Maarten Houben

23 papers A* 7A 5B 1Journal 1Unranked 8
YearRankTypeTitle / Venue / Authors
2026 A* conf
CHI
Teis Arets, Maarten Houben, Fleur van Haeren, Wijnand IJsselsteijn, Giulia Perugia
2026 conf
HRI Companion
Febe Anna Kooij-Meijer, Emilia I. Barakova, Rosa Elfering, Wang-Long Li, Maarten Houben
2025 A* conf
CHI
Sanne Beijer, Maarten Houben, Wijnand A. IJsselsteijn, Rens Brankaert
2025 A* conf
CHI
Alicia Valencia, Maarten Houben, Rens Brankaert, Berry Eggen, Wijnand A. IJsselsteijn
2025 J jnl
CoRR
Teis Arets, Giulia Perugia, Maarten Houben, Wijnand A. IJsselsteijn
2024 A* conf
CHI
Maarten Houben, Rens Brankaert, Maudy Gosen, Veerle van Overloop, Wijnand A. IJsselsteijn
2024 conf
CHI Extended Abstracts
Maarten Houben, Minha Lee, Sarah Foley, Kellie Morrissey, Rens Brankaert
2024 conf
CHI Extended Abstracts
Sanne Beijer, Fenna Dam, Maarten Houben, Rens Brankaert
2023 A* conf
CHI
Binh Vinh Duc Nguyen, Jihae Han, Maarten Houben, Yssmin Bayoumi, Andrew Vande Moere
2023 conf
CHI Extended Abstracts
Maarten Houben, Minha Lee, Sarah Foley, Kellie Morrissey, Rens Brankaert
2023 conf
CHI Extended Abstracts
Yvon Ruitenburg, Rens Brankaert, Maarten Houben, Minha Lee, Gert Pasman
2023 conf
CUI
Maarten Houben, Nena van As, Nitin Sawhney, David Unbehaun, Minha Lee
2023 A conf
Conference on Designing Interactive Systems
Maarten Houben, Melvin van Berlo, Frank Antonissen, Eveline J. M. Wouters, Rens Brankaert
2022 A* conf
CHI
Maarten Houben, Rens Brankaert, Gail Kenning, Inge M. B. Bongers, Berry Eggen
2022 B conf
TEI
Maarten Houben, Rens Brankaert, Emma Dhaeze, Gail Kenning, Inge M. B. Bongers, Berry Eggen
2020 ch.
HCI and Design in the Context of Dementia
Maarten Houben, Rens Brankaert, Saskia Bakker, Inge M. B. Bongers, Berry Eggen
2020 conf
CHI Extended Abstracts
Karlijn van Rijen, Tom Cobbenhagen, Rens Janssen, Maria Olsen, Rens Brankaert, Maarten Houben, Yuan Lu
2020 A conf
Conference on Designing Interactive Systems (Companion Volume)
Maarten Houben, Rens Brankaert, Eveline J. M. Wouters
2020 A* conf
CHI
Maarten Houben, Rens Brankaert, Saskia Bakker, Gail Kenning, Inge M. B. Bongers, Berry Eggen
2020 conf
CHI Extended Abstracts
Maarten Houben, Benjamin Lehn, Noa van den Brink, Sabeth Diks, Jasmijn Verhoef, Rens Brankaert
2019 A conf
Conference on Designing Interactive Systems (Companion Volume)
Jorgos Coenen, Maarten Houben, Andrew Vande Moere
2019 A conf
Conference on Designing Interactive Systems
Maarten Houben, Rens Brankaert, Saskia Bakker, Gail Kenning, Inge M. B. Bongers, Berry Eggen
2017 A conf
Conference on Designing Interactive Systems (Companion Volume)
Maarten Houben, Benjamin Denef, Matthias Mattelaer, Sandy Claes, Andrew Vande Moere
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"