Ramtin Gharleghi

16 papers Misc 1Journal 10Unranked 5
YearRankTypeTitle / Venue / Authors
2025 conf
MIUA (3)
Hao Wu, Sonit Singh, Ramtin Gharleghi, Arcot Sowmya, Susann Beier
2025 J jnl
CoRR
Shisheng Zhang, Ramtin Gharleghi, Sonit Singh, Daniel Moses, Dona Adikari, Arcot Sowmya, Susann Beier
2025 J jnl
CoRR
Dylan Saeed, Ramtin Gharleghi, Susann Bier, Sonit Singh
2025 J jnl
Comput. Methods Programs Biomed.
Mingzi Zhang, Hamed Keramati, Ramtin Gharleghi, Susann Beier
2025 J jnl
IEEE Trans. Biomed. Eng.
Ramtin Gharleghi, Mingzi Zhang, Dona Adikari, Lucy McGrath-Cadell, Robert M. Graham, Jolanda J. Wentzel, Mark Webster, Chris Ellis, Sze-Yuan Ooi, Susann Beier
2023 Misc conf
IVCNZ
Shisheng Zhang, Ramtin Gharleghi, Sonit Singh, Arcot Sowmya, Susann Beier
2023 J jnl
CoRR
Shisheng Zhang, Ramtin Gharleghi, Sonit Singh, Arcot Sowmya, Susann Beier
2023 J jnl
CoRR
Jianning Li, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito, Afaque R. Memon, Xiaojun Chen, Jan Stefan Kirschke, Ezequiel de la Rosa, Patrick Ferdinand Christ, Hongwei Bran Li, David G. Ellis, Michele R. Aizenberg, Sergios Gatidis, Thomas Küstner, Nadya Shusharina, Nicholas Heller, Vincent Andrearczyk, Adrien Depeursinge, Mathieu Hatt, Anjany Sekuboyina, Maximilian Löffler, Hans Liebl, Reuben Dorent, Tom Vercauteren, Jonathan Shapey, Aaron Kujawa, Stefan Cornelissen, Patrick Langenhuizen, Achraf Ben-Hamadou, Ahmed Rekik, Sergi Pujades, Edmond Boyer, Federico Bolelli, Costantino Grana, Luca Lumetti, Hamidreza Salehi, Jun Ma, Yao Zhang, Ramtin Gharleghi, Susann Beier, Arcot Sowmya, Eduardo A. Garza-Villarreal, Thania Balducci, et al.
2022 J jnl
Comput. Medical Imaging Graph.
Ramtin Gharleghi, Dona Adikari, Katy Ellenberger, Sze-Yuan Ooi, Chris Ellis, Chung-Ming Chen, Ruochen Gao, Yuting He, Raabid Hussain, Chia-Yen Lee, Jun Li, Jun Ma, Ziwei Nie, Bruno Oliveira, Yaolei Qi, Youssef Skandarani, João L. Vilaça, Xiyue Wang, Sen Yang, Arcot Sowmya, Susann Beier
2022 J jnl
CoRR
Ramtin Gharleghi, Dona Adikari, Katy Ellenberger, Mark Webster, Chris Ellis, Arcot Sowmya, Sze-Yuan Ooi, Susann Beier
2022 conf
EMBC
Chi Shen, Ramtin Gharleghi, Darson Dezheng Li, Susann Beier
2022 conf
ISBI
Nanway Chen, Ramtin Gharleghi, Arcot Sowmya, Susann Beier
2022 J jnl
Comput. Methods Programs Biomed.
Ramtin Gharleghi, Nanway Chen, Arcot Sowmya, Susann Beier
2022 J jnl
Comput. Methods Programs Biomed.
Ramtin Gharleghi, Arcot Sowmya, Susann Beier
2020 conf
ISBI
Ramtin Gharleghi, Gihan Samarasinghe, Arcot Sowmya, Susann Beier
2019 conf
MLMECH/CVII-STENT@MICCAI
Ramtin Gharleghi, Heidi Wright, Somesh Khullar, Jinbo Liu, Tapabrata Ray, Susann Beier
redb/extractors/js_extractors/js_deobfuscation.py
← Index redb/extractors/js_extractors/js_deobfuscation.py python
import hashlib
import inspect
import re
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 PATTERNS

# String literals of 4+ characters; only used by the deobfuscation diff to count
# strings revealed after deobfuscation. Compiled once at module load.
_STRING_LITERAL_4PLUS_RE = re.compile(r"[\"\']([^\"\']{4,})[\"\']")


class JSDeobfuscationExtractor(JSExtractor):
    """Compute pre/post-deobfuscation metrics for a JS sample.

    The actual deobfuscation pass (external tool with jsbeautifier fallback)
    lives on `JSContext.deobfuscated` and is cached per sample, so any other
    extractor that needs the deobfuscated text reads the same value without
    re-running the subprocess. Configure the external tool via env vars:
        JS_DEOBFUSCATOR_PATH    Path or name (default: webcrack)
        JS_DEOBFUSCATE_TIMEOUT  Seconds (default: 60)
    """

    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.deobfuscation_result = None
        self.log.debug(inspect.currentframe().f_code.co_name)

    def tag(self):
        return Tag.JS_DEOBFUSCATION.value

    def extract(self):
        src = self.js_source
        if not src:
            return None

        deobfuscated, deobfuscator_used = self._context.deobfuscated
        if deobfuscated is None:
            return None

        original_size = len(src)
        original_entropy = self._context.text_entropy
        deobfuscated_size = len(deobfuscated)
        deobfuscated_entropy = self._calculate_text_entropy(deobfuscated)
        size_change_ratio = round(deobfuscated_size / original_size, 4) if original_size else 0.0

        # Strings revealed by deobfuscation: matched literals are extracted from
        # both versions and the set difference is the count of "new" strings.
        original_strings = set(_STRING_LITERAL_4PLUS_RE.findall(src))
        deobfuscated_strings = set(_STRING_LITERAL_4PLUS_RE.findall(deobfuscated))
        new_strings = deobfuscated_strings - original_strings

        # Suspicious APIs revealed by deobfuscation. Both sides of the diff
        # come from JSContext caches: the raw scan is computed once for the
        # whole pipeline; the deobfuscated scan is computed once and reused
        # by JSSuspiciousAPIsExtractor's revealed_by_deobf rows.
        original_apis = {n for n in self._context.scan if n in PATTERNS}
        deobfuscated_apis = set(self._context.scan_deobfuscated)
        new_apis = deobfuscated_apis - original_apis

        deobfuscated_sha256 = hashlib.sha256(deobfuscated.encode('utf-8')).hexdigest()

        self.deobfuscation_result = {
            'deobfuscator_used': deobfuscator_used,
            'deobfuscation_successful': True,
            'original_size': original_size,
            'deobfuscated_size': deobfuscated_size,
            'size_change_ratio': size_change_ratio,
            'original_entropy': original_entropy,
            'deobfuscated_entropy': deobfuscated_entropy,
            'new_strings_found': len(new_strings),
            'new_apis_found': len(new_apis),
            'deobfuscated_sha256': deobfuscated_sha256,
        }
        return self.deobfuscation_result

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ClickHouseExporter":
            if not self.deobfuscation_result:
                return None

            r = self.deobfuscation_result
            current_time = datetime.now(timezone.utc)
            data = [[
                self.sha256,
                r['deobfuscator_used'],
                int(r['deobfuscation_successful']),
                r['original_size'],
                r['deobfuscated_size'],
                r['size_change_ratio'],
                r['original_entropy'],
                r['deobfuscated_entropy'],
                r['new_strings_found'],
                r['new_apis_found'],
                r['deobfuscated_sha256'],
                current_time,
            ]]

            column_names = [
                "sha256", "deobfuscator_used", "deobfuscation_successful",
                "original_size", "deobfuscated_size", "size_change_ratio",
                "original_entropy", "deobfuscated_entropy",
                "new_strings_found", "new_apis_found",
                "deobfuscated_sha256", "analysis_date",
            ]

            column_type_names = [
                "FixedString(64)", "LowCardinality(String)", "UInt8",
                "UInt64", "UInt64", "Float64",
                "Float64", "Float64",
                "UInt32", "UInt32",
                "FixedString(64)", "DateTime64(3, 'UTC')",
            ]

            return (data, column_names, column_type_names)

    def get_clickhouse_table(self) -> str:
        return "redb_js_deobfuscation"