Weimin Yuan

26 papers A* 2B 1Misc 1Journal 15Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Neural Networks
Weimin Yuan, Cai Meng, Xiangzhi Bai
2025 conf
BIBM
Yue Zeng, Yinuo Wang, Muxing Li, Siqian Ren, Junbo Li, Weimin Yuan, Cai Meng, Chunhui Yuan
2025 J jnl
Eng. Appl. Artif. Intell.
Weimin Yuan, Han Yang, Zhu Han, Yanru Zhang
2025 Misc conf
ICASSP
Wenhao Hu, Weilong Chen, Weimin Yuan, Xiaolu Chen, Han Yang, Yanru Zhang, Zhu Han
2025 J jnl
CoRR
Junbo Li, Weimin Yuan, Yinuo Wang, Yue Zeng, Shihao Shu, Cai Meng, Xiangzhi Bai
2025 J jnl
Comput. Vis. Image Underst.
Weimin Yuan, Yinuo Wang, Cai Meng, Xiangzhi Bai
2025 conf
SPAWC
Weimin Yuan, Weilong Chen, Hien Nguyen, Yifei Zhu, Dan Wang, Zhu Han
2025 J jnl
Comput. Medical Imaging Graph.
Meidi Chen, Siyin Wang, Ke Liang, Xiao Chen, Zihan Xu, Chen Zhao, Weimin Yuan, Jing Wan, Qiu Huang
2025 J jnl
Comput. Medical Imaging Graph.
Yinuo Wang, Tao Guo, Weimin Yuan, Shihao Shu, Cai Meng, Xiangzhi Bai
2025 J jnl
CoRR
Weimin Yuan, Cai Meng
2025 J jnl
IEEE Trans. Circuits Syst. Video Technol.
Weilong Chen, Wenhao Hu, Xiaolu Chen, Weimin Yuan, Yan Wang, Yanru Zhang, Zhu Han
2024 A* conf
ACM Multimedia
Wenhao Hu, Weilong Chen, Weimin Yuan, Yan Wang, Shimin Cai, Yanru Zhang
2024 B conf
IJCNN
Weimin Yuan, Yinuo Wang, Ning Li, Cai Meng, Xiangzhi Bai
2024 conf
ISBI
Yinuo Wang, Kai Chen, Weimin Yuan, Zhouping Tang, Cai Meng, Xiangzhi Bai
2024 J jnl
Comput. Vis. Image Underst.
Weimin Yuan, Yuanyuan Wang, Ruirui Fan, Yuxuan Zhang, Guangmei Wei, Cai Meng, Xiangzhi Bai
2024 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Zhaoxi Li, Cai Meng, Dingzhe Li, Limin Liu, Weimin Yuan, Zeweng Huang
2024 J jnl
Pattern Recognit.
Weimin Yuan, Cai Meng, Xiangzhi Bai
2023 J jnl
Appl. Intell.
Yuanyuan Wang, Weimin Yuan, Xiangzhi Bai
2023 conf
MMAsia (Workshops)
Weimin Yuan, Yinuo Wang, Cai Meng, Xiangzhi Bai
2023 J jnl
CoRR
Yinuo Wang, Kai Chen, Weimin Yuan, Cai Meng, Xiangzhi Bai
2022 conf
HPCC/DSS/SmartCity/DependSys
Yuxi Chen, Chenghao Huang, Weimin Yuan, Yutong Wu, Ziyi Zhang, Hao Tang, Yanru Zhang
2022 A* conf
ACM Multimedia
Weilong Chen, Chenghao Huang, Weimin Yuan, Xiaolu Chen, Wenhao Hu, Xinran Zhang, Yanru Zhang
2022 conf
SMM4H@COLING
Chenghao Huang, Xiaolu Chen, Yuxi Chen, Yutong Wu, Weimin Yuan, Yan Wang, Yanru Zhang
2021 J jnl
Signal Process. Image Commun.
Weimin Yuan, Cai Meng, Xiaoyan Tong, Zhaoxi Li
2020 J jnl
IEEE Access
Liyan Xiong, Xiangzheng Ling, Xiaohui Huang, Hong Tang, Weimin Yuan, Weichun Huang
2019 conf
IGTA
Weimin Yuan, Xiaoyan Tong, Bin Xiao
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"