Evasion And Preprocessing

Organization

VectorSpaceLab

evasion-and-preprocessing

Use ART evasion attacks, preprocessing defences, and adversarial training recipes for image/tabular robustness workflows.

Overview

Publisher	VectorSpaceLab
Repository	`AREX-Skill`
Skill name	`evasion-and-preprocessing`
Stars	341
Forks	26
Bundled files	5
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Evasion And Preprocessing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/adversarial-robustness-toolbox/sub-skills/evasion-and-preprocessing
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/adversarial-robustness-toolbox/sub-skills/evasion-and-preprocessing

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/skills/repositories/repo-skills/adversarial-robustness-toolbox/sub-skills/evasion-and-preprocessing .claude/skills/evasion-and-preprocessing

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evasion And Preprocessing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evasion And Preprocessing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evasion And Preprocessing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Evasion and preprocessing

Use this sub-skill when the task is to generate evasion adversarial examples, select a white-box/black-box/physical image attack, add preprocessing defences, or plan adversarial training with ART estimators.

Route here

Craft FGSM/FGM, PGD/BIM/MIM/AutoPGD/AutoAttack, Carlini, DeepFool, ElasticNet, JSMA, universal perturbation, virtual adversarial, HopSkipJump, Boundary, ZOO, SimBA, Square, Pixel/Threshold, SignOPT, DecisionTree, spatial, feature-adversary, or image-patch attacks.
Add image/tabular preprocessing defences such as standardisation, spatial smoothing, feature squeezing, JPEG compression, Gaussian augmentation, label smoothing, Mixup, CutMix, Cutout, thermometer encoding, total variation minimization, or PixelDefend.
Plan adversarial training with AdversarialTrainer, AdversarialTrainerMadryPGD, or TRADES-style trainers.

Route away

Model wrapping, clip_values, input_shape, backend device setup, and estimator construction details belong to ../estimators-and-models/ or ../setup-and-backends/.
Poisoning, backdoors, membership/attribute inference, model inversion, or model extraction belong to ../poisoning-inference-extraction/.
Robustness metrics, certification, tree verification, security curves, and gradient checks after attack generation belong to ../evaluation-and-certification/.
Speech, object-detection-heavy, malware, and audio-heavy evasion workflows are outside this selected runtime scope unless a future refresh adds their required backends. Recognize their ART class names, but do not promise runnable coverage here.

Operating sequence

Confirm the estimator capability: loss gradients for PGD/FGM/BIM/MIM/AutoPGD, class gradients for Carlini/DeepFool/JSMA-style attacks, prediction-only classifiers for hard-label black-box attacks, or neural-network/image-specific support for patch/spatial attacks.
Match all perturbation budgets to the estimator input scale and clip_values; for normalized [0, 1] images use budgets such as 8/255, not 8.
Check shape conventions before running an attack: PyTorch image estimators usually use channels_first=True and NCHW; many NumPy image preprocessors default to channels_first=False and NHWC.
For targeted attacks, pass target labels as y to generate; use one-hot labels unless the wrapped estimator workflow explicitly uses class-index labels.
Add preprocessing defences either directly as callable preprocessors or through estimator preprocessing_defences; do not treat preprocessing alone as proof of robustness.
For adversarial training, start from a bounded PGD/FGM attack, verify labels and clipping, then choose generic, Madry PGD, or TRADES training according to the estimator backend.

References

Attack family/API chooser: references/attack-api-reference.md
Preprocessing and adversarial training recipes: references/preprocessing-and-training.md
Evasion/preprocessing troubleshooting: references/troubleshooting.md

Bundled checks

Tiny CPU PyTorch PGD/FGM smoke: scripts/smoke_evasion_pytorch.py
Tiny NumPy standardisation/spatial smoothing smoke: scripts/smoke_preprocessor_numpy.py

Run bundled scripts with --help first; they use synthetic data and do not download datasets.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Evasion And Preprocessing AI skill do?

Use ART evasion attacks, preprocessing defences, and adversarial training recipes for image/tabular robustness workflows.

Why use Evasion And Preprocessing on TypingMind?

Because you install it once and use it with any model. Evasion And Preprocessing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evasion And Preprocessing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/adversarial-robustness-toolbox/sub-skills/evasion-and-preprocessing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evasion And Preprocessing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evasion And Preprocessing?

As many as you like. As long as a model supports skills, you can use Evasion And Preprocessing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evasion And Preprocessing AI skill free?

Yes. It is published on GitHub by VectorSpaceLab under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Weights And Biases

NousResearch

OrganizationPopular

W&B: log ML experiments, sweeps, model registry, dashboards.

Faiss

Fast vector similarity search at billion scale.

Serving Llms Vllm

vLLM: high-throughput LLM serving, OpenAI API, quantization.

Huggingface Hub

HuggingFace hf CLI: search/download/upload models, datasets.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Evasion and preprocessing

Route here

Route away

Operating sequence

References

Bundled checks

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now