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| privacy:javascript [2026/08/12 10:05] – Review pass (Fable): fix stale figures that sat OUTSIDE the corpus section and so were missed by the windowed staleness guard. The embedded js_fold.mjs docstring still quoted the 4,322-corpus counts (959/1,063, LLVM 66, Esprima 15) two screens below the t karel.kubicek.claude | privacy:javascript [2026/08/21 14:50] (current) – Boxes: <wrap> renders a span, use uppercase <WRAP>; one box per list, not per bullet karel.kubicek.claude |
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| **LLM-based classification of web scripts is, as of 2026-08-06, essentially absent from the peer-reviewed literature.** A targeted search across PETS 2025/2026, USENIX Security 2025, NDSS 2025/2026, IMC 2025, TheWebConf 2025/2026, CCS 2025 and arXiv found no paper that classifies web scripts as trackers with a language model, or that uses one to summarise a script's privacy-relevant behaviour. The nearest work is adjacent rather than on-point: LLM-aided **deobfuscation** feeding a graph classifier for JavaScript //malware//,((//Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection//, [[https://arxiv.org/abs/2507.22447|arXiv:2507.22447]], 2025.)) LLM screening of malicious npm packages, and ''humanify'', which uses a model only to //suggest identifier names// during de-minification.(([[https://github.com/jehna/humanify|github.com/jehna/humanify]], v3.1.1, checked 2026-08-06. The AST rewrite is done by ''oxc''; the model only proposes names.)) | **LLM-based classification of web scripts is, as of 2026-08-06, essentially absent from the peer-reviewed literature.** A targeted search across PETS 2025/2026, USENIX Security 2025, NDSS 2025/2026, IMC 2025, TheWebConf 2025/2026, CCS 2025 and arXiv found no paper that classifies web scripts as trackers with a language model, or that uses one to summarise a script's privacy-relevant behaviour. The nearest work is adjacent rather than on-point: LLM-aided **deobfuscation** feeding a graph classifier for JavaScript //malware//,((//Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection//, [[https://arxiv.org/abs/2507.22447|arXiv:2507.22447]], 2025.)) LLM screening of malicious npm packages, and ''humanify'', which uses a model only to //suggest identifier names// during de-minification.(([[https://github.com/jehna/humanify|github.com/jehna/humanify]], v3.1.1, checked 2026-08-06. The AST rewrite is done by ''oxc''; the model only proposes names.)) |
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| <wrap todo>Treat this as an opportunity, not a settled answer. If you are planning an LLM-based script classifier, you are not late — but you also have no baseline to cite, so budget for building one, and for the reviewer question about cost, reproducibility and prompt/version drift that this page cannot yet answer for you.</wrap> | <WRAP todo>Treat this as an opportunity, not a settled answer. If you are planning an LLM-based script classifier, you are not late — but you also have no baseline to cite, so budget for building one, and for the reviewer question about cost, reproducibility and prompt/version drift that this page cannot yet answer for you.</WRAP> |
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| ==== Two 2025 results that change how you design a crawl ==== | ==== Two 2025 results that change how you design a crawl ==== |
| ==== Methodology and limitations of these figures ==== | ==== Methodology and limitations of these figures ==== |
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| * **Seven venues only.** CCS, IMC, NDSS, PETS, USENIX Security, TheWebConf, IEEE S&P, 2010–2026, with 2025 and 2026 provisional. **EuroS&P, ACSAC, RAID, AsiaCCS, CHI and SOUPS are absent entirely** — for this topic ACSAC and EuroS&P are a real hole, since a good deal of web-script security work lands there. Every claim here is a claim about those seven venues. | * **Seven venues only**, 2010–2026, with 2025 and 2026 provisional. Which venues, which years, what each stage of the selection funnel costs and which venue-years are empty are on [[literature:corpus]] and are not restated here. For //this// topic ACSAC and EuroS&P are a real hole, since a good deal of web-script security work lands there. Every claim here is a claim about those seven venues. |
| * **206 is a floor, and it has a false-positive tail.** Papers whose extraction never names a script as the object of detection are missing; conversely a handful of papers in the population (an e-voting client audit, a router-attack paper, a PHP injection-sink study) analyse JavaScript incidentally. The report script prints the full list so you can judge. | * **206 is a floor, and it has a false-positive tail.** Papers whose extraction never names a script as the object of detection are missing; conversely a handful of papers in the population (an e-voting client audit, a router-attack paper, a PHP injection-sink study) analyse JavaScript incidentally. The report script prints the full list so you can judge. |
| * **Not every field can carry a percentage.** ''crawlConfig.*'', ''legal.law'' and ''platforms'' reproduce to within a few points on a repeat extraction and carry the figures here. ''classification.method'' agrees on only **58%** of papers between two runs of the same schema over the same text, so its table above is a **rough share, not a precise figure** — a repeat extraction moves those rows. ''detection.phenomenon'', ''classification.resourceName'' and ''groundTruthSource'' agree on roughly 20% of exact strings, which is what the folding is for and why the family and ground-truth tables print their residue. | * **Not every field can carry a percentage.** ''crawlConfig.*'', ''legal.law'' and ''platforms'' reproduce to within a few points on a repeat extraction and carry the figures here. ''classification.method'' agrees on only **58%** of papers between two runs of the same schema over the same text, so its table above is a **rough share, not a precise figure** — a repeat extraction moves those rows. ''detection.phenomenon'', ''classification.resourceName'' and ''groundTruthSource'' agree on roughly 20% of exact strings, which is what the folding is for and why the family and ground-truth tables print their residue. |
| * **Silence is not absence.** "Does not state whether it ran headless" means the paper did not say. These are reporting figures, not practice figures. | * **Silence is not absence.** "Does not state whether it ran headless" means the paper did not say. These are reporting figures, not practice figures. |
| * **Every quoted figure was checked against the paper's own text.** The prevalence values in the extraction are model summaries, so each number reproduced on this page was re-located in ''paper.cols.txt'' after whitespace normalisation. The dataset's own "0.9% of quotes cannot be located" figure was measured on the earlier 4,322-paper run and has not been re-measured. | * **Every quoted figure was checked against the paper's own text.** The prevalence values in the extraction are model summaries, so each number reproduced on this page was re-located in ''paper.cols.txt'' after whitespace normalisation. The dataset's own "0.9% of quotes cannot be located" figure was measured on the earlier 4,322-paper run and has not been re-measured. |
| | * **Every query behind this section, the report script and its unedited output** are on [[provenance:privacy:javascript]]; corpus-level caveats are on [[literature:corpus]]. |
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| ===== Open Questions ===== | ===== Open Questions ===== |
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| * <wrap todo>**No public, hand-labelled corpus of tracking scripts exists.** Every current method builds its own labels from filter lists plus manual inspection, which is why cross-paper comparison is impossible. A shared benchmark would do for this field what EasyList did for request blocking.</wrap> | <WRAP todo> |
| * <wrap todo>**LLM-based script classification is unmeasured.** No peer-reviewed paper found as of 2026-08-06. The obvious study — LLM against WebGraph, AdFlush and NoT.js on a fixed script corpus, reporting cost and version drift as well as F1 — has no baseline yet.</wrap> | * **No public, hand-labelled corpus of tracking scripts exists.** Every current method builds its own labels from filter lists plus manual inspection, which is why cross-paper comparison is impossible. A shared benchmark would do for this field what EasyList did for request blocking. |
| * <wrap todo>**Nobody has measured how much a headless or containerised crawler under-counts //script// classification specifically.** {[jueckstock2021_realistic]} and {[annamalai2024_fpfed]} show the gap exists for API traces and fingerprinting scripts; its size for tracking-script prevalence at scale is unknown.</wrap> | * **LLM-based script classification is unmeasured.** No peer-reviewed paper found as of 2026-08-06. The obvious study — LLM against WebGraph, AdFlush and NoT.js on a fixed script corpus, reporting cost and version drift as well as F1 — has no baseline yet. |
| * <wrap todo>**Function-granularity blocking has no successor paper.** NoT.js {[amjad2024_notjs]} and ByteDefender {[bahrami2025_bytedefender]} both stop at detection plus surrogate generation; nobody has measured what happens when either is deployed to real users at scale, or whether trackers adapt.</wrap> | * **Nobody has measured how much a headless or containerised crawler under-counts //script// classification specifically.** {[jueckstock2021_realistic]} and {[annamalai2024_fpfed]} show the gap exists for API traces and fingerprinting scripts; its size for tracking-script prevalence at scale is unknown. |
| * <wrap todo>**Cross-platform divergence is a confound in every older result.** If 20.6% of scripts execute differently by platform {[zafar2025_samescript]}, every desktop-only prevalence figure in this page's tables is a measurement of the desktop path only. Re-running any of them on mobile is a well-defined study.</wrap> | * **Function-granularity blocking has no successor paper.** NoT.js {[amjad2024_notjs]} and ByteDefender {[bahrami2025_bytedefender]} both stop at detection plus surrogate generation; nobody has measured what happens when either is deployed to real users at scale, or whether trackers adapt. |
| | * **Cross-platform divergence is a confound in every older result.** If 20.6% of scripts execute differently by platform {[zafar2025_samescript]}, every desktop-only prevalence figure in this page's tables is a measurement of the desktop path only. Re-running any of them on mobile is a well-defined study. |
| | </WRAP> |
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| ===== Related Pages ===== | ===== Related Pages ===== |
| * [[Privacy:Cookies]] — what the scripts write; the provenance argument (a cookie set by a blocked resource) is the same idea one layer down. | * [[Privacy:Cookies]] — what the scripts write; the provenance argument (a cookie set by a blocked resource) is the same idea one layer down. |
| * [[Privacy:Fingerprinting]] — 39.8% of browser-fingerprinting papers are really detecting //scripts//, so that page and this one share a method. | * [[Privacy:Fingerprinting]] — 39.8% of browser-fingerprinting papers are really detecting //scripts//, so that page and this one share a method. |
| * [[Programming:Crawler]] — the instrumentation this page assumes you already have, compared in detail. Its per-tool pages ([[Programming:Crawler:OpenWPM]], [[Programming:Crawler:PageGraph]], [[Programming:Crawler:Foxhound]]) are promised but not yet written. | * [[Programming:Crawler]] — the instrumentation this page assumes you already have, compared in detail. Its per-tool pages [[Programming:Crawler:OpenWPM]] and [[Programming:Crawler:PageGraph]] are written; [[Programming:Crawler:Foxhound]] is still promised. |
| * [[Programming:Stateful stateless]] — only 27.6% of these papers state it, and a stateless crawl sees first-visit script behaviour only. | * [[Programming:Stateful stateless]] — only 27.6% of these papers state it, and a stateless crawl sees first-visit script behaviour only. |
| * [[Design:Website classification]] — where script classification sits in the wider taxonomy. | * [[Design:Website classification]] — where script classification sits in the wider taxonomy. |
