Nenad Stojanovic

167 papers A* 3A 5B 14C 5Misc 7Journal 22Unranked 102
YearRankTypeTitle / Venue / Authors
2026 J jnl
J. Log. Comput.
Maja Dabic, Nenad Stojanovic, Nebojsa Ikodinovic
2026 J jnl
Int. J. Fuzzy Syst.
José Carlos R. Alcantud, Nenad Stojanovic, Ljubica Djurovic, Maja Lakovic
2026 J jnl
J. Intell. Fuzzy Syst.
Ljubica Mudric-Staniskovski, Ivana Spasenic, Danijela Tadic, Nenad Stojanovic
2025 J jnl
Int. J. Intell. Syst.
Marina Svicevic, Nemanja Vucicevic, Filip Andric, Nenad Stojanovic
2025 J jnl
Neural Comput. Appl.
Nenad Stojanovic, Maja Lakovic, Ljubica Djurovic
2025 J jnl
J. Log. Comput.
Marija Boricic Joksimovic, Nebojsa Ikodinovic, Nenad Stojanovic
2024 J jnl
CoRR
Ljubica Djurovic, Maja Lakovic, Nenad Stojanovic
2022 J jnl
Inf.
Pavlos Eirinakis, Stavros Lounis, Stathis Plitsos, George Arampatzis, Kostas Kalaboukas, Klemen Kenda, Jinzhi Lu, Joze M. Rozanec, Nenad Stojanovic
2022 conf
ISIE
Paulo Leitão, Cristina Cristalli, Nicola Paone, Paolo Chiariotti, Wilfrid Utz, Nenad Stojanovic, José Barata, Robert Woitsch
2021 J jnl
Inf.
Michael Jacoby, Branislav Jovicic, Ljiljana Stojanovic, Nenad Stojanovic
2020 J jnl
Fundam. Informaticae
Radosav Djordjevic, Nebojsa Ikodinovic, Nenad Stojanovic
2020 conf
ICE/ITMC
Sailesh Abburu, Arne J. Berre, Michael Jacoby, Dumitru Roman, Ljiljana Stojanovic, Nenad Stojanovic
2020 conf
ICE/ITMC
Pavlos Eirinakis, Kostas Kalaboukas, Stavros Lounis, Ioannis Mourtos, Joze M. Rozanec, Nenad Stojanovic, Georgios Zois
2019 ch.
Data Science for Healthcare
Ziawasch Abedjan, Nozha Boujemaa, Stuart Campbell, Patricia Casla, Supriyo Chatterjea, Sergio Consoli, Cristóbal Costa Soria, Paul Czech, Marija Despenic, Chiara Garattini, Dirk Hamelinck, Adrienne Heinrich, Wessel Kraaij, Jacek Kustra, Aizea Lojo, Marga Martin Sanchez, Miguel Angel Mayer, Matteo Melideo, Ernestina Menasalvas, Frank Møller Aarestrup, Elvira Narro Artigot, Milan Petkovic, Diego Reforgiato Recupero, Alejandro Rodríguez González, Gisele Roesems Kerremans, Roland Roller, Mário Romão, Stefan Rüping, Felix Sasaki, Wouter Spek, Nenad Stojanovic, Jack Thoms, Andrejs Vasiljevs, Wilfried Verachtert, Roel Wuyts
2018 J jnl
FLAP
Nenad Stojanovic, Nebojsa Ikodinovic, Radosav Djordjevic
2018 J jnl
Ubiquity
Jeffrey H. Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, Marco Amador
2018 conf
IEEE BigData
Nenad Stojanovic, Milan Jovic
2018 conf
IEEE BigData
Nenad Stojanovic, Dejan Milenovic
2017 conf
IEEE BigData
Nenad Stojanovic, Marko Dinic, Ljiljana Stojanovic
2017 conf
ICE/ITMC
Ljiljana Stojanovic, Nenad Stojanovic
2017 C conf
CLOSER
Yiannis Verginadis, Iyad Alshabani, Gregoris Mentzas, Nenad Stojanovic
2016 conf
OTM Workshops
Paulo Figueiras, Guilherme Guerreiro, Ruben Costa, Luka Bradesko, Nenad Stojanovic, Ricardo Jardim-Gonçalves
2016 conf
IEEE BigData
Ljiljana Stojanovic, Marko Dinic, Nenad Stojanovic, Aleksandar Stojadinovic
2015 conf
IEEE BigData
Nenad Stojanovic, Marko Dinic, Ljiljana Stojanovic
2015 conf
DEBS
Aleksandar Stojadinovic, Nenad Stojanovic, Ljiljana Stojanovic
2015 ed.
Challenge+DC@RuleML
Nick Bassiliades, Paul Fodor, Adrian Giurca, Georg Gottlob, Tomás Kliegr, Grzegorz J. Nalepa, Monica Palmirani, Adrian Paschke, Mark Proctor, Dumitru Roman, Fariba Sadri, Nenad Stojanovic
2014 conf
CAiSE (Forum/Doctoral Consortium)
Babis Magoutas, Nenad Stojanovic, Alexandros Bousdekis, Dimitris Apostolou, Gregoris Mentzas, Ljiljana Stojanovic
2014 conf
DEBS
Nenad Stojanovic, Yongchun Xu, Boban Stajic Nissatech, Ljiljana Stojanovic
2014 conf
DEBS
Nenad Stojanovic, Ljiljana Stojanovic, Yongchun Xu, Boban Stajic Nissatech
2014 ch.
Towards the Internet of Services
Rudi Studer, Catherina Burghart, Nenad Stojanovic, Thanh Tran, Valentin Zacharias
2014 conf
SOCA
Dominik Riemer, Ljiljana Stojanovic, Nenad Stojanovic
2014 conf
DEBS
Nenad Stojanovic, Yongchun Xu, Aleksandar Stojadinovic, Ljiljana Stojanovic
2013 A conf
CAiSE
Dominik Riemer, Nenad Stojanovic, Ljiljana Stojanovic
2013 C conf
MoMM
Yongchun Xu, Nenad Stojanovic, Ljiljana Stojanovic, Dusan Kostic
2013 conf
DEBS
Dominik Riemer, Ljiljana Stojanovic, Nenad Stojanovic
2013 conf
DEBS
Nenad Stojanovic, Dominik Riemer, Yongchun Xu
2013 conf
DEBS
Nenad Stojanovic, Ljiljana Stojanovic, Roland Stuehmer
2012 conf
ESWC (Satellite Events)
Yongchun Xu, Ljiljana Stojanovic, Nenad Stojanovic, Tobias Schuchert
2012 conf
EuroMed
Areti Damala, Nenad Stojanovic, Tobias Schuchert, Jorge Moragues, Ana Cabrera, Kiel Gilleade
2012 conf
ESWC (Satellite Events)
Laurent Pellegrino, Iyad Alshabani, Françoise Baude, Roland Stühmer, Nenad Stojanovic
2012 conf
Business Process Management Workshops
Babis Magoutas, Dominik Riemer, Dimitris Apostolou, Jun Ma, Gregoris Mentzas, Nenad Stojanovic
2012 conf
DEBS
Yongchun Xu, Nenad Stojanovic, Ljiljana Stojanovic, Ana Cabrera, Tobias Schuchert
2012 conf
ISWC (Posters & Demos)
Yongchun Xu, Nenad Stojanovic, Ljiljana Stojanovic, Tobias Schuchert
2012 conf
DEBS
Yongchun Xu, Nenad Stojanovic, Ljiljana Stojanovic, Tobias Schuchert
2012 J jnl
Appl. Artif. Intell.
Darko Anicic, Sebastian Rudolph, Paul Fodor, Nenad Stojanovic
2012 J jnl
Semantic Web
Darko Anicic, Sebastian Rudolph, Paul Fodor, Nenad Stojanovic
2012 conf
DEBS
Zbigniew Jerzak, Thomas Heinze, Matthias Fehr, Daniel Gröber, Raik Hartung, Nenad Stojanovic
2012 A* conf
ISMAR
Nenad Stojanovic, Areti Damala, Tobias Schuchert, Ljiljana Stojanovic, Stephen H. Fairclough, John Moores
2012 ch.
Empowering Open and Collaborative Governance
Mitja Trampus, Sinan Sen, Nenad Stojanovic, Marko Grobelnik
2012 conf
DEBS
Nenad Stojanovic, Roland Stühmer, Françoise Baude, Philippe Gibert
2012 conf
DEBS
Roland Stühmer, Nenad Stojanovic, Stefan Obermeier, Philippe Gibert
2011 conf
RuleML Europe
Darko Anicic, Sebastian Rudolph, Paul Fodor, Nenad Stojanovic
2011 conf
ESWC (2)
Yongchun Xu, Nenad Stojanovic, Ljiljana Stojanovic, Darko Anicic, Rudi Studer
2011 conf
Future Internet Assembly
Alexander Gluhak, Manfred Hauswirth, Srdjan Krco, Nenad Stojanovic, Martin Bauer, Rasmus H. Nielsen, Stephan Haller, Neeli R. Prasad, Vinny Reynolds, Óscar Corcho
2011 conf
DEBS
Nenad Stojanovic, Dejan Milenovic, Yongchun Xu, Ljiljana Stojanovic, Darko Anicic, Rudi Studer
2011 conf
DEBS
Nenad Stojanovic
2011 A* conf
WWW
Darko Anicic, Paul Fodor, Sebastian Rudolph, Nenad Stojanovic
2011 conf
DEBS
Pedro Bizarro, K. Mani Chandy, Nenad Stojanovic
2011 conf
DEBS
Roland Stühmer, Nenad Stojanovic
2011 conf
RuleML Europe
Nenad Stojanovic, Alexander Artikis
2011 conf
RuleML Europe
Darko Anicic, Sebastian Rudolph, Paul Fodor, Nenad Stojanovic
2011 conf
Foundations for the Web of Information and Services
Nenad Stojanovic, Ljiljana Stojanovic, Darko Anicic, Jun Ma, Sinan Sen, Roland Stühmer
2010 conf
RR
Darko Anicic, Paul Fodor, Sebastian Rudolph, Roland Stühmer, Nenad Stojanovic, Rudi Studer
2010 conf
DEBS
Sinan Sen, Nenad Stojanovic, Ljiljana Stojanovic
2010 conf
DEBS
Sinan Sen, Nenad Stojanovic, Bijan Fahimi Shemrani
2010 A conf
CAiSE
Sinan Sen, Nenad Stojanovic
2010 C conf
ACC
Nenad Stojanovic, Jordan M. Berg, D. H. S. Maithripala, Mark Holtz
2010 conf
LDSI@FIA
Andreas Wagner, Darko Anicic, Roland Stühmer, Nenad Stojanovic, Andreas Harth, Rudi Studer
2010 conf
SBPM
Darko Anicic, Nenad Stojanovic, Ljiljana Stojanovic
2010 ed.
SBPM
Nenad Stojanovic, Barry Norton
2010 conf
ISWC (Posters & Demos)
Yongchun Xu, Peter Wolf, Nenad Stojanovic, Hans-Jörg Happel
2009 conf
DEBS
Sinan Sen, Nenad Stojanovic, Ruofeng Lin
2009 conf
DEBS
Darko Anicic, Paul Fodor, Nenad Stojanovic, Roland Stühmer
2009 conf
OTM Conferences (2)
Roland Stühmer, Darko Anicic, Sinan Sen, Jun Ma, Kay-Uwe Schmidt, Nenad Stojanovic
2009 conf
DEBS
Roland Stühmer, Darko Anicic, Nenad Stojanovic, Sinan Sen
2009 conf
DEBS
Darko Anicic, Paul Fodor, Nenad Stojanovic, Roland Stühmer
2009 conf
CSE (1)
Darko Anicic, Paul Fodor, Roland Stühmer, Nenad Stojanovic
2009 conf
AAAI Spring Symposium: Intelligent Event Processing
Darko Anicic, Nenad Stojanovic
2009 conf
Business Process Management Workshops
Rainer von Ammon, Opher Etzion, Heiko Ludwig, Adrian Paschke, Nenad Stojanovic
2009 Misc conf
ISWC
Roland Stühmer, Darko Anicic, Sinan Sen, Jun Ma, Kay-Uwe Schmidt, Nenad Stojanovic
2009 B conf
ESWC
Ivan Markovic, Sukesh Jain, Mahmoud El-Gayyar, Armin B. Cremers, Nenad Stojanovic
2009 conf
AAAI Spring Symposium: Intelligent Event Processing
Nenad Stojanovic, Andreas Abecker, Opher Etzion, Adrian Paschke
2009 ed.
SBPM@ESWC
Martin Hepp, Knut Hinkelmann, Nenad Stojanovic
2009 conf
Wirtschaftsinformatik (1)
Ivan Markovic, Florian Hasibether, Sukesh Jain, Nenad Stojanovic
2009 J jnl
AI Mag.
Jie Bao, Uldis Bojars, Tanzeem Choudhury, Li Ding, Mark Greaves, Ashish Kapoor, Sandy Louchart, Manish Mehta, Bernhard Nebel, Sergei Nirenburg, Tim Oates, David L. Roberts, Antonio Sanfilippo, Nenad Stojanovic, Kristen Stubbs, Andrea Lockerd Thomaz, Katherine M. Tsui, Stefan Wölfl
2009 J jnl
IEEE Intell. Syst.
Dimitris Apostolou, Nenad Stojanovic, Darko Anicic
2009 conf
AAAI Spring Symposium: Intelligent Event Processing
Marwane El Kharbili, Nenad Stojanovic
2009 conf
SBPM@ESWC
Ljiljana Stojanovic, Jun Ma, Nenad Stojanovic
2008 conf
Multikonferenz Wirtschaftsinformatik
Ivan Markovic, Alessandro Costa Pereira, Nenad Stojanovic
2008 conf
FIS
Darko Anicic, Nenad Stojanovic
2008 ch.
New Directions in Intelligent Interactive Multimedia
Dimitris Apostolou, Stelios Karapiperis, Nenad Stojanovic
2008 Misc conf
SAC
Nenad Stojanovic, Ljiljana Stojanovic, Jun Ma
2008 conf
IESA
Keith Popplewell, Nenad Stojanovic, Andreas Abecker, Dimitris Apostolou, Gregoris Mentzas, Jenny A. Harding
2008 conf
Multikonferenz Wirtschaftsinformatik
Kioumars Namiri, Nenad Stojanovic
2008 conf
ICEIS (3-2)
Darko Anicic, Nenad Stojanovic
2007 conf
SBPM
Kioumars Namiri, Nenad Stojanovic
2007 conf
CAiSE Forum
Kioumars Namiri, Nenad Stojanovic
2007 conf
GI Jahrestagung (1)
Kioumars Namiri, M.-M. Kügler, Nenad Stojanovic
2007 conf
MTSR
Nenad Stojanovic, Dimitris Apostolou, Spyridon Ntioudis, Gregoris Mentzas
2007 B conf
WISE
Ljiljana Stojanovic, Nenad Stojanovic, Jun Ma
2007 conf
GI Jahrestagung (1)
Kioumars Namiri, Nenad Stojanovic
2007 B conf
K-CAP
Hans-Jörg Happel, Ljiljana Stojanovic, Nenad Stojanovic
2007 B conf
ESWC
Kay-Uwe Schmidt, Ljiljana Stojanovic, Nenad Stojanovic, Susan Thomas
2007 conf
Web Intelligence
Ljiljana Stojanovic, Nenad Stojanovic, Jun Ma
2007 conf
OTM Conferences (1)
Kioumars Namiri, Nenad Stojanovic
2007 ed.
SBPM
Martin Hepp, Knut Hinkelmann, Dimitris Karagiannis, Rüdiger Klein, Nenad Stojanovic
2007 conf
WISE Workshops
Kioumars Namiri, Nenad Stojanovic
2006 conf
CEC/EEE
Jorn Philipp Knüchel, Nenad Stojanovic
2006 J jnl
Electron. Gov. an Int. J.
Ljiljana Stojanovic, Nenad Stojanovic, Dimitris Apostolou
2006 conf
AAAI Spring Symposium: Semantic Web Meets eGovernment
Nenad Stojanovic, Ljiljana Stojanovic, Knut Hinkelmann, Gregoris Mentzas, Andreas Abecker
2006 conf
AAAI Spring Symposium: Semantic Web Meets eGovernment
Nenad Stojanovic, Gregoris Mentzas, Dimitris Apostolou
2005 conf
EGOV (Workshops and Posters)
Nenad Stojanovic, Ljiljana Stojanovic
2005 conf
Web Intelligence
Nenad Stojanovic
2005 B conf
WISE
Nenad Stojanovic
2005 J jnl
Künstliche Intell.
Nenad Stojanovic
2005 conf
GI Jahrestagung (2)
Peter Fankhauser, Norbert Fuhr, Jens Hartmann, Anthony Jameson, Claus-Peter Klas, Stefan Klink, Agnes Koschmider, Sascha Kriewel, Patrick Lehti, Peter Luksch, Ernst W. Mayr, Andreas Oberweis, Paul Ortyl, Stefan Pfingstl, Patrick Reuther, Ute Rusnak, Guido Sautter, Klemens Böhm, André Schaefer, Lars Schmidt-Thieme, Eric Schwarzkopf, Nenad Stojanovic, Rudi Studer, Roland Vollmar, Bernd Walter, Alexander Weber
2005 J jnl
Web Intell. Agent Syst.
Nenad Stojanovic
2005 conf
Wirtschaftsinformatik
Nenad Stojanovic
2005 J jnl
Inf. Syst.
Nenad Stojanovic
2005 B conf
K-CAP
Nenad Stojanovic
2005 conf
From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments
Jens Hartmann, Nenad Stojanovic, Rudi Studer, Lars Schmidt-Thieme
2005
Nenad Stojanovic
2005 conf
ECIS
Marc Ehrig, Peter Haase, Mark Hefke, Nenad Stojanovic
2004 B conf
ICTAI
Nenad Stojanovic, Ljiljana Stojanovic
2004 conf
Web Intelligence
Nenad Stojanovic
2004 B conf
ICTAI
Nenad Stojanovic
2004 conf
Web Intelligence
Nenad Stojanovic, Rudi Studer, Ljiljana Stojanovic
2004 conf
PAKM
Nenad Stojanovic
2004 conf
CoopIS/DOA/ODBASE (2)
Ljiljana Stojanovic, Andreas Abecker, Nenad Stojanovic, Rudi Studer
2004 A conf
ER
Nenad Stojanovic, Ljiljana Stojanovic
2004 C conf
SEKE
Nenad Stojanovic
2004 conf
EEE
Nenad Stojanovic
2004 conf
GI Jahrestagung (2)
Nenad Stojanovic
2004 B conf
EKAW
Nenad Stojanovic, Rudi Studer
2004 conf
ICAC
Ljiljana Stojanovic, Andreas Abecker, Nenad Stojanovic, Rudi Studer
2004 J jnl
J. Web Semant.
Raphael Volz, Siegfried Handschuh, Steffen Staab, Ljiljana Stojanovic, Nenad Stojanovic
2004 A* conf
ICDM
Nenad Stojanovic
2003 Misc conf
ISWC
Nenad Stojanovic, Rudi Studer, Ljiljana Stojanovic
2003 C conf
DEXA
Nenad Stojanovic
2003 conf
Web Intelligence
Nenad Stojanovic
2003 B conf
K-CAP
Nenad Stojanovic, Jorge Gonzalez, Ljiljana Stojanovic
2003 A conf
ER
Nenad Stojanovic
2003 A conf
CAiSE
Nenad Stojanovic
2003 B conf
WISE
Nenad Stojanovic
2003 J jnl
J. Univers. Comput. Sci.
Nenad Stojanovic
2003 conf
WOW
Nenad Stojanovic
2003 conf
Wissensmanagement
Nenad Stojanovic
2003 conf
OTM
Ljiljana Stojanovic, Nenad Stojanovic, Jorge Gonzalez, Rudi Studer
2003 B conf
K-CAP
Ljiljana Stojanovic, Alexander Maedche, Nenad Stojanovic, Rudi Studer
2003 conf
Spinning the Semantic Web
Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer, York Sure
2003 conf
GI Jahrestagung (1)
Sudhir Agarwal, Peter Fankhauser, Jorge Gonzalez-Ollala, Jens Hartmann, Silvia Hollfelder, Anthony Jameson, Stefan Klink, Patrick Lehti, Michael Ley, Emma Rabbidge, Eric Schwarzkopf, Nitesh Shrestha, Nenad Stojanovic, Rudi Studer, Gerd Stumme, Bernd Walter, Alexander Weber
2002 conf
IIP
Nenad Stojanovic, Ljiljana Stojanovic, Raphael Volz
2002 conf
ICEIMT
Peter Heisig, Martine Callot, Jan Goossenaerts, Kurt Kosanke, John Krogstie, Nenad Stojanovic
2002 conf
ER (Workshops)
Ljiljana Stojanovic, Nenad Stojanovic, Alexander Maedche
2002 conf
ECIS
Nenad Stojanovic, Ljiljana Stojanovic, Siegfried Handschuh
2002 conf
German Workshop on Experience Management
Ljiljana Stojanovic, Nenad Stojanovic, Siegfried Handschuh
2002 conf
EC-Web
Erol Bozsak, Marc Ehrig, Siegfried Handschuh, Andreas Hotho, Alexander Maedche, Boris Motik, Daniel Oberle, Christoph Schmitz, Steffen Staab, Ljiljana Stojanovic, Nenad Stojanovic, Rudi Studer, Gerd Stumme, York Sure, Julien Tane, Raphael Volz, Valentin Zacharias
2002 Misc conf
SAC
Ljiljana Stojanovic, Nenad Stojanovic, Raphael Volz
2002 conf
PAKM
Nenad Stojanovic, Ljiljana Stojanovic, Jorge Gonzalez
2002 conf
WISE Workshops
Nenad Stojanovic, Ljiljana Stojanovic, Jorge Gonzalez
2002 Misc conf
FLAIRS
Nenad Stojanovic, Ljiljana Stojanovic
2002 Misc conf
FLAIRS
Tanja Sollazzo, Siegfried Handschuh, Steffen Staab, Martin R. Frank, Nenad Stojanovic
2002 conf
OTM
Nenad Stojanovic, Ljiljana Stojanovic
2002 B conf
EKAW
Ljiljana Stojanovic, Alexander Maedche, Boris Motik, Nenad Stojanovic
2001 conf
BNCOD
Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer, York Sure
2001 B conf
K-CAP
Nenad Stojanovic, Alexander Maedche, Steffen Staab, Rudi Studer, York Sure
1997 Misc conf
KI
Nenad Stojanovic, Ljiljana Stoiljkovic, Dejan Milenovic, V. Stoiljkovic
docs/js_analysis.md
← Index docs/js_analysis.md markdown
# JavaScript Malware Analysis

REDB extracts features from JavaScript files using five dedicated extractors plus two shared extractors (IOCs and strings). Magika detects the file as `javascript`; the file must be listed in `SUPPORTED_FORMATS` in `.env` to be processed.

## Configuration

Add `javascript` to `SUPPORTED_FORMATS` in `.env`:

```
SUPPORTED_FORMATS=['pebin', 'elf', 'macho', 'apk', 'javascript']
```

| Variable | Default | Required | Description |
|----------|---------|----------|-------------|
| `SUPPORTED_FORMATS` | `['pebin']` | Yes | Must include `javascript` for JS files to be processed |
| `JS_DEOBFUSCATOR_PATH` | `webcrack` | No | Path or name of an external JS deobfuscator. If not installed, falls back to `jsbeautifier` (Python library, always available) |
| `JS_DEOBFUSCATE_TIMEOUT` | `60` | No | Timeout in seconds for the external deobfuscator subprocess |
| `JS_XRAY_RUNNER_PATH` | bundled `redb/extractors/js_extractors/scripts/js-xray-runner.js` | No | Node bridge that runs `@nodesecure/js-x-ray` and emits JSON. Falls back to heuristic-only when the bridge or its `node_modules` are missing |
| `JS_XRAY_NODE_BIN` | `node` | No | Node binary to invoke the bridge with |
| `JS_XRAY_TIMEOUT` | `30` | No | Timeout in seconds for the js-x-ray subprocess |

### Python dependencies

Installed via `requirements.txt`:
- `jsbeautifier` — code normalization and fallback deobfuscation
- `chardet` — source encoding detection
- `pyjsparser` — ES5.1 AST parser. The obfuscation heuristic's `avg_identifier_length<2` strong signal depends on AST identifier walking, so without pyjsparser the JS pipeline runs in a degraded "regex-only" mode that misses a key obfuscator.io tell. Listed as required, not optional.

### External Node tools

The Docker image bundles everything below; host CLI installs need to be done once.

- **webcrack** — reverses webpack bundling, obfuscator.io output, and common packing patterns. Significantly better than jsbeautifier for real-world obfuscated malware. Pinned to **2.16.0** in the `Dockerfile` and installed globally inside the container; on the host run `npm install -g webcrack@2.16.0` (or set `JS_DEOBFUSCATOR_PATH` to a non-default path).
- **@nodesecure/js-x-ray** — static AST analyser used by the NodeSecure project (and npm's package scanning) that recognises specific obfuscator families (`jsfuck`, `obfuscator.io`, `morse`, `jjencode`, `freejsobfuscator`, ...) and emits structured warnings. We invoke it via the bundled Node bridge at `redb/extractors/js_extractors/scripts/js-xray-runner.js`. The Dockerfile runs `npm install --omit=dev` in that directory at build time; on the host run the same once: `cd redb/extractors/js_extractors/scripts && npm install --omit=dev`. When `node_modules/@nodesecure/js-x-ray` is absent, the Python wrapper short-circuits without forking a subprocess and the pipeline falls back to heuristic-only obfuscation detection (no error, just a `debug` log line). A local patch (see *Patches* below) is auto-applied by `patch-package` during `npm install` to fix a Node 22 compatibility regression.

#### Patches

`redb/extractors/js_extractors/scripts/patches/` holds local patches applied to `node_modules/` after every `npm install` via the `postinstall: patch-package` hook in `package.json`. There's currently one:

| File | Upstream | What it fixes |
|---|---|---|
| `@nodesecure+js-x-ray+7.3.0.patch` | [@nodesecure/js-x-ray#???](https://github.com/NodeSecure/js-x-ray) | Changes `import { builtinModules } from "repl"` to `from "module"` in `src/probes/isLiteral.js`. `repl.builtinModules` was a deprecated re-export that Node 22.x stopped exposing as a named ESM export somewhere between 22.10 and 22.22; `module.builtinModules` is the canonical location and works on every Node ≥9.3. Without the patch, importing js-x-ray throws `SyntaxError: The requested module 'repl' does not provide an export named 'builtinModules'` and the bridge falls back to heuristic-only. |

Patches apply automatically — no manual step required. They're regenerated with `npx patch-package <package-name>` after editing the file in `node_modules/`. Drop a patch by deleting its file in `patches/` once upstream ships a fix.

### Host CLI vs Docker

| | Host CLI | Docker (SaaS) |
|---|---|---|
| Python deps | `pip install -r requirements.txt` | done at image build |
| Node 22 LTS | install once on host (see below) | bundled in image |
| webcrack | `sudo npm install -g webcrack@2.16.0`* | bundled in image |
| @nodesecure/js-x-ray | `cd redb/extractors/js_extractors/scripts && npm install --omit=dev` | bundled in image |

\* Global `npm install -g` writes into `/usr/lib/node_modules/` on a system-installed Node (apt / NodeSource), which is root-owned — so `sudo` is required. Skip the `sudo` if you installed Node via `nvm` or a user-owned prefix. The js-x-ray install is local to the repo so it does *not* need root; running it under `sudo` only makes `node_modules/` root-owned (harmless, the Python wrapper only reads, but tidier without).

Both paths produce the same fully-equipped pipeline. The Docker image is self-contained — unlike Binary Ninja (which is mounted from the host because of size and licensing), the JS Node tools are small enough to bundle.

#### Installing Node 22 LTS on the host

Pick whichever matches your OS — all paths land you on `node --version` reporting `v22.x`.

**macOS (Homebrew).** Most REDB developers run macOS; `brew` is the path of least resistance:

```bash
brew install node@22
brew link --overwrite node@22
node --version  # v22.x
```

**Linux (Debian / Ubuntu via NodeSource).** Same recipe the Dockerfile uses, so behaviour matches the container exactly:

```bash
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash -
sudo apt-get install -y nodejs
node --version
```

**Linux/macOS via `nvm` (multiple Node versions on one host).** Useful if other projects on the same machine want different majors:

```bash
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.1/install.sh | bash
nvm install 22 --lts
nvm use 22
```

After Node is in place, run the two `npm install` commands from the table above. Verify the toolchain with these commands (run them from the repo root — adjust the path if your repo lives elsewhere):

```bash
# webcrack on PATH (global install)
which webcrack && webcrack --version                  # 2.16.0

# js-x-ray installed locally next to the bridge
ls -d redb/extractors/js_extractors/scripts/node_modules/@nodesecure/js-x-ray

# end-to-end smoke test — should print one line of JSON
node redb/extractors/js_extractors/scripts/js-xray-runner.js test_files/test_malicious.js
```

If either of the first two checks fails, the JS pipeline still runs — webcrack falls back to `jsbeautifier` and js-x-ray short-circuits to heuristic-only obfuscation detection — but you lose the obfuscator-family identification and most semantic deobfuscation. The Python side never raises on a missing tool; it logs at `debug` and moves on.

---

## Pipeline architecture

For every JS sample, `workers.py` builds **one `JSContext`** (`redb/extractors/js_extractors/js_context.py`) and threads it into every JS extractor that runs. The context owns all per-sample shared state:

| `JSContext` field | Computed | Consumed by |
|---|---|---|
| `raw_bytes` | Single `open(...).read()` at construction | `BasicPropertiesExtractor`/`HashExtractor` go through their own paths; `self.binary` on each JS extractor delegates here |
| `source` | Decoded once at construction (BOM → UTF-8 → chardet → latin-1 fallback) | `self.js_source` on every JS extractor |
| `lines` | `source.splitlines()`, cached on first access | `self.lines` on every JS extractor |
| `text_entropy` | Shannon entropy over `source`, cached | `JSFeaturesExtractor` (stored as `text_entropy` column), `JSDeobfuscationExtractor` (`original_entropy`) |
| `scan` | One `scan_source()` pass producing `{pattern_name: {count, lines}}` for every regex in `js_patterns.PATTERNS` and `js_patterns.FEATURE_PATTERNS`, cached | `JSFeaturesExtractor` (per-pattern counts + obfuscation score + technique detection), `JSSuspiciousAPIsExtractor` (every finding), `JSDeobfuscationExtractor` (original-side `new_apis_found` set) |
| `ast` | `pyjsparser.parse(source)` lazily on first access, returns `None` if pyjsparser is absent or parsing fails | `JSFeaturesExtractor` for `total_function_count` / `total_variable_count` / `max_nesting_depth` / `avg_identifier_length` |
| `deobfuscated` | External JS deobfuscator (default `webcrack`) with `jsbeautifier` fallback, run lazily once per sample. Returns `(text, normalizer_used)` or `(None, None)` when neither produced output | `JSDeobfuscationExtractor` (metrics row), `JSContentExtractor` (persisted text) — both read the same cached value, so the subprocess runs at most once |
| `xray` | `@nodesecure/js-x-ray` invoked via the bundled Node bridge, run lazily once per sample. Returns `XRayResult(obfuscator, warnings)`; empty when the bridge or its `node_modules` are missing, when Node is absent, or when the subprocess errors out | `JSFeaturesExtractor` reads `obfuscator` for the `obfuscator_name` column and uses it as the authoritative signal in the obfuscation verdict |
| `content_type` | The magika label workers.py dispatched on (`"javascript"`), carried through so `JSContentExtractor` can record it without re-running magika | `JSContentExtractor` |

The shape eliminates the per-extractor disk reads, source decodes, scan passes, AST parses, deobfuscation runs, and entropy computations the pipeline used to do independently for each extractor instance.

### Shared regex catalogue

All compiled regexes live in `redb/extractors/js_extractors/js_patterns.py`:

- `PATTERNS` — 46 named entries that double as suspicious-API row labels and as count sources for the features extractor (the 8 patterns shared across both extractors are defined exactly once here).
- `CATEGORIES` — pattern name → category (`code_execution` / `network` / `filesystem` / `process` / `registry` / `crypto_encoding` / `dom_manipulation`).
- `FEATURE_PATTERNS` — 11 additional regexes used only by `JSFeaturesExtractor` (hex/unicode escapes, base64 strings, comments, string concatenation, etc.).
- `STRING_PATTERNS` — 6 regexes used only by `JSStringsExtractor` for encoded-string discovery (`hex_escape_seq`, `unicode_escape_seq`, `charcode_call`, `base64_quoted`, `long_quoted`, `concat_chain`). Distinct from the look-alike entries in `FEATURE_PATTERNS` (e.g. `STRING_PATTERNS["hex_escape_seq"]` matches 4+ consecutive `\xHH` while `FEATURE_PATTERNS["hex_escape"]` matches a single one). Not folded into `JSContext.scan` because the strings extractor needs the match objects (capture groups, raw text) and is the sole consumer.
- `scan_source(source, patterns=...)` — runs every compiled pattern against `source` once, with O(log N) line lookup via a precomputed line-offset table, and returns `{name: {"count": int, "lines": [unique_sorted]}}` for any pattern that matched.

All `PATTERNS` are compiled with `re.IGNORECASE`. JS is case-sensitive at runtime, but the patterns themselves match literal-case identifiers (`eval`, `atob`, `WScript.Shell`, etc.) that real-world JS spells exactly as written, so IGNORECASE produces no extra matches in normal code while making the catalogue easier to share. Two pinned tests (`test_pattern_match_is_case_insensitive`, `test_pattern_counts_are_case_insensitive`) guard against an accidental flag regression.

---

## JSFeaturesExtractor

**Table:** `redb_js_features` (1 row per sample)

Extracts structural metadata and obfuscation indicators from JavaScript source code. No external tools required — pure regex (via the shared `JSContext.scan`) and optional AST parsing.

### Fields

File size and byte-level entropy are not stored here — they are written by `BasicPropertiesExtractor` (`redb_basic_properties.filesize`, `redb_basic_properties.file_entropy`) and joinable on `sha256`. Character-level entropy is stored separately as `text_entropy` because it differs meaningfully from byte entropy on non-ASCII sources (e.g. UTF-16 inflates byte counts and depresses byte entropy).

| Field | How it is extracted |
|-------|-------------------|
| `line_count` | `source.splitlines()` count |
| `char_count` | Length of decoded text (distinct from `filesize` for non-ASCII sources) |
| `text_entropy` | Shannon entropy over the character distribution of the decoded source text. Distinct from `redb_basic_properties.file_entropy`, which is over raw bytes. Obfuscated/packed JS typically scores above 5.0; clean code is usually 4.04.8. The obfuscation-score thresholds are tuned on this value |
| `max_line_length` | Longest line in characters. Values above 5–10K suggest minification or single-line obfuscation |
| `avg_line_length` | Mean line length across all lines |
| `is_minified` | True when the file has fewer than 5 lines but more than 500 characters, or when `avg_line_length` exceeds 500. These thresholds come from observing webpack/uglify output vs hand-written code |
| `is_likely_obfuscated` | True when `@nodesecure/js-x-ray` recognised the obfuscator family, OR when the heuristic score reaches 60 *and* at least one strong signal fired (encoding density >5%, single line >10K chars, avg identifier length <2, or text entropy >5.0). The two-tier check stops mid-band entropy + single eval + handful of `\xHH` escapes from masquerading as a verdict — the failure mode of the original score-only threshold |
| `obfuscator_name` | Family name reported by js-x-ray (`jsfuck`, `obfuscator.io`, `morse`, `jjencode`, `freejsobfuscator`, ...) or empty when js-x-ray didn't flag the sample / wasn't installed. When this is non-empty, `is_likely_obfuscated` is forced True regardless of the heuristic |
| `obfuscation_score` | Weighted heuristic score 0100 (see section below). Kept as the explainability layer even when the verdict comes from js-x-ray |
| `obfuscation_techniques` | Array of detected technique labels (see section below) |
| `eval_count` | Regex `\beval\s*\(` — direct eval calls, the most common JS code execution vector |
| `function_constructor_count` | Regex `\bnew\s+Function\s*\(` — `new Function("code")` is equivalent to eval but harder to grep for |
| `settimeout_setinterval_count` | Regex `\b(setTimeout\|setInterval)\s*\(` — when called with a string argument these execute code after a delay, commonly used to evade sandbox timeouts |
| `document_write_count` | Regex `\bdocument\.write(ln)?\s*\(` — injects HTML/script into the page, used by exploit kits |
| `innerhtml_count` | Regex `\.innerHTML\s*=` — DOM injection, common in XSS and skimmers |
| `unescape_count` | Regex `\bunescape\s*\(` — deprecated decoding function, almost exclusively found in malware |
| `fromcharcode_count` | Regex `String\.fromCharCode\s*\(` — converts integer arrays to strings, used to hide payloads from static string matching |
| `atob_count` | Regex `\batob\s*\(` — base64 decode, commonly wraps encoded payloads |
| `decodeuri_count` | Regex `\b(decodeURI\|decodeURIComponent)\s*\(` — URL decoding used to unpack percent-encoded payloads |
| `total_function_count` | AST: counts `FunctionDeclaration`, `FunctionExpression`, `ArrowFunctionExpression` nodes. Falls back to regex `\bfunction\s+\w+\s*\(\|\bfunction\s*\(` when pyjsparser is not installed |
| `total_variable_count` | AST: counts declarations inside `VariableDeclaration` nodes. Regex fallback: `\b(var\|let\|const)\s+` |
| `max_nesting_depth` | AST: tracks depth through `BlockStatement` and function nodes. 0 when AST is unavailable. Deep nesting (>5) correlates with obfuscation wrappers |
| `avg_identifier_length` | AST: mean character length of all `Identifier` node names. Obfuscators like javascript-obfuscator produce 12 character names (`_0x4a2f`, `a`, `b`); clean code averages 610. Computed by pyjsparser when the source is ES5.1; on ES2015+ sources (destructuring, classes, optional chaining, etc.) pyjsparser fails parse and the value falls back to `idsLengthAvg` from `@nodesecure/js-x-ray`, which uses a modern parser. Equals `0.0` only when both paths are unavailable |
| `hex_string_count` | Count of `\xHH` escape sequences via regex `\\x[0-9a-fA-F]{2}`. High counts indicate hex-encoded string literals |
| `unicode_escape_count` | Count of `\uHHHH` escape sequences. Same reasoning as hex — used to hide readable strings |
| `long_string_count` | String literals longer than 256 chars inside quotes. Long strings often contain encoded payloads |
| `base64_string_count` | Sequences of 40+ base64 characters. Matches `[A-Za-z0-9+/]{40,}={0,2}` |
| `comment_ratio` | Ratio of characters inside `//` and `/* */` comments to total characters. Obfuscated code rarely has comments; a ratio near 0 combined with large file size is suspicious |
| `script_type` | First-match file-format classification (see *Script type values* below). Distinct from `detected_environment`, which classifies the runtime API surface — an HTA, for example, is `script_type=hta` *and* `detected_environment=wscript` |
| `detected_environment` | First-match runtime classification by API presence (see *Environment values* below) |

#### Script type values

Checked in this order; first match wins. The ordering encodes specificity — encoded JScript can only be `jse`, a WSF wrapper can only be `wsf`, etc.

| Value | Trigger |
|-------|---------|
| `jse` | Source starts with `#@~^` (JScript.Encode marker). Body is unanalysable until decoded |
| `wsf` | First 4KB contains `<job`/`<package` *and* `<script` — Windows Script File XML wrapper |
| `hta` | First 4KB contains `<hta:application` or the `application/hta` MIME hint — runs under mshta.exe |
| `embedded_html` | Starts with `<!`/`<html` or contains `<script` in first 2000 chars (generic HTML host) |
| `wscript` | Contains `WScript.` or `WSH.` (loose `.js` invoked via `wscript.exe` / `cscript.exe`) |
| `esm` | Line-anchored `import …from "…"` / bare side-effect `import "…"` / top-level `export …` |
| `node_module` | Contains `require(` or `module.exports` (CommonJS) |
| `standalone` | Fallback when nothing above matches |
| `unknown` | Empty source |

#### Environment values

Checked in this order; first match wins.

| Value | Trigger |
|-------|---------|
| `wscript` | `WScript.`, `WSH.`, `ActiveXObject`, `Scripting.FileSystemObject`, `WScript.Shell`, `ADODB.Stream` |
| `browser_extension` | `chrome.runtime`, `chrome.tabs`, `chrome.storage`, `chrome.webRequest`, `browser.runtime`, `browser.tabs` (MV2/MV3 extension APIs) |
| `service_worker` | `self.addEventListener('fetch'`, `self.importScripts`, `self.skipWaiting`, `caches.match`, `caches.open` (worker-only APIs not present in regular pages) |
| `deno` | `Deno.` (Deno runtime global) |
| `node` | `require(`, `module.exports`, `process.env`, `__dirname`, `__filename`, `Buffer.`, `child_process` |
| `browser` | `document.`, `window.`, `navigator.`, `localStorage`, `sessionStorage`, `XMLHttpRequest`, `addEventListener` |
| `unknown` | Fallback |

### Two-tier obfuscation verdict

The `is_likely_obfuscated` boolean is the answer to "should an analyst treat this file as obfuscated." It comes from two sources, in priority order:

1. **js-x-ray hit (authoritative).** When `@nodesecure/js-x-ray` recognises the obfuscator family, the verdict is `True` and `obfuscator_name` carries the family label. js-x-ray catches `jsfuck`, `obfuscator.io`, `morse`, `jjencode`, and `freejsobfuscator` by AST shape, which is far more precise than any heuristic.
2. **Heuristic with strong-signal corroboration.** When js-x-ray either didn't flag the sample or isn't installed, the heuristic decides: `obfuscation_score >= 40` AND at least one *strong* signal fired. Strong signals are unambiguous on their own; weak signals are commonly seen in legitimate code and only count toward the score, not toward the strong-signal gate. The strong-signal gate (not the score threshold) is what does the heavy lifting against false positives — a clean file with multiple weak ticks but no strong signal cannot be flagged regardless of the score.

The two-tier check is a deliberate response to the score-only threshold's failure mode: a non-obfuscated file with mid-band entropy, a single `eval`, and a handful of `\xHH` escapes used to clear `>= 40` and show up as `is_obfuscated: Yes` even though it was just legitimate code with one or two ambient indicators. With strong-signal corroboration, three weak ticks alone no longer cross the line.

### Obfuscation score breakdown

The score is a sum of weighted indicators, capped at 100:

| Indicator | Tier | Weight | Rationale |
|-----------|------|--------|-----------|
| Hex/unicode escape density > 5% of source | strong | +20 | Encoded payload — at this density the source is mostly escape sequences |
| Hex/unicode escape density > 1% | weak | +8 | Notable encoding but could also be a few hex literals in legitimate code |
| Avg identifier length < 2 chars | strong | +15 | Obfuscators shorten everything to single chars; clean code averages 6+ |
| Avg identifier length < 3 chars | weak | +6 | Slightly longer but still suspicious |
| Max line > 10K chars | strong | +15 | Single enormous line — hallmark of packer output |
| Max line > 5K chars | weak | +8 | Long single line |
| `text_entropy` > 5.0 | strong | +15 | Encoded payload range. The old 4.54.8 weak band caught jQuery and is dropped |
| Each `eval()` call (capped at +12) | weak | +4 each | One eval is normal in templating / AngularJS / polyfills; only piles of them count |
| `String.fromCharCode` present | weak | +6 | Common in legacy escapers but worth a tick |
| String concat density > 20 per 100 lines | weak | +8 | Excessive `"a" + "b" + "c"` rebuild of greppable strings |
| Comment ratio < 1% + few lines + size > 1 KB | weak | +5 | Minifier/packer tell |
| Non-ASCII codepoint density > 30% | strong | +20 | Unicode-codepoint payload (e.g. WSH droppers building a runtime string of >0x7f chars). Real-world JS averages <5% non-ASCII; >30% is almost always obfuscation. The strong-signal gate prevents the corner-case false-positive on heavy-localization files (which can cross 30% legitimately) — a localization file scoring only this signal can't reach the threshold |
| Non-ASCII codepoint density > 10% | weak | +8 | Notable non-ASCII presence — could be substantial i18n in legitimate code, or the start of a Unicode-codepoint obfuscation pattern |
| Line-uniqueness ratio < 10% (line_count > 100) | strong | +15 | Junk-padded bulk: thousands of duplicate lines burying the actual logic. Hand-written code has near-1 uniqueness even in repetitive sections (CSS-in-JS, fixture data, etc.) |
| Line-uniqueness ratio < 30% (line_count > 100) | weak | +6 | Significant repetition; could be a packer working from a small template, or padding warming up |

### Obfuscation techniques detected

Each technique is flagged when its threshold is exceeded. Density-based tags use the same bar as the score's strong-signal threshold so the displayed tags reflect what the score actually credited:

| Technique label | Detection rule |
|----------------|---------------|
| `eval_usage` | `eval(` present |
| `function_constructor` | Function-constructor invocation present (`new Function(...)`) |
| `hex_encoding` | More than 5 `\xHH` sequences AND density > 0.1% of source |
| `unicode_encoding` | More than 5 `\uHHHH` sequences AND density > 0.1% of source |
| `charcode_encoding` | More than 3 `String.fromCharCode(` calls |
| `string_concatenation` | More than 10 `"..." + "..."` patterns |
| `base64_decoding` | `atob(` present |
| `unescape_usage` | `unescape(` present |
| `array_function_calls` | Pattern `[0xNN](` or `[N](` — calling functions via array index lookup, typical of javascript-obfuscator output |
| `short_identifiers` | `0 < avg_identifier_length < 3.0` — identifiers averaging under 3 chars, typical of obfuscator.io's `_0xNNNN` renaming. Sourced from pyjsparser when the file parses as ES5.1, falling back to js-x-ray's `idsLengthAvg` on ES2015+ sources |
| `packed_single_line` | `max_line_length > 5000` — single enormous line, hallmark of packer/minifier output |
| `high_entropy` | `text_entropy > 5.0` — character distribution in encoded-payload range; distinct from `redb_basic_properties.file_entropy` (byte entropy) |
| `non_ascii_payload` | Non-ASCII codepoint density > 10%. Catches Unicode-codepoint stuffing (e.g. `this.x += "<U+1184><U+159b>..."` repeated thousands of times) — a pattern the per-escape `unicode_encoding` tag misses because the source contains the actual codepoints, not literal `\uHHHH` escape sequences |
| `repetitive_padding` | Line-uniqueness ratio < 30% with line_count > 100. Junk-filled bulk burying the actual payload; the line-count floor prevents false positives on tiny files that happen to repeat a few lines |

---

## JSSuspiciousAPIsExtractor

**Table:** `redb_js_suspicious_apis` (multi-row per sample, one row per detected API)

Reads `JSContext.scan` and emits one row per `js_patterns.PATTERNS` entry that matched the source. Findings are emitted in the canonical insertion order of `PATTERNS` (`code_execution` → `network` → `filesystem` → `process` → `registry` → `crypto_encoding` → `dom_manipulation`) so output ordering is deterministic. Each pattern matches a specific API call or object instantiation known to be used in malicious JavaScript.

### Categories and patterns

**code_execution** — APIs that execute arbitrary code:
`eval()`, `new Function()`, `execScript()`, `document.write()`, `.innerHTML =`, `.outerHTML =`, `.insertAdjacentHTML()`

**network** — APIs that make network requests:
`new XMLHttpRequest`, `fetch()`, `new WebSocket()`, `navigator.sendBeacon()`, `ActiveXObject("MSXML2.XMLHTTP")`, `require("http"/"https"/"net"/"dgram")`, `axios`

**filesystem** — APIs that access the filesystem:
`require("fs")`, `require("path")`, `Scripting.FileSystemObject`, `ADODB.Stream`, `Shell.Application`, `WScript.CreateObject`

**process** — APIs that spawn processes:
`require("child_process")`, `child_process.exec/spawn/execFile/fork`, `WScript.Shell`, `.Run()`, `.Exec()`, `ShellExecute`, `"powershell"`, `"cmd.exe"`, `require("os")`

**registry** — Windows registry access:
`.RegRead()`, `.RegWrite()`, `.RegDelete()`, `StdRegProv`

**crypto_encoding** — Encoding/decoding/crypto operations:
`atob()`, `btoa()`, `String.fromCharCode()`, `unescape()`, `decodeURIComponent()`, `Buffer.from()`, `crypto.createCipher/Decipher/Hash/Hmac`

**dom_manipulation** — DOM operations typical of skimmers/injectors:
`document.forms`, `document.cookie`, `querySelector` targeting password/credit/card/cvv/ssn inputs, `addEventListener("submit")`, `createElement("script"/"iframe")`, `.src = "http://..."`

### Output fields

| Field | Description |
|-------|-------------|
| `api_name` | Human-readable name of the matched API |
| `api_category` | One of the 7 categories above |
| `call_count` | Number of lines where the pattern matched |
| `line_numbers` | Array of line numbers (1-indexed) where the API was found |
| `context_snippet` | Up to 3 truncated source lines where the API appears (max 200 chars each, joined by ` \| `) |

---

## JSStringsExtractor

**Table:** `code_binja_strings_raw` (shared with binary string extraction)

Finds encoded strings in JS source, decodes them, and writes both the decoded value and the original encoded form to the same table used by DecompileBinja and DecompileAPK. This means `string:"powershell"` queries return results from all formats.

The 6 detection regexes live in `js_patterns.STRING_PATTERNS` (compiled once at module load); the per-match concat tokeniser is also compiled once. Line numbers for each finding (`string_offset`) are looked up in O(log L) via `bisect` against a newline-offset table built once per `extract()` call — the historical O(N·M) `source[:start].count('\n')` pass is gone.

### Decoding methods

Scope: only *hidden* strings — values whose decoded form is not visible to a substring search over the raw text. Plain long literals are not extracted here because they're already preserved in `code_text_content.text_raw` and scraped by the IOC pipeline over the same `text_raw` / `text_normalized` surfaces (column names match the `redb_iocs.source_type` enum values, so a join across the two tables doesn't have to translate names).

| `string_encoding` value | What it decodes | Example input | Example output |
|------------------------|----------------|---------------|----------------|
| `hex` | `\xHH` escape sequences (4+ consecutive) | `\x68\x74\x74\x70` | `http` |
| `unicode` | `\uHHHH` escape sequences (3+ consecutive) | `WScript` | `WScript` |
| `charcode` | `String.fromCharCode(N, N, ...)` calls | `String.fromCharCode(112, 111, 119)` | `pow` |
| `base64` | Base64 strings (40+ chars) inside quotes. Only kept if decoding produces >80% printable UTF-8 text | `"cG93ZXJzaGVsbA=="` | `powershell` |
| `concat` | Reassembled `"a" + "b" + "c"` concatenation (3+ parts) | `"ht" + "tp" + "://" + "evil" + ".com"` | `http://evil.com` |

### Field mapping to shared table

| Shared column | JS value |
|--------------|----------|
| `string` | Decoded/reconstructed string value |
| `string_raw` | Original encoded form as it appeared in source |
| `string_encoding` | One of: hex, unicode, charcode, base64, concat, plaintext |
| `string_offset` | Line number in the JS source file (1-indexed) |
| `string_length` | Length of the decoded string |
| `string_raw_length` | Length of the original encoded form |
| `string_entropy` | Shannon entropy of the decoded string |

---

## JSDeobfuscationExtractor

**Table:** `redb_js_deobfuscation` (1 row per sample)

Attempts to deobfuscate the JS source using external tools, then compares pre/post metrics to measure how much was hidden.

### Tool chain

1. **Primary: webcrack** (or any tool at `JS_DEOBFUSCATOR_PATH` env var). Run as a subprocess with `JS_DEOBFUSCATE_TIMEOUT` seconds timeout (default 60). The tool receives the source file path and its stdout is captured as the deobfuscated output. Process group management handles cleanup on timeout (SIGTERM then SIGKILL).

2. **Fallback: jsbeautifier** (Python library). Used when the primary tool is not installed. Normalizes formatting (indentation, line breaks) but does not perform semantic deobfuscation. Still useful because it makes minified code readable and can reveal strings that were hidden by formatting tricks.

### Output fields

| Field | Description |
|-------|-------------|
| `deobfuscator_used` | Name of the tool that produced the output (`webcrack`, `jsbeautifier`, etc.) |
| `deobfuscation_successful` | 1 if the tool produced non-empty output |
| `original_size` | Character count of the input source |
| `deobfuscated_size` | Character count of the deobfuscated output |
| `size_change_ratio` | `deobfuscated_size / original_size`. Values significantly different from 1.0 indicate the tool transformed the code |
| `original_entropy` | Shannon entropy of the input. Reused from `JSContext.text_entropy` so the same Shannon computation is not redone here |
| `deobfuscated_entropy` | Shannon entropy of the output. A drop in entropy after deobfuscation suggests encoded content was unpacked into readable text |
| `new_strings_found` | Count of string literals (4+ chars) present in the deobfuscated output but absent in the original. These are strings that were hidden by the obfuscation |
| `new_apis_found` | Count of `PATTERNS` entries that matched the deobfuscated output but did not match the original. The original-side pattern set is read from `JSContext.scan` (already computed once for this sample); only the deobfuscated text triggers an additional `scan_source()` pass since that text is unique to this extractor. Reveals API calls that were concealed |
| `deobfuscated_sha256` | SHA-256 of the deobfuscated output, for deduplication and cross-referencing |

---

## JSContentExtractor

**Table:** `code_text_content` (1 row per sample, shared with future text-content extractors)

Persists the actual text of the sample (raw + normalised) so analysts can re-query the source content directly and so future improvements to IOC extraction or pattern matching can be re-applied without re-running the deobfuscator. The same table is intended to host any text-based artefact in the future (PowerShell, Python, plain text, email bodies, extracted PDF/Office text); the `content_type` column carries the magika label so callers can filter without joining other tables.

The deobfuscation pass is computed once per sample and shared with `JSDeobfuscationExtractor` (which writes the metrics row), so this extractor adds no extra subprocess cost.

| Field | Description |
|-------|-------------|
| `content_type` | The magika label for the artefact (`"javascript"` for JS samples). Lets a single table hold heterogeneous text content without per-format tables |
| `text_raw` | The decoded source as it sits on disk. Column name matches the `redb_iocs.source_type='text_raw'` enum value, so an analyst tracing an IOC back to its surface lands on the column with the same identifier |
| `text_normalized` | Output of the deobfuscator (or jsbeautifier fallback). `NULL` when neither produced output, distinguishing "we tried and got nothing" from a successful normalisation. Same naming alignment with `redb_iocs.source_type='text_normalized'` |
| `normalizer_used` | Name of the tool that produced the normalised text (`"webcrack"`, `"jsbeautifier"`, etc.). `NULL` when `text_normalized` is `NULL` |

Both `text_raw` and `text_normalized` are stored with ClickHouse `CODEC(ZSTD(3))` to keep storage cost reasonable across millions of samples.

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## IOC extraction

**Table:** `redb_iocs` (shared with all formats)

JavaScript IOC extraction uses the same `IOCExtractorFromResults` class as DecompileBinja and DecompileAPK. JS samples get the same 22 IOC types (IPv4, IPv6, FQDN, URL, email, crypto addresses, CVEs, file paths, registry keys, etc.) with defanging support and IANA TLD validation. Called automatically in `workers.py` after the JS-specific extractors complete.

### Windows paths & registry keys in source-code form

`WINDOWS_PATH_PATTERN` and `REGISTRY_KEY_PATTERN` accept both the runtime form (`C:\Windows\Temp`, `HKLM\SYSTEM\...`) and the source-escaped form (`C:\\Windows\\Temp`, `HKLM\\SYSTEM\\...`) that appears inside JS / JSON / PowerShell string literals. Doubled backslashes are normalised to single before storage so an analyst querying for `C:\Users\Public` sees both forms collapsed to one IOC. Wildcard segments (e.g. `C:\Users\*\AppData\Local\Temp`) are preserved.

Registry hives recognised: `HKLM`, `HKCU`, `HKCR`, `HKU`, `HKCC`, `HKPD`, `HKEY_LOCAL_MACHINE`, `HKEY_CURRENT_USER`, `HKEY_CLASSES_ROOT`, `HKEY_USERS`, `HKEY_CURRENT_CONFIG`, `HKEY_PERFORMANCE_DATA`. A bare hive mention with no path component does not match (avoids prose false positives).

Three surfaces are scraped for every JS sample, each tagged with its own `redb_iocs.source_type` value so analysts can tell where an IOC was first visible:

| `source_type` | Surface | Catches |
|---|---|---|
| `text_raw` | The decoded source as it sits on disk | URLs, IPs, emails, etc. that aren't hidden by encoding or wrapping |
| `text_normalized` | The deobfuscated/beautified form (only added when it differs from raw) | IOCs unwrapped by webcrack from `eval(atob(...))` payloads, identifiers exposed by jsbeautifier on minified code |
| `string` | The decoded strings produced by `JSStringsExtractor` (hex/unicode/charcode/base64/concat unpacked into plaintext) | URLs and FQDNs hidden behind `String.fromCharCode(...)`, base64-wrapped tokens, concatenated `"a" + "b" + ...` chains, etc. |

The `text_raw` and `text_normalized` values are universal across text-based artefacts — the same two `SourceType` values are intended to host PowerShell, Python, email body, and extracted PDF/Office text in the future.