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BinarySoap

A python proof of concept tool to assist in your payloads classification against EDR/AV's machine learning models

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This is 1 of 88 launches in penetration testing tools — see how it stacks up on momentum and crowding →

785 other launches read as similar to this one →

Details

External ID
1413462783
Source
GITHUB
Company
—
Product
BinarySoap
Website domain
github.com
Launched
Oct. 10, 2026
Cohort
—
Upvotes
32
Upvotes percentile
0.60
Tags
—

Enrichment

Niche
penetration testing tools
Vertical
Security
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
testing tool for evaluating payloads against edr and av machine learning models
Manually corrected
False

Could you build this?

No Developing an adversarial tool to benchmark payloads against EDR/AV machine learning classifiers requires specialized cybersecurity expertise and ML security evasion knowledge.

What it would actually take: The architecture would consist of Python PE/ELF parser libraries (like pefile, lief), feature extraction mimicking production EDR ML models (e.g., Ember, byte histograms, entropy, imports), and adversarial optimization algorithms (e.g., genetic algorithms or gradient-based byte modification). The hard part is accurately replicating proprietary vendor heuristics and training classifiers on large datasets of malicious and benign binaries.

Competitors

Other products that read as similar to this one — 785 launches clear the similarity bar, closest 8 shown.

Attention rank: #290 of 786 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 346 days after the earliest competitor.

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