Vincent A. Traag

36 papers C 1Journal 29Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
CoRR
Puyu Yang, Vincent A. Traag, Rodrigo Costas, Giovanni Colavizza
2025 J jnl
CoRR
Lucila G. Alvarez Zuzek, Juan Pablo Bascur, Anna Bertani, Riccardo Gallotti, Vincent A. Traag
2023 J jnl
J. Open Source Softw.
Szabolcs Horvát, Jakub Podkalicki, Gábor Csárdi, Tamás Nepusz, Vincent A. Traag, Fabio Zanini, Daniel Noom
2023 J jnl
CoRR
Michael Antonov, Gábor Csárdi, Szabolcs Horvát, Kirill Müller, Tamás Nepusz, Daniel Noom, Maëlle Salmon, Vincent A. Traag, Brooke Foucault Welles, Fabio Zanini
2022 J jnl
CoRR
Vincent A. Traag, Ludo Waltman
2022 J jnl
CoRR
Vincent A. Traag
2022 J jnl
CoRR
Szabolcs Horvát, Jakub Podkalicki, Gábor Csárdi, Tamás Nepusz, Vincent A. Traag, Fabio Zanini, Daniel Noom
2022 J jnl
CoRR
Vincent A. Traag, Lovro Subelj
2021 J jnl
Quant. Sci. Stud.
Vincent A. Traag
2021 J jnl
Netw. Sci.
Hanjo D. Boekhout, Vincent A. Traag, Frank W. Takes
2020 J jnl
Scientometrics
Aliakbar Akbaritabar, Vincent A. Traag, Alberto Caimo, Flaminio Squazzoni
2020 J jnl
CoRR
Vincent A. Traag, Marco Malgarini, S. Sarlo
2019 J jnl
CoRR
Vincent A. Traag
2019 conf
ISSI
Lovro Subelj, Ludo Waltman, Vincent A. Traag, Nees Jan van Eck
2019 conf
ISSI
Vincent A. Traag, Ludo Waltman
2019 conf
ISSI
Giovanni Colavizza, Massimo Franceschet, Vincent A. Traag, Ludo Waltman
2018 J jnl
CoRR
Vincent A. Traag, Ludo Waltman, Nees Jan van Eck
2018 J jnl
CoRR
Lovro Subelj, Ludo Waltman, Vincent A. Traag, Nees Jan van Eck
2018 J jnl
CoRR
Vincent A. Traag, Patrick Doreian, Andrej Mrvar
2018 J jnl
CoRR
Vincent A. Traag, Ludo Waltman
2017 J jnl
CoRR
Ludo Waltman, Vincent A. Traag
2016 J jnl
CoRR
Adeline Decuyper, Arnaud Browet, Vincent A. Traag, Vincent D. Blondel, Jean-Charles Delvenne
2016 J jnl
CoRR
Vincent A. Traag
2016 J jnl
Soc. Networks
Justus Uitermark, Vincent A. Traag, Jeroen Bruggeman
2015 J jnl
CoRR
Vincent A. Traag, Rodrigo Aldecoa, Jean-Charles Delvenne
2015 J jnl
CoRR
Vincent A. Traag
2014 J jnl
CoRR
Vincent A. Traag, Ridho Reinanda, Jacky Hicks, Gerry van Klinken
2014 conf
ECCS
Vincent A. Traag, Ridho Reinanda, Gerry van Klinken
2014 J jnl
CoRR
Vincent A. Traag, Ridho Reinanda, Gerry van Klinken
2013 J jnl
CoRR
Vincent A. Traag, Gautier Krings, Paul Van Dooren
2012 J jnl
CoRR
Vincent A. Traag, Paul Van Dooren, Patrick De Leenheer
2012 J jnl
CoRR
Balázs Csanád Csáji, Arnaud Browet, Vincent A. Traag, Jean-Charles Delvenne, Etienne Huens, Paul Van Dooren, Zbigniew Smoreda, Vincent D. Blondel
2011 C conf
ALIFE
Vincent A. Traag, Paul Van Dooren, Yurii E. Nesterov
2011 J jnl
CoRR
Vincent A. Traag, Paul Van Dooren, Yurii E. Nesterov
2011 conf
SocialCom/PASSAT
Vincent A. Traag, Arnaud Browet, Francesco Calabrese, Frédéric Morlot
2010 conf
SocInfo
Vincent A. Traag, Yurii E. Nesterov, Paul Van Dooren
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"