Mamdouh Alenezi

54 papers A 2Journal 42Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Mamdouh Alenezi
2026 J jnl
CoRR
Mamdouh Alenezi
2024 J jnl
IEEE Access
Mohammed Zagane, Mamdouh Alenezi
2024 conf
ICSCA
Mohammed Akour, Mamdouh Alenezi, Osama Al Qasem
2024 J jnl
Int. J. e Collab.
Hanwei Fan, Mamdouh Alenezi
2024 J jnl
Int. J. Cloud Appl. Comput.
Suliman Mohamed Fati, Mamdouh Alenezi
2023 J jnl
CoRR
Mamdouh Alenezi
2022 conf
IWBBIO (1)
Mamdouh Alenezi, Abdelouahed Khalil, Tamás Fülöp, Éric Turcotte, M'hamed Bentourkia
2022 J jnl
CoRR
Mamdouh Alenezi, Mohammad Zarour, Mohammad Akour
2022 J jnl
Axioms
Noor Mohammed Noorani, Abu Taha Zamani, Mamdouh Alenezi, Mohammad Shameem, Priyanka Singh
2022 J jnl
CoRR
Mamdouh Alenezi
2022 J jnl
Int. J. Softw. Innov.
Mohammed Zagane, Mamdouh Alenezi, Mustapha Kamel Abdi
2022 J jnl
CoRR
Mamdouh Alenezi
2022 J jnl
Int. J. Eng. Pedagog.
Mamdouh Alenezi, Mohammad Akour
2022 J jnl
J. King Saud Univ. Comput. Inf. Sci.
Alka Agrawal, Mamdouh Alenezi, Suhel Ahmad Khan, Rajeev Kumar, Raees Ahmad Khan
2022 J jnl
J. King Saud Univ. Comput. Inf. Sci.
Md Tarique Jamal Ansari, Dhirendra Pandey, Mamdouh Alenezi
2022 J jnl
CoRR
Mamdouh Alenezi
2022 J jnl
Softw. Pract. Exp.
Mamdouh Alenezi, Hamid Abdul Basit, Maham Anwar Beg, Muhammad Saad Shaukat
2022 J jnl
CoRR
Mamdouh Alenezi
2021 J jnl
IET Inf. Secur.
Khalid T. Al-Sarayreh, Mamdouh Alenezi, Mohammad Zarour, Kenza Meridji
2021 J jnl
Inf.
Ali Al-Laith, Mamdouh Alenezi
2021 J jnl
Comput. Syst. Sci. Eng.
Mamdouh Alenezi
2020 A conf
EASE
Mamdouh Alenezi, Hamid Abdul Basit, Faraz Idris Khan, Maham Anwar Beg
2020 J jnl
Int. J. Softw. Innov.
Mohammed Zagane, Mustapha Kamel Abdi, Mamdouh Alenezi
2020 J jnl
Symmetry
Alka Agrawal, Mamdouh Alenezi, Rajeev Kumar, Raees Ahmad Khan
2020 J jnl
IEEE Access
Mohammed Zagane, Mustapha Kamel Abdi, Mamdouh Alenezi
2020 J jnl
Symmetry
Suhel Ahmad Khan, Mamdouh Alenezi, Alka Agrawal, Rajeev Kumar, Raees Ahmad Khan
2020 J jnl
IEEE Access
Mamdouh Alenezi, Alka Agrawal, Rajeev Kumar, Raees Ahmad Khan
2020 J jnl
IEEE Access
Mohammad Zarour, Md Tarique Jamal Ansari, Mamdouh Alenezi, Amal Krishna Sarkar, Mohd Faizan, Alka Agrawal, Rajeev Kumar, Raees Ahmad Khan
2020 conf
ESSE
Wajdi Aljedaani, Yasir Javed, Mamdouh Alenezi
2020 J jnl
CoRR
Mamdouh Alenezi, Mohammad Zarour
2020 conf
ICBDE
Wajdi Aljedaani, Yasir Javed, Mamdouh Alenezi
2020 J jnl
IEEE Access
Joseph Henry Anajemba, Tang Yue, Celestine Iwendi, Mamdouh Alenezi, Mohit Mittal
2020 conf
INTAP
Yasir Javed, Qasim Ali Arain, Mamdouh Alenezi
2020 A conf
EASE
Mohammad Zarour, Mamdouh Alenezi, Khalid Alsarayrah
2020 J jnl
IEEE Access
Osama Al Qasem, Mohammed Akour, Mamdouh Alenezi
2020 J jnl
Sensors
Celestine Iwendi, Suleman Khan, Joseph Henry Anajemba, Mohit Mittal, Mamdouh Alenezi, Mamoun Alazab
2019 J jnl
Int. J. Inf. Secur. Priv.
Mamdouh Alenezi, Muhammad Usama, Khaled Mohamad Almustafa, Waheed Iqbal, Muhammad Ali Raza, Tanveer Khan
2019 J jnl
Int. J. Comput. Intell. Syst.
Rajeev Kumar, Mohammad Zarour, Mamdouh Alenezi, Alka Agrawal, Raees Ahmad Khan
2019 J jnl
IEEE Access
Alka Agrawal, Mamdouh Alenezi, Rajeev Kumar, Raees Ahmad Khan
2019 J jnl
CoRR
Md Tarique Jamal Ansari, Dhirendra Pandey, Mamdouh Alenezi
2019 J jnl
PeerJ Comput. Sci.
Alka Agrawal, Mohammad Zarour, Mamdouh Alenezi, Rajeev Kumar, Raees Ahmad Khan
2018 J jnl
J. Inf. Sci. Eng.
Iman M. Almomani, Mamdouh Alenezi
2018 J jnl
Int. J. Softw. Innov.
Layla Mohammed Alrawais, Mamdouh Alenezi, Mohammad Akour
2018 J jnl
CoRR
Mamdouh Alenezi, Shadi Banitaan, Mohammad Zarour
2017 conf
EUSPN/ICTH
Khaled Mohamad Almustafa, Mamdouh Alenezi
2016 J jnl
J. Univers. Comput. Sci.
Ibrahim Abunadi, Mamdouh Alenezi
2015 J jnl
Int. J. Cloud Appl. Comput.
Mamdouh Alenezi, Fakhry M. Khellah
2015 J jnl
CoRR
Mamdouh Alenezi, Ibrahim Abunadi
2013 conf
ICMLA (2)
Mamdouh Alenezi, Shadi Banitaan
2013 conf
ICMLA (2)
Shadi Banitaan, Mamdouh Alenezi
2013 J jnl
J. Softw.
Mamdouh Alenezi, Kenneth Magel, Shadi Banitaan
2013 conf
ICCIT
Shadi Banitaan, Mamdouh Alenezi
2013 conf
ITNG
Shadi Banitaan, Mamdouh Alenezi, Kendall E. Nygard, Kenneth Magel
redb/extractors/js_extractors/js_context.py
← Index redb/extractors/js_extractors/js_context.py python
"""Per-sample shared state for the JavaScript extractor pipeline.

A `JSContext` is built exactly once per JS sample (in `workers.py`) and threaded
into every extractor that runs against that sample. It owns the disk read, the
decoded source text, the line-split cache, the Shannon text-entropy figure, the
shared `scan_source()` results, and the pyjsparser AST. Each of those is
computed lazily through `cached_property` so an extractor that doesn't need a
particular artefact does not pay for it.

Without this object, every JS extractor instance redoes the same disk read,
decode, scan, and (for any consumer) AST parse. With it, every extractor
shares one set of results.

`JSExtractor.__init__` accepts the context via a `context=` kwarg; if absent
(e.g. unit tests instantiating an extractor directly with `source=...`) it
builds a fresh context from the constructor arguments. Either path produces a
fully-populated context, so extractor code can always rely on
`self._context.scan` / `self._context.ast` / etc.
"""

from __future__ import annotations

import math
from collections import Counter
from dataclasses import dataclass
from functools import cached_property
from typing import Any, Dict, List, Optional

import chardet

from redb.extractors.js_extractors.js_patterns import scan_source


def decode_source(raw_bytes: bytes) -> str:
    """Decode raw JS bytes to text, honouring BOMs and falling back to chardet.

    Mirrors the historical `JSExtractor._decode_source` logic so existing tests
    continue to round-trip identically.
    """
    if not raw_bytes:
        return ""

    if raw_bytes[:3] == b"\xef\xbb\xbf":
        return raw_bytes[3:].decode("utf-8", errors="replace")
    if raw_bytes[:2] in (b"\xff\xfe", b"\xfe\xff"):
        return raw_bytes.decode("utf-16", errors="replace")

    try:
        return raw_bytes.decode("utf-8")
    except UnicodeDecodeError:
        pass

    try:
        detected = chardet.detect(raw_bytes)
        if detected and detected.get("encoding"):
            return raw_bytes.decode(detected["encoding"], errors="replace")
    except Exception:
        pass

    return raw_bytes.decode("latin-1", errors="replace")


def _text_entropy(text: str) -> float:
    """Shannon entropy of the character distribution of `text`, rounded to 4dp."""
    if not text:
        return 0.0
    counter = Counter(text)
    length = len(text)
    entropy = 0.0
    for count in counter.values():
        p = count / length
        if p > 0:
            entropy -= p * math.log2(p)
    return round(entropy, 4)


@dataclass
class JSContext:
    """Shared raw materials for one JS sample, consumed by every JS extractor.

    Cheap attributes (raw_bytes, source) are populated eagerly by the factory.
    Expensive ones (scan, ast) are cached_property — computed on first access
    and reused across every extractor that holds the same context.

    `content_type` is the magika label (e.g. `"javascript"`) carried alongside
    the source so the new code_text_content writer (and any future generic
    text-content writer) can record it without re-running magika. Defaults to
    `"javascript"` because by construction this context type is JS-specific;
    workers.py supplies the actual magika value when it builds the context.
    """

    filepath: str
    raw_bytes: bytes
    source: str
    log: Any = None
    content_type: str = "javascript"
    # Populated by JSStringsExtractor.extract() (the decoded/reconstructed
    # strings — hex/unicode/charcode/base64/concat unpacked into plaintext).
    # Read post-loop by the IOC plumbing in workers.py so any IOCs hidden
    # behind those encodings get scraped from the decoded form. Stays None
    # if JSStringsExtractor didn't run for this sample.
    decoded_strings: Optional[list] = None

    @cached_property
    def lines(self) -> List[str]:
        return self.source.splitlines() if self.source else []

    @cached_property
    def text_entropy(self) -> float:
        return _text_entropy(self.source)

    @cached_property
    def scan(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over self.source."""
        return scan_source(self.source) if self.source else {}

    @cached_property
    def ast(self) -> Optional[Any]:
        """Lazy pyjsparser AST. Returns None if the parser is missing or fails.

        Extractors should treat None AST as "fall back to regex" — every
        AST-consuming extractor already handles that path.
        """
        if not self.source:
            return None
        try:
            import pyjsparser
            return pyjsparser.parse(self.source)
        except ImportError:
            if self.log is not None:
                self.log.debug("pyjsparser not installed, AST analysis skipped")
        except Exception as e:
            if self.log is not None:
                self.log.warning(f"AST parsing failed for {self.filepath}: {e}")
        return None

    @cached_property
    def deobfuscated(self) -> "tuple[Optional[str], Optional[str]]":
        """Run the configured JS deobfuscator (with jsbeautifier fallback) once
        per sample and cache the result. Returns `(text, normalizer_used)` or
        `(None, None)` if neither path produced output.

        Computed lazily on first access — samples whose pipeline never reads
        this don't pay the subprocess cost.
        """
        from redb.extractors.js_extractors.js_deobfuscator import deobfuscate
        return deobfuscate(self.source, self.log)

    @cached_property
    def scan_deobfuscated(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over the deobfuscated
        text, keyed by PATTERNS only (FEATURE_PATTERNS are not consulted by
        the dual-pass consumers). Empty dict when there is no deobfuscated
        text or it equals the raw source.

        Two extractors consume the post-deobf API surface:
        `JSSuspiciousAPIsExtractor` (for revealed_by_deobf rows) and
        `JSDeobfuscationExtractor` (for the new_apis_found diff). Caching here
        means we scan the deobfuscated text once instead of twice per sample.
        """
        from redb.extractors.js_extractors.js_patterns import PATTERNS
        deobf_text, _ = self.deobfuscated
        if not deobf_text or deobf_text == self.source:
            return {}
        return scan_source(deobf_text, patterns=(PATTERNS,))

    @cached_property
    def xray(self):
        """Run @nodesecure/js-x-ray once per sample and cache the result.

        Returns an `XRayResult` (always — the function collapses every failure
        path to an empty result so callers don't have to special-case missing
        Node, missing package, timeouts, or parse errors). The
        `JSFeaturesExtractor` reads it for the obfuscator family name and for
        corroborating warning kinds; the heuristic falls back cleanly when
        `xray.obfuscator is None`.
        """
        from redb.extractors.js_extractors.js_xray import run
        return run(self.source, self.log)

    @classmethod
    def from_path(
        cls,
        filepath: str,
        log: Any = None,
        source: Optional[str] = None,
        raw_bytes: Optional[bytes] = None,
        content_type: str = "javascript",
    ) -> "JSContext":
        """Build a context from disk. `raw_bytes` and `source` are optional
        overrides — useful when the caller has already read or decoded the file.
        `content_type` is the magika label workers.py dispatched on; it lands
        on the context for the code_text_content writer to record.
        """
        if raw_bytes is None:
            with open(filepath, "rb") as f:
                raw_bytes = f.read()
        if source is None:
            source = decode_source(raw_bytes)
        return cls(
            filepath=filepath,
            raw_bytes=raw_bytes,
            source=source,
            log=log,
            content_type=content_type,
        )