Naveen Saini

38 papers A 2B 5C 1Journal 20Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Knowl. Based Syst.
Jiten Parmar, Naveen Saini, Dhananjoy Dey, Diego Oliva, Omkeshwar
2026 J jnl
IEEE Access
Supreeth D. K., Siddappa I. Bekinal, Naveen Saini, Krishna Pratap Singh
2026 J jnl
Swarm Evol. Comput.
Anubhav Singh, Naveen Saini, Konstantinos Zervoudakis, Vikas Kumar Tiwari
2026 J jnl
J. Supercomput.
Yashwant Pravinrao Bangde, Naveen Saini, Vikas Kumar Tiwari
2024 B conf
CEC
Jiten Parmar, Naveen Saini, Dhananjoy Dey
2024 J jnl
IEEE Trans. Affect. Comput.
Diksha Bansal, Rahul Grover, Naveen Saini, Sriparna Saha
2024 conf
ICPR (19)
Shreya Goswami, Naveen Saini, Saurabh Shukla
2024 conf
ICPR (1)
Yashwant Pravinrao Bangde, Naveen Saini
2023 A conf
CIKM
Raghvendra Kumar, Ratul Chakraborty, Abhishek Tiwari, Sriparna Saha, Naveen Saini
2023 conf
ECIR (2)
Vishal Singh Roha, Naveen Saini, Sriparna Saha, José G. Moreno
2023 J jnl
Appl. Intell.
Naveen Saini, Saichethan Miriyala Reddy, Sriparna Saha, José G. Moreno, Antoine Doucet
2022 J jnl
Appl. Intell.
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2022 J jnl
IEEE Trans. Comput. Soc. Syst.
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya, Shubhankar Mrinal, Santosh Kumar Mishra
2022 J jnl
Appl. Intell.
Santosh Kumar Mishra, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2022 A conf
GECCO
Vishal Singh Roha, Naveen Saini, Sriparna Saha, José G. Moreno
2021 J jnl
IEEE Access
Diksha Bansal, Naveen Saini, Sriparna Saha
2021 C conf
NLDB
Santosh Kumar Mishra, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2021 B conf
SMC
Anuj Shastri, Naveen Saini, Sriparna Saha, Santosh Kumar Mishra
2021 J jnl
Expert Syst. Appl.
Naveen Saini, Diksha Bansal, Sriparna Saha, Pushpak Bhattacharyya
2021 conf
PAKDD (Workshops)
Saichethan Miriyala Reddy, Naveen Saini
2020 conf
ICONIP (1)
Naveen Saini, Sriparna Saha, Sahil Mansoori, Pushpak Bhattacharyya
2020 J jnl
Appl. Intell.
Naveen Saini, Sriparna Saha, Chirag Soni, Pushpak Bhattacharyya
2020 J jnl
Soft Comput.
Naveen Saini, Sriparna Saha, Sahil Mansoori, Pushpak Bhattacharyya
2020 conf
SDP@EMNLP
Saichethan Miriyala Reddy, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2020 conf
SDP@EMNLP
Santosh Kumar Mishra, Harshavardhan Kundarapu, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2020 B conf
CEC
Naveen Saini, Sushil Kumar, Sriparna Saha, Pushpak Bhattacharyya
2020 B conf
ICPR
Naveen Saini, Sushil Kumar, Sriparna Saha, Pushpak Bhattacharyya
2020 J jnl
ACM Trans. Multim. Comput. Commun. Appl.
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya, Himanshu Tuteja
2019 J jnl
Cogn. Comput.
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2019 J jnl
Knowl. Based Syst.
Naveen Saini, Sriparna Saha, Anubhav Jangra, Pushpak Bhattacharyya
2019 J jnl
IEEE Intell. Syst.
Naveen Saini, Sriparna Saha, Vedavikas Potnuru, Rahul Grover, Pushpak Bhattacharyya
2019 conf
PReMI (1)
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2019 conf
ICONIP (5)
Naveen Saini, Sriparna Saha, Anurag Kumar, Pushpak Bhattacharyya
2019 J jnl
IEEE Trans. Comput. Soc. Syst.
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2019 J jnl
Aust. J. Intell. Inf. Process. Syst.
Naveen Saini, Rahul Grover, Sriparna Saha, Pushpak Bhattacharyya
2019 J jnl
Appl. Intell.
Naveen Saini, Sriparna Saha, Aditya Harsh, Pushpak Bhattacharyya
2018 B conf
IJCNN
Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
2017 conf
ICONIP (6)
Naveen Saini, Shubham Chourasia, Sriparna Saha, Pushpak Bhattacharyya
redb/extractors/js_extractors/js_strings.py
← Index redb/extractors/js_extractors/js_strings.py python
import base64
import bisect
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 STRING_PATTERNS, line_offsets

# Local aliases for the compiled patterns this extractor uses. Defined and
# compiled exactly once in js_patterns.STRING_PATTERNS.
_HEX_STRING_RE = STRING_PATTERNS["hex_escape_seq"]
_UNICODE_STRING_RE = STRING_PATTERNS["unicode_escape_seq"]
_CHARCODE_RE = STRING_PATTERNS["charcode_call"]
_BASE64_STRING_RE = STRING_PATTERNS["base64_quoted"]
_CONCAT_STRING_RE = STRING_PATTERNS["concat_chain"]

# Tokeniser used inside _reconstruct_concat to pull each quoted part out of a
# matched concat chain. Compiled once at module load (was recompiled on every
# concat match before).
_CONCAT_TOKEN_RE = re.compile(r'["\']([^"\']*)["\']')


class JSStringsExtractor(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.string_findings = None
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _decode_hex_string(self, hex_str):
        """Decode \\x41\\x42 style hex strings."""
        try:
            # Remove \\x prefix and decode
            clean = hex_str.replace('\\x', '')
            return bytes.fromhex(clean).decode('utf-8', errors='replace')
        except Exception:
            return None

    def _decode_unicode_string(self, uni_str):
        """Decode \\u0041\\u0042 style unicode strings."""
        try:
            return uni_str.encode('utf-8').decode('unicode_escape')
        except Exception:
            return None

    def _decode_charcode(self, charcode_str):
        """Decode String.fromCharCode(72, 101, 108, ...) sequences."""
        try:
            codes = [int(c.strip()) for c in charcode_str.split(',') if c.strip().isdigit()]
            return ''.join(chr(c) for c in codes if 0 <= c <= 0x10FFFF)
        except Exception:
            return None

    def _decode_base64(self, b64_str):
        """Attempt to decode base64 string."""
        try:
            decoded = base64.b64decode(b64_str)
            # Check if result is printable text
            text = decoded.decode('utf-8', errors='strict')
            # Only return if it looks like text (>80% printable)
            printable = sum(1 for c in text if c.isprintable() or c in '\n\r\t')
            if printable / len(text) > 0.8:
                return text
        except Exception:
            pass
        return None

    def _reconstruct_concat(self, concat_match):
        """Reconstruct concatenated string parts."""
        try:
            parts = _CONCAT_TOKEN_RE.findall(concat_match)
            return ''.join(parts)
        except Exception:
            return None

    def _find_line_number(self, match_start):
        """1-indexed line number for `match_start`, looked up in O(log L) via
        bisect over `self._line_offsets` (built once per extract() call).

        Replaces the historical `self.js_source[:match_start].count('\\n') + 1`
        which was O(N) per call and quadratic across all matches in a sample.
        """
        return bisect.bisect_right(self._line_offsets, match_start)

    def _scan_text(self, text):
        """Run every encoded-string pattern over `text` and return a list of
        finding dicts. Stateless apart from the per-call `_line_offsets` cache,
        which `_find_line_number` reads — callers must reset it before invoking
        this so line numbers reference the text being scanned, not the previous
        one.
        """
        findings = []

        # Hex-encoded strings
        for m in _HEX_STRING_RE.finditer(text):
            raw = m.group()
            decoded = self._decode_hex_string(raw)
            if decoded and len(decoded) >= 4:
                findings.append({
                    'string': decoded[:4000],
                    'string_raw': raw[:4000],
                    'string_encoding': 'hex',
                    'string_offset': self._find_line_number(m.start()),
                    'string_length': len(decoded),
                    'string_raw_length': len(raw),
                    'string_entropy': self._calculate_text_entropy(decoded),
                })

        # Unicode-encoded strings
        for m in _UNICODE_STRING_RE.finditer(text):
            raw = m.group()
            decoded = self._decode_unicode_string(raw)
            if decoded and len(decoded) >= 3:
                findings.append({
                    'string': decoded[:4000],
                    'string_raw': raw[:4000],
                    'string_encoding': 'unicode',
                    'string_offset': self._find_line_number(m.start()),
                    'string_length': len(decoded),
                    'string_raw_length': len(raw),
                    'string_entropy': self._calculate_text_entropy(decoded),
                })

        # String.fromCharCode sequences
        for m in _CHARCODE_RE.finditer(text):
            raw = m.group()
            decoded = self._decode_charcode(m.group(1))
            if decoded and len(decoded) >= 4:
                findings.append({
                    'string': decoded[:4000],
                    'string_raw': raw[:4000],
                    'string_encoding': 'charcode',
                    'string_offset': self._find_line_number(m.start()),
                    'string_length': len(decoded),
                    'string_raw_length': len(raw),
                    'string_entropy': self._calculate_text_entropy(decoded),
                })

        # Base64-encoded strings
        for m in _BASE64_STRING_RE.finditer(text):
            raw = m.group(0)
            b64_val = m.group(1)
            decoded = self._decode_base64(b64_val)
            if decoded and len(decoded) >= 10:
                findings.append({
                    'string': decoded[:4000],
                    'string_raw': raw[:4000],
                    'string_encoding': 'base64',
                    'string_offset': self._find_line_number(m.start()),
                    'string_length': len(decoded),
                    'string_raw_length': len(raw),
                    'string_entropy': self._calculate_text_entropy(decoded),
                })

        # Concatenated strings (reassembled)
        for m in _CONCAT_STRING_RE.finditer(text):
            raw = m.group()
            reconstructed = self._reconstruct_concat(raw)
            if reconstructed and len(reconstructed) >= 20:
                findings.append({
                    'string': reconstructed[:4000],
                    'string_raw': raw[:4000],
                    'string_encoding': 'concat',
                    'string_offset': self._find_line_number(m.start()),
                    'string_length': len(reconstructed),
                    'string_raw_length': len(raw),
                    'string_entropy': self._calculate_text_entropy(reconstructed),
                })

        return findings

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

        # Pass 1: raw source. _line_offsets is keyed off whichever text is
        # currently being scanned so _find_line_number resolves to that text.
        self._line_offsets = line_offsets(src)
        findings = self._scan_text(src)

        # Pass 2: deobfuscated text, when the deobfuscator produced something
        # meaningfully different. Same patterns, but a different surface — for
        # samples where the encoded payload is hidden behind an outer wrapper
        # (e.g. array.join() + eval in Vjw0rm/WSH-RAT) only this pass yields
        # any rows at all.
        deobf_text, _ = self._context.deobfuscated
        if deobf_text and deobf_text != src:
            self._line_offsets = line_offsets(deobf_text)
            findings.extend(self._scan_text(deobf_text))

        if not findings:
            return None

        # Deduplicate by decoded string value (raw pass wins on collision: it
        # comes first in `findings`). A string that surfaces only in the
        # deobfuscated text still gets persisted, which is the whole point of
        # the second pass.
        seen_values = set()
        deduped = []
        for f in findings:
            val_key = f['string'][:100]
            if val_key not in seen_values:
                seen_values.add(val_key)
                deduped.append(f)

        self.string_findings = deduped[:500]  # Limit per file
        # Publish to the shared context so post-loop consumers (notably the IOC
        # plumbing in workers.py) can scrape the decoded strings without
        # holding a reference to this extractor instance.
        self._context.decoded_strings = self.string_findings
        return self.string_findings

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

            data = []
            for f in self.string_findings:
                data.append([
                    self.sha256,
                    f['string'],
                    f['string_raw'],
                    f['string_encoding'],
                    f['string_offset'],
                    f['string_length'],
                    f['string_raw_length'],
                    f['string_entropy'],
                ])

            column_names = [
                "sha256",
                "string",
                "string_raw",
                "string_encoding",
                "string_offset",
                "string_length",
                "string_raw_length",
                "string_entropy",
            ]

            column_type_names = [
                "FixedString(64)",
                "String",
                "String",
                "LowCardinality(String)",
                "UInt64",
                "UInt32",
                "UInt32",
                "Float32",
            ]

            return (data, column_names, column_type_names)

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