Xiaojun Ye

24 papers A* 1B 1C 1Misc 1Journal 9Unranked 11
YearRankTypeTitle / Venue / Authors
2025 conf
KDD (2)
Zixuan Gu, Qiufeng Fan, Long Sun, Yang Liu, Xiaojun Ye
2025 J jnl
CoRR
Zixuan Gu, Qiufeng Fan, Long Sun, Yang Liu, Xiaojun Ye
2023 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Jing Yu, Shukai Duan, Xiaojun Ye
2022 J jnl
IEEE Trans. Serv. Comput.
Jisheng Pei, Lijie Wen, Xiaojun Ye, Akhil Kumar
2022 J jnl
IEEE Trans. Intell. Transp. Syst.
Jing Yu, Xiaojun Ye, Qiang Tu
2021 J jnl
IEEE Trans. Serv. Comput.
Jisheng Pei, Lijie Wen, Hedong Yang, Jianmin Wang, Xiaojun Ye
2021 J jnl
IEEE Trans. Knowl. Data Eng.
Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu
2016 J jnl
Concurr. Comput. Pract. Exp.
Naiqiao Du, Xiaojun Ye, Jianmin Wang
2015 conf
Internetware
Lin Liu, Jianmin Wang, Xiaojun Ye, Hongji Yang
2015 conf
COMPSAC Workshops
Letong Feng, Yanqing Li, Lin Liu, Xiaojun Ye, Jianmin Wang, Zhanqiang Cao, Xin Peng
2014 J jnl
Inf. Syst. Frontiers
Naiqiao Du, Xiaojun Ye, Jianmin Wang
2014 J jnl
Sci. China Inf. Sci.
Lin Liu, Chen Yang, Jianmin Wang, Xiaojun Ye, Yingbo Liu, Hongji Yang, Xiaodong Liu
2013 conf
Internetware
Dan Chen, Xiaojun Ye, Jianmin Wang
2013 A* conf
CVPR
Zijia Lin, Guiguang Ding, Mingqing Hu, Jianmin Wang, Xiaojun Ye
2012 C conf
APSCC
Naiqiao Du, Xiaojun Ye, Jianmin Wang
2012 conf
Internetware
Tao Li, Xiaojun Ye, Jianmin Wang
2009 conf
Internetware
Naiqiao Du, Xiaojun Ye, Jianmin Wang
2009 conf
TPCTC
Xiaojun Ye, Jingmin Xie, Jianmin Wang, Hao Tang, Naiqiao Du
2009 conf
Internetware
Wenting Ma, Lin Liu, Xiaojun Ye, Jianmin Wang, John Mylopoulos
2009 conf
DBTest
Naiqiao Du, Xiaojun Ye, Jianmin Wang
2009 conf
Internetware
Zude Li, Xiaojun Ye, Jianmin Wang
2006 B conf
TrustBus
Guoqiang Zhan, Zude Li, Xiaojun Ye, Jianmin Wang
2006 conf
BNCOD
Guoqiang Zhan, Zude Li, Xiaojun Ye, Jianmin Wang
2005 Misc conf
WISA
Fei Guo, Jianmin Wang, Zhihao Zhang, Xiaojun Ye, Deyi Li
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)));