REPOGEO REPORT · LITE
cleverhans-lab/cleverhans
Default branch master · commit 574efc1d · scanned 5/14/2026, 12:12:40 AM
GitHub: 6,433 stars · 1,400 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface cleverhans-lab/cleverhans, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Emphasize multi-framework benchmarking in README's first sentence
Why:
CURRENTThis repository contains the source code for CleverHans, a Python library to benchmark machine learning systems' vulnerability to adversarial examples.
COPY-PASTE FIXCleverHans is a Python library for benchmarking machine learning systems' vulnerability to adversarial examples across JAX, PyTorch, and TensorFlow 2.
- mediumtopics#2Add specific adversarial ML and framework topics
Why:
CURRENT["benchmarking", "machine-learning", "security"]
COPY-PASTE FIX["benchmarking", "machine-learning", "security", "adversarial-machine-learning", "adversarial-robustness", "jax", "pytorch", "tensorflow"]
- lowreadme#3Add a 'Why CleverHans?' or 'Comparison' section to the README
Why:
COPY-PASTE FIX## Why CleverHans? CleverHans stands out as one of the earliest and most influential open-source libraries for adversarial machine learning, initially developed by Google Brain. It provides a standardized framework for implementing, evaluating, and comparing adversarial attacks and defenses across JAX, PyTorch, and TensorFlow 2.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Foolbox · recommended 2×
- IBM Adversarial Robustness Toolbox (ART) · recommended 1×
- Microsoft Counterfit · recommended 1×
- Adversarial-ML-Threats (MITRE ATT&CK for ML) · recommended 1×
- Advertorch · recommended 1×
- CATEGORY QUERYHow can I assess the security of my machine learning models against adversarial inputs?you: #2AI recommended (in order):
- IBM Adversarial Robustness Toolbox (ART)
- CleverHans ← you
- Foolbox
- Microsoft Counterfit
- Adversarial-ML-Threats (MITRE ATT&CK for ML)
Show full AI answer
- CATEGORY QUERYNeed a library to benchmark adversarial robustness across JAX, PyTorch, and TensorFlow models.you: #4AI recommended (in order):
- Advertorch
- Foolbox
- ART (Adversarial Robustness Toolbox)
- CleverHans ← you
- Torchattacks
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of cleverhans-lab/cleverhans?passAI named cleverhans-lab/cleverhans explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts cleverhans-lab/cleverhans in production, what risks or prerequisites should they evaluate first?passAI named cleverhans-lab/cleverhans explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo cleverhans-lab/cleverhans solve, and who is the primary audience?passAI named cleverhans-lab/cleverhans explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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cleverhans-lab/cleverhans — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite