Osama Abdulaziz Alamri

15 papers Journal 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Axioms
Hamed Salemian, Eisa Mahmoudi, Osama Abdulaziz Alamri
2025 J jnl
Commun. Stat. Simul. Comput.
Muhammad Nouman Qureshi, Muhammad Umair Tariq, Osama Abdulaziz Alamri, Muhammad Hanif
2024 J jnl
Int. J. Wavelets Multiresolution Inf. Process.
Mohammad Younus Bhat, Osama Abdulaziz Alamri, Aamir Hamid Dar
2024 J jnl
Axioms
Nuran Medhat Hassan, Osama Abdulaziz Alamri
2024 J jnl
Syst.
Marwan H. Alhelali, Osama Abdulaziz Alamri, Alanazi Talal Abdulrahman, Mohammed Ahmed Alomair, Basim S. O. Alsaedi
2024 J jnl
Symmetry
Sajad A. Sheikh, Mohammad Ibrahim Mir, Osama Abdulaziz Alamri, Javid Gani Dar
2024 J jnl
Axioms
Fatehi Yahya Eissa, Chhaya Dhanraj Sonar, Osama Abdulaziz Alamri, Ahlam H. Tolba
2023 J jnl
Axioms
Osama Abdulaziz Alamri, Mahesh Kumar Jayaswal, Mandeep Mittal
2023 J jnl
Axioms
Osama Abdulaziz Alamri
2022 J jnl
Big Data Cogn. Comput.
Ebrahem A. Algehyne, Muhammad Lawan Jibril, Naseh A. Algehainy, Osama Abdulaziz Alamri, Abdullah K. Alzahrani
2021 J jnl
Complex.
Xiaofeng Liu, Zubair Ahmad, Saima K. Khosa, Mohammed Yusuf, Osama Abdulaziz Alamri, Walid Emam
2021 J jnl
Comput. Intell. Neurosci.
Basim S. O. Alsaedi, Mahmoud M. Abd El-Raouf, Eslam H. Hafez, Zahra Almaspoor, Osama Abdulaziz Alamri, Kamel Atallah Alanazi, Saima K. Khosa
2021 J jnl
Comput. Intell. Neurosci.
Osama Abdulaziz Alamri, Mahmoud M. Abd El-Raouf, Eman Ahmed Ismail, Zahra Almaspoor, Basim S. O. Alsaedi, Saima K. Khosa, Mohammed Yusuf
2021 J jnl
Complex.
Jin Zhao, Zubair Ahmad, Saima K. Khosa, Mohammed Yusuf, Osama Abdulaziz Alamri, Mohamed Said Mohamed
2021 J jnl
Comput. Intell. Neurosci.
Jia Cong, Zubair Ahmad, Basim S. O. Alsaedi, Osama Abdulaziz Alamri, Ibrahim Alkhairy, Hassan Alsuhabi
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)));