Xiameng Qin

23 papers A* 4A 1B 1C 1Journal 14Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Jianjian Cao, Xiameng Qin, Sanyuan Zhao, Jianbing Shen
2025 A* conf
AAAI
Mingliang Zhai, Cheng Li, Zengyuan Guo, Ningrui Yang, Xiameng Qin, Sanyuan Zhao, Junyu Han, Ji Tao, Yuwei Wu, Yunde Jia
2024 J jnl
CoRR
Jianjian Cao, Beiya Dai, Yulin Li, Xiameng Qin, Jingdong Wang
2024 J jnl
CoRR
Hannan Lu, Xiaohe Wu, Shudong Wang, Xiameng Qin, Xinyu Zhang, Junyu Han, Wangmeng Zuo, Ji Tao
2024 J jnl
Mach. Intell. Res.
Yukun Zhai, Xiaoqiang Zhang, Xiameng Qin, Sanyuan Zhao, Xingping Dong, Jianbing Shen
2024 J jnl
CoRR
Mingliang Zhai, Cheng Li, Zengyuan Guo, Ningrui Yang, Xiameng Qin, Sanyuan Zhao, Junyu Han, Ji Tao, Yuwei Wu, Yunde Jia
2023 A* conf
IJCAI
Mingliang Zhai, Yulin Li, Xiameng Qin, Chen Yi, Qunyi Xie, Chengquan Zhang, Kun Yao, Yuwei Wu, Yunde Jia
2023 J jnl
CoRR
Mingliang Zhai, Yulin Li, Xiameng Qin, Chen Yi, Qunyi Xie, Chengquan Zhang, Kun Yao, Yuwei Wu, Yunde Jia
2023 J jnl
CoRR
Beiya Dai, Xing Li, Qunyi Xie, Yulin Li, Xiameng Qin, Chengquan Zhang, Kun Yao, Junyu Han
2023 A* conf
ICLR
Yuechen Yu, Yulin Li, Chengquan Zhang, Xiaoqiang Zhang, Zengyuan Guo, Xiameng Qin, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang
2023 J jnl
CoRR
Yuechen Yu, Yulin Li, Chengquan Zhang, Xiaoqiang Zhang, Zengyuan Guo, Xiameng Qin, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang
2023 J jnl
CoRR
Yukun Zhai, Xiaoqiang Zhang, Xiameng Qin, Sanyuan Zhao, Xingping Dong, Jianbing Shen
2021 J jnl
CoRR
Jianjian Cao, Xiameng Qin, Sanyuan Zhao, Jianbing Shen
2021 A* conf
ACM Multimedia
Yulin Li, Yuxi Qian, Yuechen Yu, Xiameng Qin, Chengquan Zhang, Yan Liu, Kun Yao, Junyu Han, Jingtuo Liu, Errui Ding
2021 J jnl
CoRR
Yulin Li, Yuxi Qian, Yuchen Yu, Xiameng Qin, Chengquan Zhang, Yan Liu, Kun Yao, Junyu Han, Jingtuo Liu, Errui Ding
2019 A conf
ICDAR
He Guo, Xiameng Qin, Jiaming Liu, Junyu Han, Jingtuo Liu, Errui Ding
2019 J jnl
CoRR
He Guo, Xiameng Qin, Jiaming Liu, Junyu Han, Jingtuo Liu, Errui Ding
2015 J jnl
IEEE Trans. Cybern.
Xiameng Qin, Jianbing Shen, Xiaoyang Mao, Xuelong Li, Yunde Jia
2015 J jnl
IEEE Trans. Multim.
Xiameng Qin, Jianbing Shen, Xiaoyang Mao, Xuelong Li, Yunde Jia
2014 C conf
CIS
Yanmei Dong, Mingtao Pei, Xiameng Qin
2012 B conf
Intelligent Vehicles Symposium
Yunde Jia, Xiameng Qin
2012 conf
ROBIO
Xiameng Qin, Jiaolong Yang, Wei Liang, Mingtao Pei, Yunde Jia
2011 conf
CVPR Workshops
Yong Duan, Lei Chen, Yucheng Wang, Min Yang, Xiameng Qin, Shaoyang He, Yunde Jia
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,
        )