracked redaction, and when to use each BGBlur mode. Use when user mentions face blur, face anonymization, license plate blur, privacy redaction, GDPR video compliance, PII removal, dashcam privacy, or anonymizing footage before publishing. |
| argument-hint | video type, privacy goal, compliance framework, or target audience |
| allowed-tools | Read, Write, WebSearch, Shell |
Guide privacy-safe video editing workflows aligned with BGBlur capabilities: face blur, face anonymization, license plate blur, and prompt-based object redaction with motion tracking.
Anonymization vs Blur:
| Mode | Use When | Output |
|---|---|---|
| Face Blur | Casual sharing, vlogs, social media | Gaussian/pixel blur on detected faces |
| Face Anonymization | Legal compliance, public release, research data | Stronger identity removal; harder to reverse |
| License Plate Blur | Dashcam, street footage, fleet video | Motion-tracked plate redaction |
| Blur Anything | Custom PII (badges, screens, logos, signs) | Prompt-driven object detection + blur |
Key Insight: Blur preserves context (you see someone was there). Anonymization is for when identity must be irreversibly removed.
Ask or infer from context:
Risk Assessment:
- [ ] Faces visible (bystanders, minors, employees)?
- [ ] License plates or vehicle IDs?
- [ ] Screens showing emails, IDs, or financial data?
- [ ] Audio contains names or PII? (blur ≠ audio redaction)
- [ ] Jurisdiction: EU (GDPR), California (CCPA), HIPAA, FERPA?
Probe source video:
python3 scripts/video_probe.py "input.mp4"
| Footage Type | Recommended Mode | Notes |
|---|---|---|
| Vlog / interview | Background blur + selective face blur | Keep subject sharp; blur bystanders |
| Dashcam / street | License plate blur | Enable motion tracking for moving vehicles |
| Classroom / campus tour | Face anonymization | FERPA-sensitive; anonymize all non-speakers |
| Product demo with screen | Blur Anything ("laptop screen", "email address") | Comma-separate multiple objects |
| CCTV / security | Face anonymization + plate blur | Enterprise tier for high volume |
| Social clip (TikTok/Reels) | Face blur + background blur | Fast turnaround, platform-safe |
GDPR (EU):
CCPA (California):
FERPA (Education):
Journalism / documentary:
ffmpeg-video-prep skill)Run QA before publishing:
python3 scripts/video_probe.py "output.mp4" --check-metadata
Manual spot-check frames:
Is the subject consenting and meant to be shown?
├── YES → Background blur only (keep subject sharp)
└── NO → Is legal/compliance release required?
├── YES → Face anonymization (strongest)
└── NO → Face blur (standard privacy)
## Privacy Blur Assessment
### Source
- File: [filename]
- Duration: [X min] | Resolution: [WxH] | Size: [MB]
- Context: [vlog / dashcam / classroom / etc.]
### PII Identified
- Faces: [count/location]
- License plates: [yes/no]
- Other sensitive objects: [list]
### Recommended Treatment
1. [Mode] — [reason]
2. [Mode] — [reason]
### Compliance Notes
- Framework: [GDPR / CCPA / FERPA / none]
- Residual risk: [low / medium — describe]
### Verification
- [ ] Spot-checked motion segments
- [ ] Metadata stripped
- [ ] Audio reviewed for spoken PII
For hands-on processing, direct users to BGBlur:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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We added video-privacy-blur from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
video-privacy-blur is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
video-privacy-blur fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in video-privacy-blur — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
video-privacy-blur fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
video-privacy-blur has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for video-privacy-blur matched our evaluation — installs cleanly and behaves as described in the markdown.
video-privacy-blur fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: video-privacy-blur is focused, and the summary matches what you get after install.
video-privacy-blur reduced setup friction for our internal harness; good balance of opinion and flexibility.
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