I hereby claim:
- I am 9b on github.
- I am 9bplus (https://keybase.io/9bplus) on keybase.
- I have a public key ASDXArDVDZslzdQphHwNk0YbXgJapLZ9yFgrrWCGcK-7Ago
To claim this, I am signing this object:
| Below is a suggested recipe and the rationale behind each choice. Since this is a deeply complex blend—with bright florals (Ethiopia, Gesha), hoppy/citrus ferment notes (IPA, Pink Bourbon), and delicate sweetness—our goal is to showcase each layer without over-extracting. We achieve that by balancing concentration, using a slightly extended bloom, and carefully staging our temperatures. | |
| --- | |
| ## CORE BREW SETTINGS | |
| - **Ratio**: 1:15 | |
| **Why**: This slightly more concentrated ratio (compared to a common 1:16) helps intensify the nuanced flavors—particularly the floral and citrus characteristics of the Ethiopian and Pink Bourbon components—while still maintaining enough clarity to let the delicate Gesha notes come through. | |
| - **Bloom ratio**: 1:3 |
| """Extract MITRE ATT&CK techniques into a file.""" | |
| import bs4 as bs | |
| import requests | |
| root_url = "https://attack.mitre.org" | |
| file_name = "mitre.txt" | |
| def get_urls(): | |
| """Get MITRE ATT&CK URLs for processing.""" |
| Descriptor: | |
| Name: BlockadeIoService | |
| DisplayName: Blockade.io | |
| Description: Skills for blocking suspicious and malicious indicators using blockade.io | |
| SkillGroups: | |
| - Format: API | |
| Settings: | |
| OpenApiSpecUrl: https://gist.githubusercontent.com/9b/f3f3e4d831bddcf0ab3f8a32b471893b/raw/b40421aa882e556794d4305dea50bd7f9acc1188/blockadeio.yaml |
| openapi: 3.0.1 | |
| info: | |
| title: Blockade.io | |
| description: Block suspicious and malicious indicators in participating browsers | |
| version: "v1" | |
| servers: | |
| - url: https://api.blockade.io/ |
| Modify the script to include your username and API key. | |
| Create a virtualenv to keep your space clean: | |
| $ virtualenv -p python3 venv3 | |
| Activate it: | |
| $ source venv3/bin/activate | |
| { | |
| 'statistics': { | |
| 'noise': 264, | |
| 'ips_processed': 283, | |
| 'duplicate_entries': 4609, | |
| 'money_saved': '$179.17', | |
| 'duplicate_ratio': 94.0, | |
| 'noise_ratio': 93.0, | |
| 'time_saved': '8:48:00', | |
| 'interest': 19, |
I hereby claim:
To claim this, I am signing this object:
| !function(e) { | |
| function t(i) { | |
| if (n[i]) | |
| return n[i].exports; | |
| var o = n[i] = { | |
| "i": i, | |
| "l": !1, | |
| "exports": {} | |
| }; | |
| return e[i].call(o.exports, o, o.exports, t), |
| { | |
| "condition": "AND", | |
| "rules": [ | |
| { | |
| "id": "monitor_category", | |
| "field": "monitor_category", | |
| "type": "string", | |
| "input": "select", | |
| "operator": "equal", | |
| "value": "Competition", |
| """Use image analysis to extract scores from coffee charts.""" | |
| from PIL import Image, ImageFilter, ImageEnhance | |
| from pytesseract import image_to_string | |
| import cv2 | |
| import os | |
| import sys | |
| import numpy as np |