Valentina Zangrando

12 papers B 1Journal 2Unranked 9
YearRankTypeTitle / Venue / Authors
2021 conf
SIIE
Francisco J. García-Peñalvo, Lucía García-Holgado, Alicia García-Holgado, Valentina Zangrando, Liliana Romaniuc, Maria Kyriakidou, María P. Vassileva, Daina Gudoniene, Katarzyna Rak, Peter Frühmann, Afxentis Afxentiou, Anna Bartoli, Vasia Karkantzou
2021 conf
ICIST
Daina Gudoniene, Tomas Blazauskas, Vitalija Kersiene, Valentina Zangrando
2018 conf
TEEM
María José Rodríguez-Conde, Alicia García-Holgado, Valentina Zangrando, Francisco José García-Peñalvo
2018 conf
TEEM
Alicia García-Holgado, José Carlos Sánchez Prieto, Lucía García-Holgado, Valentina Zangrando, Ömer Yigit, Francisco José García-Peñalvo
2015 conf
TEEM
Paloma No-Gutiérrez, María José Rodriguez-Conde, Valentina Zangrando, Antonio M. Seoane-Pardo
2014 conf
TEEM
Paloma No-Gutiérrez, María José Rodríguez-Conde, Valentina Zangrando, Antonio M. Seoane-Pardo, Lorenzo Luatti
2014 J jnl
Int. J. Hum. Cap. Inf. Technol. Prof.
Maria Clara Viegas, Maria Arcelina Marques, Gustavo R. Alves, Aleksandra Mykowska, Nikolas Galanis, Marc Alier Forment, Francis Brouns, José Janssen, Francisco J. García-Peñalvo, Alicia García-Holgado, Valentina Zangrando, Miguel Ángel Conde González
2013 B conf
EC-TEL
Francisco J. García-Peñalvo, Valentina Zangrando, Alicia García-Holgado, Miguel Ángel Conde González, Antonio M. Seoane-Pardo, Marc Alier Forment, Nikolas Galanis, Jordi López, José Janssen, Francis Brouns, Anton Finders, Adriana J. Berlanga, Peter B. Sloep, Dai Griffiths, Mark William Johnson, Elwira Waszkiewicz, Aleksandra Mykowska, Miroslav Minovic, Milos Milovanovic, Maria Arcelina Marques, Maria C. Viegas, Gustavo Ribeiro Alves
2013 conf
WEILER@EC-TEL
Miguel Ángel Conde González, Francisco J. García-Peñalvo, Valentina Zangrando, Alicia García-Holgado, Antonio M. Seoane-Pardo, Marc Alier Forment, Nikolas Galanis, Dai Griffiths, Mark William Johnson, José Janssen, Francis Brouns, Hubert Vogten, Anton Finders, Peter B. Sloep, Maria Arcelina Marques, Maria C. Viegas, Gustavo Ribeiro Alves, Elwira Waszkiewicz, Aleksandra Mykowska, Miroslav Minovic, Milos Milovanovic
2013 conf
WEILER@EC-TEL
Maria Arcelina Marques, Maria C. Viegas, Gustavo Ribeiro Alves, Valentina Zangrando, Nikolas Galanis, José Janssen, Elwira Waszkiewicz, Miguel Ángel Conde González, Francisco J. García-Peñalvo
2013 J jnl
J. Univers. Comput. Sci.
Francisco J. García-Peñalvo, Miguel Ángel Conde González, Valentina Zangrando, Alicia García-Holgado, Anton M. Seoane, Marc Alier Forment, Nikolas Galanis, Francis Brouns, Hubert Vogten, David Griffiths, Aleksandra Mykowska, Gustavo Ribeiro Alves, Miroslav Minovic
2013 conf
TEEM
Maria Clara Viegas, Maria Arcelina Marques, Gustavo Ribeiro Alves, Nikolas Galanis, Francis Brouns, José Janssen, Elwira Waszkiewicz, Aleksandra Mykowska, Dom Szkolen i Doradztwa, Valentina Zangrando, Alicia García-Holgado, Miguel Ángel Conde González, Francisco José García-Peñalvo
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"