Rafael Rodrigues

22 papers A* 1B 6Misc 1Journal 7Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Multim. Tools Appl.
Rafael Rodrigues, Lucie Lévêque, Jesús Gutiérrez, Houda Jebbari, Meriem Outtas, Lu Zhang, Aladine Chetouani, Shaymaa Al-Juboori, Maria G. Martini, António M. G. Pinheiro
2025 J jnl
IEEE Access
João Prazeres, Rafael Rodrigues, Manuela Pereira, António M. G. Pinheiro
2025 Misc conf
ICASSP
João Prazeres, Rafael Rodrigues, Manuela Pereira, António M. G. Pinheiro
2025 J jnl
CoRR
Fabian Kovac, Sebastian Neumaier, Timea Pahi, Torsten Priebe, Rafael Rodrigues, Dimitrios Christodoulou, Maxime Cordy, Sylvain Kubler, Ali Kordia, Georgios Pitsiladis, John Soldatos, Petros Zervoudakis
2023 B conf
ICIP
João Prazeres, Rafael Rodrigues, Manuela Pereira, António M. G. Pinheiro
2023 A* conf
ACM Multimedia
Michela Testolina, Davi Lazzarotto, Rafael Rodrigues, Shima Mohammadi, João Ascenso, António M. G. Pinheiro, Touradj Ebrahimi
2022 conf
SmartNets
Rui S. Moreira, Christophe Soares, José M. Torres, Pedro Miguel Sobral, Célio Carvalho, Bruno Gomes, Karim Karmali, Salim Karmali, Rafael Rodrigues
2022 conf
EUVIP
João Prazeres, Rafael Rodrigues, Manuela Pereira, António M. G. Pinheiro
2022 B conf
ICIP
Rafael Rodrigues, Susana Quijano-Roy, Robert-Yves Carlier, António M. G. Pinheiro
2022 J jnl
CoRR
Rafael Rodrigues, Susana Quijano-Roy, Robert-Yves Carlier, António M. G. Pinheiro
2022 conf
IEEE SENSORS
Siziwe Gqoba, Tshegofatso Mabilane, Mildred Airo, Lerato Machogo, Pudo Sithole, Nosipho Moloto, Rafael Rodrigues, Ivo A. Hümmelgen
2021 conf
ISBI
Rafael Rodrigues, Marta Gómez-García de la Banda, Mickael Tordjman, David Gómez-Andrés, Susana Quijano-Roy, Robert-Yves Carlier, António M. G. Pinheiro
2020 conf
WorldCIST (2)
Bruno Gomes, Nilsa Melo, Rafael Rodrigues, Pedro Costa, Célio Carvalho, Karim Karmali, Salim Karmali, Christophe Soares, José M. Torres, Pedro Miguel Sobral, Rui S. Moreira
2020 J jnl
Multim. Tools Appl.
Rafael Rodrigues, Peter Pocta, Hugh Melvin, Marco V. Bernardo, Manuela Pereira, António M. G. Pinheiro
2020 conf
WorldCIST (2)
Pedro Costa, Bruno Gomes, Nilsa Melo, Rafael Rodrigues, Célio Carvalho, Karim Karmali, Salim Karmali, Christophe Soares, José M. Torres, Pedro Miguel Sobral, Rui S. Moreira
2020 J jnl
CoRR
Andrew Perkis, Christian Timmerer, Sabina Barakovic, Jasmina Barakovic Husic, Søren Bech, Sebastian Bosse, Jean Botev, Kjell Brunnström, Luís Alberto da Silva Cruz, Katrien De Moor, Andrea de Polo Saibanti, Wouter Durnez, Sebastian Egger-Lampl, Ulrich Engelke, Tiago H. Falk, Asim Hameed, Andrew Hines, Tanja Kojic, Dragan Kukolj, Eirini Liotou, Dragorad Milovanovic, Sebastian Möller, Niall Murray, Babak Naderi, Manuela Pereira, Stuart W. Perry, António M. G. Pinheiro, Andres Pinilla Palacios, Alexander Raake, Sarvesh Rajesh Agrawal, Ulrich Reiter, Rafael Rodrigues, Raimund Schatz, Peter Schelkens, Steven Schmidt, Saeed Shafiee Sabet, Ashutosh Singla, Lea Skorin-Kapov, Mirko Suznjevic, Stefan Uhrig, Sara Vlahovic, Jan-Niklas Voigt-Antons, Saman Zadtootaghaj
2019 conf
EUSIPCO
Rafael Rodrigues, António M. G. Pinheiro
2019 J jnl
CoRR
Rafael Rodrigues, António M. G. Pinheiro
2018 B conf
QoMEX
Lucie Leveque, Hantao Liu, Sabina Barakovic, Jasmina Barakovic Husic, Maria G. Martini, Meriem Outtas, Lu Zhang, Asli Kumcu, Ljiljana Platisa, Rafael Rodrigues, António M. G. Pinheiro, Athanassios Skodras
2016 B conf
QoMEX
Rafael Rodrigues, Peter Pocta, Hugh Melvin, Manuela Pereira, António M. G. Pinheiro
2012 B conf
ICPR
Rafael Rodrigues, António M. G. Pinheiro, Rui Braz, Manuela Pereira, J. Moutinho
2007 B conf
SMC
Eduardo Tavares, Paulo Romero Martins Maciel, Bruno Silva, Meuse N. Oliveira Jr., Rafael Rodrigues, Renato Marques
redb/extractors/js_extractors/js_context.py
← Index redb/extractors/js_extractors/js_context.py python
"""Per-sample shared state for the JavaScript extractor pipeline.

A `JSContext` is built exactly once per JS sample (in `workers.py`) and threaded
into every extractor that runs against that sample. It owns the disk read, the
decoded source text, the line-split cache, the Shannon text-entropy figure, the
shared `scan_source()` results, and the pyjsparser AST. Each of those is
computed lazily through `cached_property` so an extractor that doesn't need a
particular artefact does not pay for it.

Without this object, every JS extractor instance redoes the same disk read,
decode, scan, and (for any consumer) AST parse. With it, every extractor
shares one set of results.

`JSExtractor.__init__` accepts the context via a `context=` kwarg; if absent
(e.g. unit tests instantiating an extractor directly with `source=...`) it
builds a fresh context from the constructor arguments. Either path produces a
fully-populated context, so extractor code can always rely on
`self._context.scan` / `self._context.ast` / etc.
"""

from __future__ import annotations

import math
from collections import Counter
from dataclasses import dataclass
from functools import cached_property
from typing import Any, Dict, List, Optional

import chardet

from redb.extractors.js_extractors.js_patterns import scan_source


def decode_source(raw_bytes: bytes) -> str:
    """Decode raw JS bytes to text, honouring BOMs and falling back to chardet.

    Mirrors the historical `JSExtractor._decode_source` logic so existing tests
    continue to round-trip identically.
    """
    if not raw_bytes:
        return ""

    if raw_bytes[:3] == b"\xef\xbb\xbf":
        return raw_bytes[3:].decode("utf-8", errors="replace")
    if raw_bytes[:2] in (b"\xff\xfe", b"\xfe\xff"):
        return raw_bytes.decode("utf-16", errors="replace")

    try:
        return raw_bytes.decode("utf-8")
    except UnicodeDecodeError:
        pass

    try:
        detected = chardet.detect(raw_bytes)
        if detected and detected.get("encoding"):
            return raw_bytes.decode(detected["encoding"], errors="replace")
    except Exception:
        pass

    return raw_bytes.decode("latin-1", errors="replace")


def _text_entropy(text: str) -> float:
    """Shannon entropy of the character distribution of `text`, rounded to 4dp."""
    if not text:
        return 0.0
    counter = Counter(text)
    length = len(text)
    entropy = 0.0
    for count in counter.values():
        p = count / length
        if p > 0:
            entropy -= p * math.log2(p)
    return round(entropy, 4)


@dataclass
class JSContext:
    """Shared raw materials for one JS sample, consumed by every JS extractor.

    Cheap attributes (raw_bytes, source) are populated eagerly by the factory.
    Expensive ones (scan, ast) are cached_property — computed on first access
    and reused across every extractor that holds the same context.

    `content_type` is the magika label (e.g. `"javascript"`) carried alongside
    the source so the new code_text_content writer (and any future generic
    text-content writer) can record it without re-running magika. Defaults to
    `"javascript"` because by construction this context type is JS-specific;
    workers.py supplies the actual magika value when it builds the context.
    """

    filepath: str
    raw_bytes: bytes
    source: str
    log: Any = None
    content_type: str = "javascript"
    # Populated by JSStringsExtractor.extract() (the decoded/reconstructed
    # strings — hex/unicode/charcode/base64/concat unpacked into plaintext).
    # Read post-loop by the IOC plumbing in workers.py so any IOCs hidden
    # behind those encodings get scraped from the decoded form. Stays None
    # if JSStringsExtractor didn't run for this sample.
    decoded_strings: Optional[list] = None

    @cached_property
    def lines(self) -> List[str]:
        return self.source.splitlines() if self.source else []

    @cached_property
    def text_entropy(self) -> float:
        return _text_entropy(self.source)

    @cached_property
    def scan(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over self.source."""
        return scan_source(self.source) if self.source else {}

    @cached_property
    def ast(self) -> Optional[Any]:
        """Lazy pyjsparser AST. Returns None if the parser is missing or fails.

        Extractors should treat None AST as "fall back to regex" — every
        AST-consuming extractor already handles that path.
        """
        if not self.source:
            return None
        try:
            import pyjsparser
            return pyjsparser.parse(self.source)
        except ImportError:
            if self.log is not None:
                self.log.debug("pyjsparser not installed, AST analysis skipped")
        except Exception as e:
            if self.log is not None:
                self.log.warning(f"AST parsing failed for {self.filepath}: {e}")
        return None

    @cached_property
    def deobfuscated(self) -> "tuple[Optional[str], Optional[str]]":
        """Run the configured JS deobfuscator (with jsbeautifier fallback) once
        per sample and cache the result. Returns `(text, normalizer_used)` or
        `(None, None)` if neither path produced output.

        Computed lazily on first access — samples whose pipeline never reads
        this don't pay the subprocess cost.
        """
        from redb.extractors.js_extractors.js_deobfuscator import deobfuscate
        return deobfuscate(self.source, self.log)

    @cached_property
    def scan_deobfuscated(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over the deobfuscated
        text, keyed by PATTERNS only (FEATURE_PATTERNS are not consulted by
        the dual-pass consumers). Empty dict when there is no deobfuscated
        text or it equals the raw source.

        Two extractors consume the post-deobf API surface:
        `JSSuspiciousAPIsExtractor` (for revealed_by_deobf rows) and
        `JSDeobfuscationExtractor` (for the new_apis_found diff). Caching here
        means we scan the deobfuscated text once instead of twice per sample.
        """
        from redb.extractors.js_extractors.js_patterns import PATTERNS
        deobf_text, _ = self.deobfuscated
        if not deobf_text or deobf_text == self.source:
            return {}
        return scan_source(deobf_text, patterns=(PATTERNS,))

    @cached_property
    def xray(self):
        """Run @nodesecure/js-x-ray once per sample and cache the result.

        Returns an `XRayResult` (always — the function collapses every failure
        path to an empty result so callers don't have to special-case missing
        Node, missing package, timeouts, or parse errors). The
        `JSFeaturesExtractor` reads it for the obfuscator family name and for
        corroborating warning kinds; the heuristic falls back cleanly when
        `xray.obfuscator is None`.
        """
        from redb.extractors.js_extractors.js_xray import run
        return run(self.source, self.log)

    @classmethod
    def from_path(
        cls,
        filepath: str,
        log: Any = None,
        source: Optional[str] = None,
        raw_bytes: Optional[bytes] = None,
        content_type: str = "javascript",
    ) -> "JSContext":
        """Build a context from disk. `raw_bytes` and `source` are optional
        overrides — useful when the caller has already read or decoded the file.
        `content_type` is the magika label workers.py dispatched on; it lands
        on the context for the code_text_content writer to record.
        """
        if raw_bytes is None:
            with open(filepath, "rb") as f:
                raw_bytes = f.read()
        if source is None:
            source = decode_source(raw_bytes)
        return cls(
            filepath=filepath,
            raw_bytes=raw_bytes,
            source=source,
            log=log,
            content_type=content_type,
        )