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PromptsMay 14, 2026·2 min de lectura
Anamorpher — Image-Scaling Prompt Injection Lab
trailofbits/anamorpher crafts image-scaling attacks for multimodal prompt injection; verified 1,049★ with a uv backend and browser frontend workflow.
Listo para agents
Instalación lista para agent
Este activo puede instalarse después de elegir el runtime, revisar el plan y ejecutar el comando correspondiente.
Native · 96/100Política: permitir
Superficie agent
Cualquier agent MCP/CLI
Confianza
Confianza: Established
Comando de instalación directa
npx -y tokrepo@latest install 76460f4b-70b2-5592-9107-1e2015123b56 --target codexEjecutar después de confirmar el plan con dry-run.
Introducción
trailofbits/anamorpher crafts image-scaling attacks for multimodal prompt injection; verified 1,049★ with a uv backend and browser frontend workflow.
Best for: Security teams testing multimodal models and apps for downscaling-triggered hidden instructions
Works with: Python 3.11+, uv (recommended), and a browser-opened HTML frontend for visualization
Setup time: 10-25 minutes
Key facts (verified)
- GitHub: 1049 stars · 91 forks · pushed 2026-05-11.
- License: Apache-2.0 · owner avatar + repo URL verified via GitHub API.
- README-backed entrypoint:
uv run python backend/app.py.
Main
Use it as an evaluation harness: craft a payload image, then test how different downscalers reveal (or hide) the prompt injection after resizing.
Compare implementations: README highlights OpenCV, PyTorch, TensorFlow, and Pillow for scaling behavior differences.
Treat results as probabilistic: README warns outcomes vary and recommends running each example ~5 times for consistent evaluation.
Source-backed notes
- README positions Anamorpher as a tool for crafting/visualizing image scaling attacks and provides both a frontend UI and Python API.
- README lists supported downscaling algorithms (bicubic, bilinear, nearest neighbor) and comparison backends (OpenCV/PyTorch/TensorFlow/Pillow).
- README setup uses
uv sync, runs the backend via uv run python backend/app.py, and opens frontend/index.html in a browser.
FAQ
- Is this for text-only LLMs?: No — README explicitly targets multi-modal AI systems where image downscaling can hide/reveal instructions.
- Do results always reproduce?: Not always — README warns outcomes can vary and suggests running examples multiple times.
- What’s a safe rollout?: Run it in a controlled eval environment and document the exact preprocessing pipeline (resize settings, libraries) you deploy.
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