牺牲可访问性以防止网络抓取
Sacrificing accessibility for not getting web scraped

原始链接: https://tilschuenemann.de/projects/sacrificing-accessibility-for-not-getting-web-scraped

这段文字似乎是一条经过大量混淆的信息,可能包含代码和自然语言,核心在于字体混淆和HTML操作。它详细描述了一个Python脚本,旨在混淆字体文件(“Mulish-Regular.ttf”)中的字形,然后将这种混淆应用于HTML文档中的文本。 该脚本通过重新映射字符创建一种新的混淆字体(“Mulish-Regular-scrambled.ttf”)。然后,它使用BeautifulSoup解析HTML,识别`

`元素,并将字符替换应用于这些元素*内部*的文本,排除代码块和标题。 这段文字还包含一些零碎的、看似无关的短语(“Et tu, Caesar?”,“Umj iRB wuDyj...”),以及一个概述缺点的部分——混淆可能会影响可读性,并且如果混淆字体没有得到正确处理,可能会导致错误。最终目标是通过改变网页中文本的视觉表现形式来编码信息。

## 为了阻止网络抓取而牺牲可访问性:摘要 一篇博文详细描述了一种新颖但有争议的方法,通过混淆字体字符到字形的映射来阻止人工智能训练模型抓取内容。虽然文本对人类来说仍然可读,但对基本的抓取程序来说却显得一团糟。作者承认这会影响可访问性,特别是对屏幕阅读器而言,但将其定位为一种概念验证。 讨论迅速集中在该方法的效果上。虽然大型语言模型*可以*付出努力来解码文本(有些甚至在几分钟内就完成了),但目标并非完全阻止,而是提高成本,足以阻止用于训练数据的自动化大规模抓取。 许多评论者指出了缺点:复制/粘贴、搜索索引和 RSS 订阅等功能损坏。人们对牺牲可访问性的伦理影响表示担忧,并对依赖服务条款来阻止坚定的抓取程序的法律徒劳性表示担忧。最终,共识倾向于这是一种临时措施,类似于早期的 DRM 尝试,并且会给合法用户带来令人沮丧的体验。
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原文

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# /// script # requires-python = ">=3.12" # dependencies = [ # "bs4", # "fonttools", # ] # /// import random import string from typing import Dict from bs4 import BeautifulSoup from fontTools.ttLib import TTFont def scramble_font(seed: int = 1234) -> Dict[str, str]: random.seed(seed) font = TTFont("src/fonts/Mulish-Regular.ttf") # Pick a Unicode cmap (Windows BMP preferred) cmap_table = None for table in font["cmap"].tables: if table.isUnicode() and table.platformID == 3: break cmap_table = table cmap = cmap_table.cmap # Filter codepoints for a-z and A-Z codepoints = [cp for cp in cmap.keys() if chr(cp) in string.ascii_letters] glyphs = [cmap[cp] for cp in codepoints] shuffled_glyphs = glyphs[:] random.shuffle(shuffled_glyphs) # Create new mapping scrambled_cmap = dict(zip(codepoints, shuffled_glyphs, strict=True)) cmap_table.cmap = scrambled_cmap translation_mapping = {} for original_cp, original_glyph in zip(codepoints, glyphs, strict=True): for new_cp, new_glyph in scrambled_cmap.items(): if new_glyph == original_glyph: translation_mapping[chr(original_cp)] = chr(new_cp) break font.save("src/fonts/Mulish-Regular-scrambled.ttf") return translation_mapping def scramble_html( input: str, translation_mapping: Dict[str, str], ) -> str: def apply_cipher(text): repl = "".join(translation_mapping.get(c, c) for c in text) return repl # Read HTML file soup = BeautifulSoup(input, "html.parser") # Find all main elements main_elements = soup.find_all("main") skip_tags = {"code", "h1", "h2"} # Apply cipher only to text within main for main in main_elements: for elem in main.find_all(string=True): if elem.parent.name not in skip_tags: elem.replace_with(apply_cipher(elem)) return str(soup)

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