J. C. S. Kadupitiya

15 papers B 2Journal 9Unranked 4
YearRankTypeTitle / Venue / Authors
2022 J jnl
IEEE Trans. Parallel Distributed Syst.
J. C. S. Kadupitiya, Vikram Jadhao, Prateek Sharma
2022 J jnl
Mach. Learn. Sci. Technol.
J. C. S. Kadupitiya, Geoffrey C. Fox, Vikram Jadhao
2021 J jnl
CoRR
J. C. S. Kadupitiya, Nasim Anousheh, Vikram Jadhao
2020 conf
EduHPC@SC
Vikram Jadhao, J. C. S. Kadupitiya
2020 J jnl
CoRR
Vikram Jadhao, J. C. S. Kadupitiya
2020 J jnl
Int. J. High Perform. Comput. Appl.
J. C. S. Kadupitiya, Geoffrey C. Fox, Vikram Jadhao
2020 J jnl
J. Comput. Sci.
J. C. S. Kadupitiya, Fanbo Sun, Geoffrey C. Fox, Vikram Jadhao
2020 J jnl
CoRR
J. C. S. Kadupitiya, Geoffrey C. Fox, Vikram Jadhao
2019 conf
IPDPS Workshops
Geoffrey C. Fox, James A. Glazier, J. C. S. Kadupitiya, Vikram Jadhao, Minje Kim, Judy Qiu, James P. Sluka, Endre T. Somogyi, Madhav V. Marathe, Abhijin Adiga, Jiangzhuo Chen, Oliver Beckstein, Shantenu Jha
2019 J jnl
CoRR
Geoffrey C. Fox, James A. Glazier, J. C. S. Kadupitiya, Vikram Jadhao, Minje Kim, Judy Qiu, James P. Sluka, Endre T. Somogyi, Madhav V. Marathe, Abhijin Adiga, Jiangzhuo Chen, Oliver Beckstein, Shantenu Jha
2019 conf
ICCS (2)
J. C. S. Kadupitiya, Geoffrey C. Fox, Vikram Jadhao
2019 J jnl
CoRR
Prateek Sharma, J. C. S. Kadupitiya, Vikram Jadhao
2017 B conf
ICALT
J. C. S. Kadupitiya, Surangika Ranathunga, Gihan Dias
2017 B conf
ICALT
Diunuge Buddhika Wijesinghe, J. C. S. Kadupitiya, Surangika Ranathunga, Gihan Dias
2016 conf
WSSANLP@COLING
J. C. S. Kadupitiya, Surangika Ranathunga, Gihan Dias
redb/extractors/js_extractors/scripts/js-xray-runner.js
← Index redb/extractors/js_extractors/scripts/js-xray-runner.js javascript
#!/usr/bin/env node
// Bridge between the Python JS pipeline and @nodesecure/js-x-ray.
//
// Usage: node js-xray-runner.js <path-to-js-file>
//   stdout  one JSON object: {"obfuscator": <name|null>, "warnings": [...]}
//   stderr  human-readable error on failure
//   exit 0  analysis ran (the file may still be benign — see "obfuscator")
//   exit 1  the file could not be read or analysed
//
// Each warning is emitted as {kind, value} so the Python side can tag
// supporting signals (encoded-literal, short-identifiers, suspicious-literal,
// unsafe-stmt) without having to mirror js-x-ray's whole schema.
//
// js-x-ray ≥7 ships as an ES module, which CommonJS `require()` cannot load
// from a `.js` script — the dynamic `import()` below is what makes the
// bridge work without renaming the file to `.mjs` or adding `"type":
// "module"` to package.json (which would break tools that still
// `require()` from this directory).

const fs = require("fs");
const path = require("path");

function fail(msg) {
  process.stderr.write(msg + "\n");
  process.exit(1);
}

async function main() {
  const target = process.argv[2];
  if (!target) fail("usage: js-xray-runner.js <file>");

  let source;
  try {
    source = fs.readFileSync(target, "utf8");
  } catch (e) {
    fail(`read failed: ${e.message}`);
  }

  // The legacy `runASTAnalysis` function is deprecated (removed in v8); the
  // current API is the `AstAnalyser` class. Both produce a result with the
  // same `warnings` shape, so the rest of the bridge is unchanged.
  let AstAnalyser;
  try {
    ({ AstAnalyser } = await import("@nodesecure/js-x-ray"));
  } catch (e) {
    fail(`@nodesecure/js-x-ray not installed (run \`npm install\` in ${path.dirname(__filename)}): ${e.message}`);
  }

  // js-x-ray defaults to module-mode parsing, which rejects scripts that
  // (legally) use reserved words as identifiers, top-level `return`, etc.
  // A lot of real-world JS malware is script-style (WScript/HTA bodies,
  // pasted snippets) — retrying in script mode catches those without
  // pulling in a more lenient parser. Both attempts share the same
  // analyser; only the parse mode flips. If both fail, the original error
  // (module-mode) is reported because that's the more informative one for
  // genuinely broken sources.
  let result;
  const analyser = new AstAnalyser();
  let firstErr;
  try {
    result = await analyser.analyse(source, { module: true });
  } catch (e) {
    firstErr = e;
    try {
      result = await analyser.analyse(source, { module: false });
    } catch (e2) {
      fail(`js-x-ray analysis failed: ${firstErr.message}`);
    }
  }

  const warnings = (result.warnings || []).map((w) => ({
    kind: w.kind,
    value: w.value !== undefined ? w.value : null,
  }));

  // js-x-ray flags the obfuscator family in a warning whose kind is
  // "obfuscated-code" and whose value names the family (jsfuck, obfuscator.io,
  // freejsobfuscator, morse, jjencode, ...). Absent => not detected.
  const obfWarning = warnings.find((w) => w.kind === "obfuscated-code");
  const obfuscator = obfWarning ? obfWarning.value : null;

  // js-x-ray runs its own AST internally with a modern parser, so its
  // identifier-length average is the only path the Python pipeline has to
  // that signal on ES2015+ sources — pyjsparser is ES5.1-only and silently
  // drops to 0 the moment it hits destructuring, classes, optional chaining,
  // etc. Surfacing this lets the heuristic's `avg_identifier_length<2`
  // strong signal fire on real obfuscator.io output. `null` when the value
  // is missing or non-numeric (defensive — older js-x-ray builds may differ).
  const idsLengthAvg =
    typeof result.idsLengthAvg === "number" && !Number.isNaN(result.idsLengthAvg)
      ? result.idsLengthAvg
      : null;

  process.stdout.write(JSON.stringify({ obfuscator, warnings, idsLengthAvg }));
}

main().catch((e) => fail(e.message || String(e)));