Wanchun Chen

36 papers C 1Journal 21Unranked 14
YearRankTypeTitle / Venue / Authors
2025 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Xiang Xu, Wanchun Chen, Liang Yang
2024 conf
ICAC
Xiaopeng Gong, Wanchun Chen, Zhongyuan Chen
2024 conf
ICAC
Chenglong Luo, Yuannan Xu, Wanchun Chen, Zhongyuan Chen, Xinrui Xu
2024 conf
ICAC
Nanxiang Wang, Wanchun Chen, Zhongyuan Chen
2024 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Xiaopeng Gong, Wanchun Chen, Zhongyuan Chen, Wenjie Yuan
2024 conf
ICAC
Peng Wang, Wanchun Chen, Zhongyuan Chen, Jinchuan Hu
2024 conf
ICAC
Qing Li, Wanchun Chen, Zhongyuan Chen, Jinchuan Hu
2023 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Qi Yu, Wanchun Chen, Wenbin Yu
2023 J jnl
J. Frankl. Inst.
Zhongyuan Chen, Xiaoming Liu, Wanchun Chen
2022 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Wenbin Yu, Jin Yang, Wanchun Chen
2021 J jnl
J. Intell. Robotic Syst.
Zhongyuan Chen, M. Reza Emami, Wanchun Chen
2021 J jnl
IEEE Syst. J.
Yang Li, Wanchun Chen, Hao Zhou, Liang Yang
2021 J jnl
Int. J. Control
Liang Yang, Jin Yang, Xiaoming Liu, Wanchun Chen, Hao Zhou
2021 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Wenbin Yu, Wanchun Chen
2021 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Yang Li, Wanchun Chen, Liang Yang
2020 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Wenbin Yu, Penglei Zhao, Wanchun Chen
2020 conf
UV
Mengya Gao, Wanchun Chen, Wenbin Yu
2020 J jnl
IEEE Access
Xingcai He, Wanchun Chen, Liang Yang
2020 J jnl
IEEE Access
Hao Zhou, Tao Cheng, Xiaoming Liu, Wanchun Chen
2019 conf
CCTA
Yijun Feng, Wanchun Chen, Liang Yang, Donghui Wei
2019 J jnl
Comput. Optim. Appl.
Wanchun Chen, Wenhao Du, William W. Hager, Liang Yang
2019 conf
CIS/RAM
Peng Wang, Wanchun Chen, Xiaoming Liu, Zhongyuan Chen
2019 J jnl
IEEE Access
Liang Yang, Jin Yang, Wanchun Chen, Hao Liu
2019 conf
CIS/RAM
Zhaowei Yu, Wanchun Chen, Zhongyuan Chen, Xiaoming Liu
2018 J jnl
Comput. Appl. Eng. Educ.
Zhongyuan Chen, Wanchun Chen, Xiaoming Liu, Chuang Song
2018 J jnl
J. Sensors
Zhongyuan Chen, Wanchun Chen, Xiaoming Liu, Chuang Song
2017 conf
CIS/RAM
Tailong He, Wanchun Chen
2017 conf
CIS/RAM
Jingwei Xie, Wanchun Chen
2016 C conf
IGARSS
Chunhui Pan, Fuzhong Weng, Trevor Beck, Ding Liang, Eve-Marie Devaliere, Wanchun Chen, Shuoguo Ding
2015 conf
ICCAIS
Jing Zhang, Liuqiu You, Wanchun Chen
2015 conf
ICCAIS
Jinchuan Hu, Jinglin Li, Wanchun Chen
2013 conf
ASCC
Tawfiqur Rahman, Hao Zhou, Wanchun Chen
2012 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Xiaoming Liu, Jiali Gu, Wanchun Chen, Xiaolan Xing, Xingliang Yin
2011 J jnl
IEEE Trans. Geosci. Remote. Sens.
Flavio Iturbide-Sanchez, Sid-Ahmed Boukabara, Ruiyue Chen, Kevin Garrett, Christopher Grassotti, Wanchun Chen, Fuzhong Weng
2011 J jnl
IEEE Trans. Geosci. Remote. Sens.
Sid-Ahmed Boukabara, Kevin Garrett, Wanchun Chen, Flavio Iturbide-Sanchez, Christopher Grassotti, Cezar Kongoli, Ruiyue Chen, Quanhua (Mark) Liu, Banghua Yan, Fuzhong Weng, Ralph Ferraro, Thomas J. Kleespies, Huan Meng
2010 J jnl
IEEE Trans. Geosci. Remote. Sens.
Sid-Ahmed Boukabara, Kevin Garrett, Wanchun Chen
redb/extractors/js_extractors/js_suspicious_apis.py
← Index redb/extractors/js_extractors/js_suspicious_apis.py python
import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.js_extractor import JSExtractor
from redb.extractors.js_extractors.js_patterns import CATEGORIES, PATTERNS


# Backwards-compatible export: `{category: [(raw_pattern_string, api_name), ...]}`
# in canonical PATTERNS insertion order (code_execution, network, filesystem,
# process, registry, crypto_encoding, dom_manipulation). Kept so external
# callers (notably JSDeobfuscationExtractor pre-cleanup) keep working until
# they are migrated to PATTERNS directly.
SUSPICIOUS_APIS: "dict[str, list[tuple[str, str]]]" = {}
for _name, _compiled in PATTERNS.items():
    SUSPICIOUS_APIS.setdefault(CATEGORIES[_name], []).append((_compiled.pattern, _name))


class JSSuspiciousAPIsExtractor(JSExtractor):

    def __init__(
        self, filepath, log, exporters=None, index_prefix=None,
        known_benign=False, known_malicious=False, source=None, context=None,
    ):
        super().__init__(
            filepath, log, exporters, index_prefix,
            known_benign, known_malicious, source, context=context,
        )
        self.api_findings = None
        self.log.debug(inspect.currentframe().f_code.co_name)

    def tag(self):
        return Tag.JS_SUSPICIOUS_APIS.value

    def _get_context_snippet(self, line, max_len=200):
        """Get a truncated context snippet around a match."""
        line = line.strip()
        if len(line) > max_len:
            return line[:max_len] + "..."
        return line

    def extract(self):
        src = self.js_source
        if not src:
            return None

        # Pass 1: shared per-sample scan over the raw source. The dict contains
        # entries for both PATTERNS and FEATURE_PATTERNS; the loop below only
        # consults PATTERNS keys, so feature-only entries are ignored.
        raw_scan = self._context.scan or {}
        raw_lines = self.lines

        # Pass 2: same patterns over the deobfuscated text, when the
        # deobfuscator produced something meaningfully different. APIs hidden
        # behind one obfuscation layer (Vjw0rm-style array.join + eval,
        # Dean-Edwards packers, jjencode, ...) only surface here. The scan is
        # cached on JSContext so JSDeobfuscationExtractor (which computes the
        # new_apis_found diff) reuses the same result.
        deobf_scan = self._context.scan_deobfuscated
        if deobf_scan:
            deobf_text, _ = self._context.deobfuscated
            deobf_lines = deobf_text.splitlines()
        else:
            deobf_lines = []

        findings = []
        # Iterate PATTERNS in canonical order so output is deterministic and
        # matches the historical category/pattern ordering. For each api_name,
        # raw findings take precedence; if an API is found only in the
        # deobfuscated text, we surface it as a row tagged revealed_by_deobf=1
        # with line numbers / snippets pulled from the deobfuscated source.
        for api_name in PATTERNS:
            raw_info = raw_scan.get(api_name)
            if raw_info:
                line_numbers = raw_info["lines"]
                lines_for_snippets = raw_lines
                revealed_by_deobf = 0
            else:
                deobf_info = deobf_scan.get(api_name)
                if not deobf_info:
                    continue
                line_numbers = deobf_info["lines"]
                lines_for_snippets = deobf_lines
                revealed_by_deobf = 1

            snippets = [
                self._get_context_snippet(lines_for_snippets[ln - 1])
                for ln in line_numbers[:3]
                if 0 < ln <= len(lines_for_snippets)
            ]
            findings.append({
                "api_name": api_name,
                "api_category": CATEGORIES[api_name],
                # Historical semantics: count = number of unique lines with a
                # match, not total in-source match count.
                "call_count": len(line_numbers),
                "line_numbers": line_numbers,
                "context_snippet": " | ".join(snippets),
                "revealed_by_deobf": revealed_by_deobf,
            })

        if not findings:
            return None

        self.api_findings = findings
        return findings

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ClickHouseExporter":
            if not self.api_findings:
                return None

            current_time = datetime.now(timezone.utc)
            data = []
            for f in self.api_findings:
                data.append([
                    self.sha256,
                    f['api_name'],
                    f['api_category'],
                    f['call_count'],
                    f['line_numbers'],
                    f['context_snippet'],
                    f['revealed_by_deobf'],
                    current_time,
                ])

            column_names = [
                "sha256", "api_name", "api_category",
                "call_count", "line_numbers", "context_snippet",
                "revealed_by_deobf",
                "analysis_date",
            ]

            column_type_names = [
                "FixedString(64)", "String", "LowCardinality(String)",
                "UInt32", "Array(UInt32)", "String",
                "UInt8",
                "DateTime64(3, 'UTC')",
            ]

            return (data, column_names, column_type_names)

    def get_clickhouse_table(self) -> str:
        return "redb_js_suspicious_apis"