跳到正文
研踪PaperTrail
← 研踪 PaperTrail

arXiv:2611.15302 · v1

Browser Immune System (BIS): Innate and Adaptive Threat Detection in the Browser with a Cybersecurity Transformer

首次提交 2026-11-11 18:36
版本更新 2026-11-11 18:36
雷达观测 2026-11-13 11:11
arXiv ↗PDF ↗

摘要

Security decisions about a web page are best made where the page is: in the browser, before anything leaves the machine. We present the Browser Immune System (BIS), a browser extension that screens navigation with a cybersecurity transformer running entirely on the user's GPU, and alias-web, the model that powers it: a 4B-parameter model that starts from the dual-regime cybersecurity transformer (CT0), extends its public release alias3-micro with a context-category sensor, and is quantised to 4 bits and compiled to a 2.44 GB graph for WebGPU. alias-web is the first in-browser realisation of that model's typed decision mode, System 1, with its official pieces: the marker-token mapping, the complete pointer head and the final normalisation that the exported graph omits. It answers a typed security question in about 150 ms on a laptop GPU, and the same weights generate explanations at 10.5 tokens/s on demand. BIS treats the model as an immune system: an innate response, one System 1 question per threat class, runs on every page; an adaptive response, System 2 text, explains a verdict only when the user asks. On BISBENCH-8, eight synthetic sites of which six execute real but harmless malicious behaviour and two are adversarial controls, BIS returns the expected page verdict on 7/8 sites with both controls green and a class-level micro-F1 of 0.71, scans a page in 0.9 to 6.4 s, and gives identical verdicts across samples and across Chrome and Firefox. Single-variable diagnostics trace both benchmark errors to what the model was shown and, with a first pass over eleven real public pages, show that two of the seven questions answer yes on ordinary scripts and login forms: specificity on the real web is the open problem. We report every error, the engineering obstacles between a research checkpoint and a working extension, and what the evidence does not yet support.

AI 论文解读

基于摘要 · 非全文审阅

此版本尚未生成 AI 解读。解读由后台任务生成并按论文版本保存,登录后共享已有结果。

版本差异

目前只收录了一个版本。收录下一版后,可以对照标题、作者、分类和摘要。

观测到的版本

相邻记录可能跳过中间版本;首次发现 v2 及以上也会标为版本更新。

v1 · 2026-11-11 18:36 · 最新观测版本

Browser Immune System (BIS): Innate and Adaptive Threat Detection in the Browser with a Cybersecurity Transformer

Security decisions about a web page are best made where the page is: in the browser, before anything leaves the machine. We present the Browser Immune System (BIS), a browser extension that screens navigation with a cybersecurity transformer running entirely on the user's GPU, and alias-web, the model that powers it: a 4B-parameter model that starts from the dual-regime cybersecurity transformer (CT0), extends its public release alias3-micro with a context-category sensor, and is quantised to 4 bits and compiled to a 2.44 GB graph for WebGPU. alias-web is the first in-browser realisation of that model's typed decision mode, System 1, with its official pieces: the marker-token mapping, the complete pointer head and the final normalisation that the exported graph omits. It answers a typed security question in about 150 ms on a laptop GPU, and the same weights generate explanations at 10.5 tokens/s on demand. BIS treats the model as an immune system: an innate response, one System 1 question per threat class, runs on every page; an adaptive response, System 2 text, explains a verdict only when the user asks. On BISBENCH-8, eight synthetic sites of which six execute real but harmless malicious behaviour and two are adversarial controls, BIS returns the expected page verdict on 7/8 sites with both controls green and a class-level micro-F1 of 0.71, scans a page in 0.9 to 6.4 s, and gives identical verdicts across samples and across Chrome and Firefox. Single-variable diagnostics trace both benchmark errors to what the model was shown and, with a first pass over eleven real public pages, show that two of the seven questions answer yes on ordinary scripts and login forms: specificity on the real web is the open problem. We report every error, the engineering obstacles between a research checkpoint and a working extension, and what the evidence does not yet support.

查看此版本解读 →查看此版本原文 ↗