Chang-you Xing

43 papers B 3C 2Journal 26Unranked 12
YearRankTypeTitle / Venue / Authors
2023 J jnl
J. Inf. Secur. Appl.
Yuan He, Chang-you Xing, Ke Ding, Guomin Zhang, Lihua Song
2023 J jnl
Comput. Commun.
Yaqun Liu, Jun Xie, Chang-you Xing, Shengxu Xie, Baoan Ni
2023 J jnl
Comput. Secur.
Jinyin Chen, Shulong Hu, Haibin Zheng, Chang-you Xing, Guomin Zhang
2023 J jnl
Comput. Networks
Yaqun Liu, Jun Xie, Chang-you Xing, Shengxu Xie
2022 J jnl
IEEE Wirel. Commun. Lett.
Yaqun Liu, Jun Xie, Chang-you Xing, Shengxu Xie
2022 J jnl
Comput. Networks
Shengxu Xie, Guyu Hu, Chang-you Xing, Jiachen Zu, Yaqun Liu
2022 J jnl
CoRR
Jinyin Chen, Shulong Hu, Haibin Zheng, Chang-you Xing, Guomin Zhang
2021 J jnl
Secur. Commun. Networks
Shengxu Xie, Chang-you Xing, Guomin Zhang, Jinlong Zhao
2021 J jnl
Comput. Networks
Lingfeng Cai, Xianglin Wei, Chang-you Xing, Xia Zou, Guomin Zhang, Xiulei Wang
2020 J jnl
J. Netw. Comput. Appl.
Ming Chen, Shunkang Zhang, Hai Deng, Bing Chen, Chang-you Xing, Bo Xu
2020 conf
SocialSec
Shengxu Xie, Chang-you Xing, Guomin Zhang, Xianglin Wei, Guyu Hu
2019 J jnl
Comput. Commun.
Dongyang Li, Chang-you Xing, Guomin Zhang, Huaping Cao, Bo Xu
2019 J jnl
Peer-to-Peer Netw. Appl.
Dongyang Li, Chang-you Xing, Ningyun Dai, Fei Dai, Guomin Zhang
2019 conf
ICBDS
Shengxu Xie, Chang-you Xing, Guomin Zhang, Jinlong Zhao
2018 J jnl
J. High Speed Networks
Chao Hu, Bo Liu, Chang-you Xing, Ke Ding, Bo Xu, Xianglin Wei, Xiaoming Zhang
2018 J jnl
Int. J. Robotics Autom.
Hui Hu, Bo Liu, Chao Hu, Ming Chen, Guang Cheng, Chang-you Xing
2017 conf
CBD
Dongyang Li, Ningyun Dai, Feng Li, Chang-you Xing, Fei Dai
2017 J jnl
Comput. Networks
Ming Chen, Ke Ding, Jie Hao, Chao Hu, Gaogang Xie, Chang-you Xing, Bing Chen
2017 conf
ICC
Bo Xu, Chao Hu, Bo Liu, Chang-you Xing, Dongyang Li
2016 J jnl
Frontiers Inf. Technol. Electron. Eng.
Bo Liu, Ming Chen, Bo Xu, Hui Hu, Chao Hu, Qingyun Zuo, Chang-you Xing
2016 J jnl
IEICE Trans. Inf. Syst.
Xiulei Wang, Ming Chen, Chang-you Xing, Tingting Zhang
2016 conf
ICC
Chao Hu, Bo Liu, Chang-you Xing, Zhenjun Yue, Lihua Song, Ming Chen
2016 J jnl
KSII Trans. Internet Inf. Syst.
Chang-you Xing, Ke Ding, Chao Hu, Ming Chen, Bo Xu
2016 J jnl
IEEE Commun. Lett.
Chang-you Xing, Ke Ding, Chao Hu, Ming Chen
2015 J jnl
Informatica (Slovenia)
Guomin Zhang, Chao Hu, Na Wang, Xianglin Wei, Chang-you Xing
2015 conf
FCST
Xiulei Wang, Ming Chen, Chang-you Xing
2014 J jnl
Comput. Commun.
Chao Hu, Ming Chen, Chang-you Xing, Guomin Zhang
2014 conf
3PGCIC
Guomin Zhang, Chao Hu, Na Wang, Xianglin Wei, Chang-you Xing
2014 J jnl
Int. J. Mob. Comput. Multim. Commun.
Guomin Zhang, Zhanfeng Wang, Rui Wang, Na Wang, Chang-you Xing
2013 conf
CBD
Ming Chen, Xi Weng, Xiulei Wang, Chang-you Xing, Guomin Zhang
2013 J jnl
KSII Trans. Internet Inf. Syst.
Chang-you Xing, Ming Chen, Chao Hu
2013 J jnl
J. Netw. Comput. Appl.
Zhanfeng Wang, Ming Chen, Chang-you Xing, Jing Feng, Xianglin Wei, Huali Bai
2013 J jnl
Comput. Networks
Chao Hu, Ming Chen, Chang-you Xing
2012 J jnl
Peer-to-Peer Netw. Appl.
Chao Hu, Ming Chen, Chang-you Xing, Bo Xu
2011 B conf
IWQoS
Lidong Yu, Chang-you Xing, Huali Bai, Ming Chen, Mingwei Xu
2011 conf
ICCSA (5)
Lidong Yu, Ming Chen, Chang-you Xing
2010 C conf
NPC
Chang-you Xing, Li Yang, Ming Chen
2009 conf
CNSR
Chang-you Xing, Ming Chen
2009 B conf
GLOBECOM
Chang-you Xing, Ming Chen, Li Yang
2009 conf
ACIS-ICIS
Chang-you Xing, Ming Chen
2008 B conf
GLOBECOM
Chang-you Xing, Ming Chen
2008 conf
ICNSC
Chang-you Xing, Ming Chen
2007 C conf
NPC
Chang-you Xing, Ming Chen
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,
        )