Kangquan Li

69 papers Journal 67Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
IACR Cryptol. ePrint Arch.
Chaofeng Guan, Lan Luo, Haodong Jiang, Jianhua Hou, Tong Yu, Hong Wang, Kangquan Li, Longjiang Qu
2026 J jnl
Discret. Math.
Yaqin Li, Kangquan Li, Qiancheng Zhang
2026 J jnl
Finite Fields Their Appl.
Sha Jiang, Kangquan Li, Longjiang Qu
2025 J jnl
CoRR
Qiancheng Zhang, Kangquan Li, Longjiang Qu
2025 J jnl
CoRR
Kangquan Li, Hao Chen, Wengang Jin, Longjiang Qu
2025 J jnl
Adv. Math. Commun.
Yunwen Chi, Kangquan Li, Longjiang Qu
2025 J jnl
Des. Codes Cryptogr.
Kangquan Li
2025 J jnl
Finite Fields Their Appl.
Mu Yuan, Kangquan Li, Longjiang Qu
2025 J jnl
Finite Fields Their Appl.
Mu Yuan, Longjiang Qu, Kangquan Li, Xiaoqiang Wang
2025 J jnl
CoRR
Yaqin Li, Kangquan Li, Qiancheng Zhang
2025 J jnl
Finite Fields Their Appl.
Sha Jiang, Mu Yuan, Kangquan Li, Longjiang Qu
2025 J jnl
Appl. Algebra Eng. Commun. Comput.
Guoqiang Liu, Sha Jiang, Kangquan Li
2025 J jnl
J. Cryptol.
Longjiang Qu, Qiancheng Zhang, Kangquan Li
2025 J jnl
IEEE Trans. Inf. Theory
Wengang Jin, Kangquan Li, Longjiang Qu
2025 J jnl
Discret. Math.
Wengang Jin, Kangquan Li, Longjiang Qu
2025 J jnl
Discret. Appl. Math.
Wengang Jin, Kangquan Li, Longjiang Qu
2025 J jnl
Finite Fields Their Appl.
Wengang Jin, Kangquan Li, Longjiang Qu
2025 J jnl
CoRR
Wengang Jin, Kangquan Li, Longjiang Qu
2025 J jnl
IEEE Trans. Inf. Theory
Zijian Zhou, Kangquan Li, Yue Zhou
2024 J jnl
Finite Fields Their Appl.
Longjiang Qu, Kangquan Li
2024 J jnl
CoRR
Yunwen Chi, Kangquan Li, Longjiang Qu
2024 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Nikolay S. Kaleyski
2023 J jnl
Finite Fields Their Appl.
Tailin Niu, Kangquan Li, Longjiang Qu, Chao Li
2023 J jnl
Finite Fields Their Appl.
Marco Calderini, Kangquan Li, Irene Villa
2023 J jnl
J. Comb. Theory A
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2023 J jnl
Finite Fields Their Appl.
Tailin Niu, Kangquan Li, Longjiang Qu, Bing Sun
2022 J jnl
CoRR
Tailin Niu, Kangquan Li, Longjiang Qu, Chao Li
2022 J jnl
Cryptogr. Commun.
Sha Jiang, Kangquan Li, Yubo Li, Longjiang Qu
2022 J jnl
Adv. Math. Commun.
Kangquan Li, Hao Chen, Longjiang Qu
2022 J jnl
CoRR
Tailin Niu, Kangquan Li, Longjiang Qu, Bing Sun
2022 J jnl
CoRR
Longjiang Qu, Kangquan Li
2022 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Yue Zhou, Chunlei Li, Longjiang Qu
2022 J jnl
CoRR
Marco Calderini, Kangquan Li, Irene Villa
2022 J jnl
IACR Cryptol. ePrint Arch.
Kangquan Li, Nikolay S. Kaleyski
2021 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2021 conf
LATINCRYPT
Anne Canteaut, Lukas Kölsch, Chao Li, Chunlei Li, Kangquan Li, Longjiang Qu, Friedrich Wiemer
2021 J jnl
IACR Cryptol. ePrint Arch.
Anne Canteaut, Lukas Kölsch, Chao Li, Chunlei Li, Kangquan Li, Longjiang Qu, Friedrich Wiemer
2021 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2021 J jnl
Des. Codes Cryptogr.
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2021 J jnl
IEEE Trans. Inf. Theory
Tailin Niu, Kangquan Li, Longjiang Qu, Qiang Wang
2021 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Sihem Mesnager, Longjiang Qu
2021 J jnl
Cryptogr. Commun.
Yubo Li, Kangquan Li, Sihem Mesnager, Longjiang Qu
2021 J jnl
IEEE Trans. Inf. Theory
Bing Sun, Kangquan Li, Jian Guo, Longjiang Qu
2021 J jnl
CoRR
Kangquan Li, Yue Zhou, Chunlei Li, Longjiang Qu
2020 J jnl
CoRR
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2020 J jnl
CoRR
Tailin Niu, Kangquan Li, Longjiang Qu, Qiang Wang
2020 J jnl
Finite Fields Their Appl.
Kangquan Li, Longjiang Qu, Yue Zhou
2020 J jnl
Des. Codes Cryptogr.
Yubo Li, Zhichao Yang, Kangquan Li, Longjiang Qu
2020 J jnl
CoRR
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2020 J jnl
Cryptogr. Commun.
Tailin Niu, Kangquan Li, Longjiang Qu, Qiang Wang
2020 J jnl
Finite Fields Their Appl.
Kangquan Li, Longjiang Qu, Chao Li, Hao Chen
2020 J jnl
CoRR
Yubo Li, Kangquan Li, Longjiang Qu
2019 J jnl
Cryptogr. Commun.
Kangquan Li, Longjiang Qu, Qiang Wang
2019 J jnl
CoRR
Kangquan Li, Chunlei Li, Tor Helleseth, Longjiang Qu
2019 J jnl
CoRR
Kangquan Li, Sihem Mesnager, Longjiang Qu
2019 conf
IWSDA
Kangquan Li, Sihem Mesnager, Longjiang Qu
2019 J jnl
IEICE Trans. Fundam. Electron. Commun. Comput. Sci.
Yubo Li, Kangquan Li, Longjiang Qu, Chao Li
2019 J jnl
IEEE Trans. Inf. Theory
Kangquan Li, Longjiang Qu, Bing Sun, Chao Li
2019 J jnl
CoRR
Kangquan Li, Longjiang Qu, Bing Sun, Chao Li
2019 J jnl
IACR Cryptol. ePrint Arch.
Kangquan Li, Longjiang Qu, Bing Sun, Chao Li
2019 J jnl
CoRR
Kangquan Li, Longjiang Qu, Chao Li, Hao Chen
2019 J jnl
CoRR
Kangquan Li, Chunlei Li, Chao Li, Longjiang Qu
2019 J jnl
CoRR
Anne Canteaut, Lukas Kölsch, Chao Li, Chunlei Li, Kangquan Li, Longjiang Qu, Friedrich Wiemer
2018 J jnl
Des. Codes Cryptogr.
Kangquan Li, Longjiang Qu, Qiang Wang
2018 J jnl
Cryptogr. Commun.
Kangquan Li, Longjiang Qu, Xi Chen, Chao Li
2017 J jnl
CoRR
Kangquan Li, Longjiang Qu, Qiang Wang
2017 J jnl
Finite Fields Their Appl.
Kangquan Li, Longjiang Qu, Xi Chen
2016 J jnl
CoRR
Kangquan Li, Longjiang Qu, Chao Li, Shaojing Fu
2015 J jnl
CoRR
Kangquan Li, Longjiang Qu, Xi 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,
        )