Xiangyan Zeng

28 papers Journal 24Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Inf. Sci.
Feifei Huang, Xiangyan Zeng, Shuli Yan
2026 J jnl
Grey Syst. Theory Appl.
Feifei Huang, Xiangyan Zeng, Shuli Yan, Fangli He, Houdong Kuang
2025 J jnl
Grey Syst. Theory Appl.
Zhenxiu Cao, Xiangyan Zeng, Shuli Yan, Lihua Ning
2025 J jnl
Grey Syst. Theory Appl.
Shuli Yan, Xiaoyu Gong, Xiangyan Zeng
2025 J jnl
SoftwareX
Dawit Aberra, Xiangyan Zeng, Chunhua Dong Mahon, Sanjeev Arora
2024 J jnl
Grey Syst. Theory Appl.
Haoze Cang, Xiangyan Zeng, Shuli Yan
2024 J jnl
Expert Syst. Appl.
Haoze Cang, Xiangyan Zeng, Shuli Yan
2023 J jnl
Soft Comput.
Sixuan Wu, Xiangyan Zeng, Chunming Li, Haoze Cang, Qiancheng Tan, Dewei Xu
2023 J jnl
Inf. Fusion
Shuli Yan, Qi Su, Zaiwu Gong, Xiangyan Zeng, Enrique Herrera-Viedma
2022 J jnl
Expert Syst. Appl.
Shuli Yan, Qi Su, Zaiwu Gong, Xiangyan Zeng
2022 J jnl
Grey Syst. Theory Appl.
Shuli Yan, Xiangyan Zeng, Pingping Xiong, Na Zhang
2022 J jnl
Expert Syst. Appl.
Qi Su, Shuli Yan, Lifeng Wu, Xiangyan Zeng
2022 J jnl
Int. J. Comput. Sci. Math.
Hong Zhao, Lupeng Yue, Weijie Wang, Xiangyan Zeng
2021 J jnl
Multim. Tools Appl.
Zhuo Cheng, Hongjian Li, Xiaolin Duan, Xiangyan Zeng, Mingxuan He, Hao Luo
2021 J jnl
Sci. Program.
Quan Yuan, Zhenyun Peng, Zhencheng Chen, Yanke Guo, Bin Yang, Xiangyan Zeng
2021 J jnl
J. Web Eng.
Hong Zhao, Lupeng Yue, Weijie Wang, Xiangyan Zeng
2021 conf
ACM Southeast Conference
Hong Tran, Chunhua Dong, Masoud Naghedolfeizi, Xiangyan Zeng
2020 J jnl
Multim. Tools Appl.
Zhuo Cheng, Hongjian Li, Xiangyan Zeng, Meiqi Wang, Xiaolin Duan
2019 J jnl
J. Intell. Fuzzy Syst.
Shuli Yan, Sifeng Liu, Xiangyan Zeng
2019 J jnl
J. Comput. Networks Commun.
Hong Zhao, Zhaobin Chang, Guangbin Bao, Xiangyan Zeng
2019 J jnl
IEEE Access
Hong Zhao, Zhaobin Chang, Weijie Wang, Xiangyan Zeng
2019 J jnl
J. Comput. Networks Commun.
Hong Zhao, Chunning Hou, Hala Alrobassy, Xiangyan Zeng
2019 J jnl
Remote. Sens.
Chunhua Dong, Masoud Naghedolfeizi, Dawit Aberra, Xiangyan Zeng
2018 conf
ACM Southeast Regional Conference
Kaleb Smith, Chunhua Dong, Masoud Naghedolfeizi, Xiangyan Zeng
2013 conf
IFSA/NAFIPS
Xiangyan Zeng, Lan Shu
2012 J jnl
J. Next Gener. Inf. Technol.
Xiangyan Zeng, Yenwei Chen, Owen Hughes, Henning Stahlberg
2011 conf
ACM Southeast Regional Conference
Xiangyan Zeng, James Ervin Glover, Owen Hughes, Henning Stahlberg
2006 J jnl
J. Comput. Aided Mol. Des.
Ludovic Renault, Hui-Ting Chou, Po-Lin Chiu, Rena M. Hill, Xiangyan Zeng, Bryant Gipson, Zi Yan Zhang, An-Chi Chen, Vinzenz Unger, Henning Stahlberg
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,
        )