James D. Wilson

41 papers C 1Journal 34Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
NeuroImage
Gustav R. Sjobeck, Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Charles DeCarli, James D. Wilson, Dana L. Tudorascu
2024 J jnl
Inf. Sci.
Terence Parr, Jeff Hamrick, James D. Wilson
2023 J jnl
Medical Image Anal.
Mahbaneh Eshaghzadeh Torbati, Davneet S. Minhas, Charles M. Laymon, Pauline Maillard, James D. Wilson, Chang-Le Chen, Ciprian M. Crainiceanu, Charles DeCarli, Seong Jae Hwang, Dana L. Tudorascu
2022 J jnl
CoRR
Connor P. Gibbs, Bailey K. Fosdick, James D. Wilson
2022 J jnl
Qual. Reliab. Eng. Int.
Lisha Yu, Inez Maria Zwetsloot, Nathaniel T. Stevens, James D. Wilson, Kwok Leung Tsui
2021 J jnl
Netw. Sci.
James D. Wilson, Melanie Baybay, Rishi Sankar, Paul E. Stillman, Abbie M. Popa
2021 J jnl
CoRR
James D. Wilson, Jihui Lee
2020 J jnl
CoRR
Terence Parr, James D. Wilson, Jeff Hamrick
2020 J jnl
Comput. Stat. Data Anal.
Jihui Lee, Gen Li, James D. Wilson
2019 J jnl
CoRR
Terence Parr, James D. Wilson
2019 J jnl
NeuroImage
Paul E. Stillman, James D. Wilson, Matthew J. Denny, Bruce A. Desmarais, Skyler J. Cranmer, Zhong-Lin Lu
2019 conf
EMBC
Rathinaswamy B. Govindan, An N. Massaro, Srinivas Kota, Reagan C. Grabowski, James D. Wilson, Adré du Plessis
2019 J jnl
Sensors
Yiqi Lin, Mengxue Zhang, Patricio S. La Rosa, James D. Wilson, Arye Nehorai
2019 conf
GlobalSIP
Neslihan Bisgin, James D. Wilson, Hari Eswaran
2019 J jnl
Qual. Reliab. Eng. Int.
James D. Wilson, Nathaniel T. Stevens, William H. Woodall
2019 J jnl
CoRR
Lisha Yu, Inez Maria Zwetsloot, Nathaniel T. Stevens, James D. Wilson, Kwok Leung Tsui
2019 conf
BHI
Neslihan Bisgin, James D. Wilson, Pamela Murphy, Eric R. Siegel, Curtis L. Lowery, Hari Eswaran
2018 J jnl
CoRR
James D. Wilson, Melanie Baybay, Rishi Sankar, Paul E. Stillman
2018 J jnl
IEEE J. Biomed. Health Informatics
Recep Avci, James D. Wilson, Diana I. Escalona-Vargas, Hari Eswaran
2017 J jnl
J. Mach. Learn. Res.
James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel
2017 J jnl
IEEE Trans. Biomed. Eng.
James D. Wilson, Jens Haueisen
2017 J jnl
Soc. Networks
James D. Wilson, Matthew J. Denny, Shankar Bhamidi, Skyler J. Cranmer, Bruce A. Desmarais
2017 J jnl
CoRR
James D. Wilson, David T. Uminsky
2017 J jnl
CoRR
Kelsey MacMillan, James D. Wilson
2016 J jnl
Comput. Biol. Medicine
Srinivasan Vairavan, Umit D. Ulusar, Hari Eswaran, Hubert Preissl, James D. Wilson, S. S. Mckelvey, Curtis L. Lowery, Rathinaswamy B. Govindan
2016 J jnl
CoRR
William H. Woodall, Meng J. Zhao, Kamran Paynabar, Ross Sparks, James D. Wilson
2016 J jnl
CoRR
James D. Wilson, John Palowitch, Shankar Bhamidi, Andrew B. Nobel
2016 J jnl
CoRR
James D. Wilson, Nathaniel T. Stevens, William H. Woodall
2016 J jnl
CoRR
Ross Sparks, James D. Wilson
2015
James D. Wilson
2013 J jnl
CoRR
James D. Wilson, Simi Wang, Peter J. Mucha, Shankar Bhamidi, Andrew B. Nobel
2013 conf
EMBC
Bhargavi Sriram, James D. Wilson, Rathinaswamy B. Govindan, Curtis L. Lowery, Hubert Preissl, Hari Eswaran
2011 conf
EMBC
Rathinaswamy B. Govindan, Srinivasan Vairavan, Bhargavi Sriram, James D. Wilson, Hubert Preissl, Hari Eswaran
2009 J jnl
IEEE Trans. Biomed. Eng.
Srinivasan Vairavan, Hari Eswaran, Naim Haddad, Douglas F. Rose, Hubert Preissl, James D. Wilson, Curtis Lowery, Rathinaswamy B. Govindan
2008 J jnl
NeuroImage
Rathinaswamy B. Govindan, James D. Wilson, Hubert Preissl, Pamela Murphy, Curtis L. Lowery, Hari Eswaran
2008 J jnl
IEEE Trans. Biomed. Eng.
James D. Wilson, Rathinaswamy B. Govindan, Jeff O. Hatton, Curtis Lowery, Hubert Preissl
2004 J jnl
IEEE Trans. Biomed. Eng.
Jiri Vrba, Stephen E. Robinson, Jack McCubbin, Curtis L. Lowery, Hari Eswaran, James D. Wilson, Pamela Murphy, Hubert Preissl
2004 J jnl
NeuroImage
Jiri Vrba, Stephen E. Robinson, Jack McCubbin, Pamela Murphy, Hari Eswaran, James D. Wilson, Hubert Preissl, Curtis Lowery
2003 C conf
ICANN
Coskun Bayrak, Z. Chen, Jonathan Norton, Hubert Preissl, Curtis Lowery, Hari Eswaran, James D. Wilson
2000 J jnl
Int. J. Bifurc. Chaos
N. Radhakrishnan, James D. Wilson, Philipos C. Loizou
2000 J jnl
Int. J. Bifurc. Chaos
N. Radhakrishnan, James D. Wilson, Curtis Lowery, Pamela Murphy, Hari Eswaran
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"