Resolving JavaScript Vulnerabilities in the Browser Runtime
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The volume of Web based malware on the Internet keeps rising despite huge investments on Web security. JavaScript, the dominant scripting language for Web applications, is the primary channel for most of these attacks. In this paper, we describe research into the design and implementation of new Web client protection system based on code instrumentation techniques. This system combines traditional static analysis techniques with a dynamic HTML, CSS and JavaScript code runtime monitoring agent to offer an efficient, easily deployable, policy driven framework for improved user protection. Rewriting and runtime monitoring are based on providing safe equivalents of JavaScript code constructs known to contain in securities and hence exploitable by malicious Web applications. As a demonstration of the practical capabilities of our framework, we also include a case study attack and empirical analysis of some of its various aspects across 1000 home pages belonging to the most popular web sites on the Internet.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it