Ramya Tekumalla

16 papers A 1B 3Journal 9Unranked 3
YearRankTypeTitle / Venue / Authors
2023 J jnl
Database J. Biol. Databases Curation
Davy Weissenbacher, Karen O'Connor, Siddharth Rawal, Yu Zhang, Richard Tzong-Han Tsai, Timothy Miller, Dongfang Xu, Carol Anderson, Bo Liu, Qing Han, Jinfeng Zhang, Igor Kulev, Berkay Köprü, Raul Rodriguez-Esteban, Elif Ozkirimli, Ammer Ayach, Roland Roller, Stephen R. Piccolo, Peijin Han, V. G. Vinod Vydiswaran, Ramya Tekumalla, Juan M. Banda, Parsa Bagherzadeh, Sabine Bergler, João Figueira Silva, Tiago Melo Almeida, Paloma Martínez, Renzo M. Rivera Zavala, Chen-Kai Wang, Hong-Jie Dai, Luis Alberto Robles Hernandez, Graciela Gonzalez-Hernandez
2023 conf
HCI (50)
Ramya Tekumalla, Juan M. Banda
2023 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
2023 B conf
IEEE Big Data
Ramya Tekumalla, Luis Alberto Robles Hernandez, Juan M. Banda
2023 J jnl
Neural Comput. Appl.
Ramya Tekumalla, Juan M. Banda
2022 B conf
IEEE Big Data
Ramya Tekumalla, Juan M. Banda
2022 conf
ICWSM Workshops
Ramya Tekumalla, Zia Baig, Michelle Pan, Luis Alberto Robles Hernandez, Michael Wang, Juan M. Banda
2022 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
2022 B conf
IEEE Big Data
Ramya Tekumalla, Juan M. Banda
2022 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
2020 J jnl
CoRR
Juan M. Banda, Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Gerardo Chowell
2020 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
2020 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
2020 conf
NLP4COVID@EMNLP
Ramya Tekumalla, Juan M. Banda
2020 A conf
ICWSM
Ramya Tekumalla, Javad Rafiei Asl, Juan M. Banda
2020 J jnl
CoRR
Ramya Tekumalla, Juan M. Banda
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"