Geminio

(★ 9)

[ICCV 2025] Geminio is a VLM-powered gradient inversion attack in federated learning (FL). It allows the adversary (the FL server) to describe the data of value and reconstruct the victim client's private data matching the description.

오너의 다른 레포

Imperio ★ 44

[IJCAI 2024] Imperio is an LLM-powered backdoor attack. It allows the adversary to issue language-guided instructions to control the victim model's prediction for arbitrary targets.

Python
Protego ★ 10

[CVPR 2026] Protego is a user-centric privacy protection method that safeguards facial images from retrieval-based privacy intrusions.

Jupyter Notebook
AnywhereDoor ★ 9

AnywhereDoor is a multi-target backdoor attack tailored for object detection. Once implanted, it enables adversaries to specify different attack types (object vanishing, fabrication, or misclassification) and configurations (untargeted or targeted with specific classes) to dynamically control detection behavior.

Jupyter Notebook
Confundo ★ 9

[SEC 2026] Confundo: Learning to Generate Robust Poison for Practical RAG Systems

Python

파일 탐색기

ZIP 다운로드
  • .gitignore
  • LICENSE
  • main_breaching-imagenet.py
  • main_geminio-imagenet.py
  • README.md
  • reconstruct.py
  • requirements.txt
  • test_pipeline_imagenet.sh
  • vlm-imagenet-embed.py

# CDN으로 사용하기

jsDelivr

jsDelivr는 공개 GitHub 리포지토리를 별도 설정 없이 CDN으로 즉시 서빙합니다. 버전과 파일을 고르면 웹페이지에 바로 붙일 수 있는 링크와 예시 코드가 만들어집니다.

링크
예시

명령어 용어집

이 문서에서 사용된 명령어를 모아봤습니다. 낯선 명령어가 있다면 펼쳐서 확인해보세요.

🔍

conda activate

설명 보기 ▼

Activate a conda environment.
See also: `conda deactivate`.

conda activate myenv

Activate an existing environment named `myenv`:

conda activate {{path/to/myenv}}

Activate an existing environment located at custom path:

conda activate --stack myenv

Stack `myenv` environment on top of a previous environment making libraries/commands/variables from both accessible:

🔍

conda create

설명 보기 ▼

Create new conda environments.

conda create {{[-y|--yes]}} {{[-n|--name]}} py39 python=3.9 "numpy>=1.11" scipy

Create a new environment named `py39`, install Python 3.9, NumPy v1.11 or above in it, and the latest stable version of SciPy. Say yes to all confirmations:

conda create {{[-n|--name]}} myenv --file {{file1.yml}} --file {{file2.yml}}

Create a new environment named `myenv` and install packages listed in files:

conda create {{[-p|--prefix]}} {{path/to/myenv}}

Create a new environment at a custom path (i.e. prefix):

🔍

pip install

설명 보기 ▼

Install Python packages.

pip install {{package1 package2 ...}}

Install one or more packages:

pip install {{package1 package2 ...}} {{[-U|--upgrade]}}

Upgrade all specified packages to the latest version, installing any that are not already present:

pip install {{package}}=={{version}}

Install a specific version of a package:

🔍

python

설명 보기 ▼

Python 언어 인터프리터.
더 많은 정보: <https://docs.python.org/using/cmdline.html>.

python

REPL(대화형 셸) 시작:

python {{path/to/file.py}}

특정 Python 파일 실행:

python -i {{path/to/file.py}}

특정 Python 파일 실행 후 REPL 시작:

# 프로젝트 배지

  • 설명 없음
// repository documentation