split-layout-technical
Warn
Audited by Gen Agent Trust Hub on Oct 29, 2026
Risk Level: MEDIUMOBFUSCATIONDYNAMIC_EXECUTIONEXTERNAL_DOWNLOADSINDIRECT_PROMPT_INJECTIONMETADATA_POISONING
Full Analysis
- [OBFUSCATION]: The demo implementation in
demo/index.htmlstores its primary source code as an encoded string. - Evidence: The
encodedHtmlconstant contains a large Base64-encoded string representing the complete HTML, CSS, and JavaScript of the design demo. - [DYNAMIC_EXECUTION]: The skill's demo environment dynamically decodes and executes content at runtime.
- Evidence: The script in
demo/index.htmlusesatobandTextDecoderto process the encoded HTML and injects it into aniframevia thesrcdocproperty. - [EXTERNAL_DOWNLOADS]: The demo fetches runtime libraries and assets from well-known external services and cloud providers.
- Evidence:
demo/source.jsonand the decoded HTML reveal dependencies on Cloudflare's CDN (GSAP, ScrollTrigger), Google Fonts, Fontshare, and asset storage on Supabase. - [INDIRECT_PROMPT_INJECTION]: The skill is designed to process external brand data and content, creating an attack surface for embedded instructions.
- Ingestion points: The
remix promptindemo/PROMPT.mdinstructs the agent to ingest external brand, subject, and copy details. - Boundary markers: No explicit instruction delimiters or sanitization warnings are present to isolate user-supplied content from the skill's logic.
- Capability inventory: While primarily a design tool, it specifically targets "login sections" and authentication flows, which could be exploited for phishing if malicious inputs are processed.
- Sanitization: There is no evidence of input validation or content filtering.
- [METADATA_POISONING]: The skill uses simulated social proof and ranking data within its prompts to establish authority.
- Evidence:
demo/PROMPT.mdanddemo/source.jsoninclude specific view counts, favorite counts, and ranking positions (#1) designed to make the skill appear highly popular and verified.
Audit Metadata