Isha Puri

14 papers A* 2Journal 10Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Isha Puri, Mehul Damani, Idan Shenfeld, Marzyeh Ghassemi, Jacob Andreas, Yoon Kim
2025 J jnl
CoRR
Isha Puri, Shivchander Sudalairaj, Guangxuan Xu, Kai Xu, Akash Srivastava
2025 J jnl
CoRR
Isha Puri, David D. Cox
2025 J jnl
CoRR
Mehul Damani, Isha Puri, Stewart Slocum, Idan Shenfeld, Leshem Choshen, Yoon Kim, Jacob Andreas
2025 J jnl
CoRR
Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Kartikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2025 J jnl
CoRR
Yuexing Hao, Kumail Alhamoud, Hyewon Jeong, Haoran Zhang, Isha Puri, Philip Torr, Mike Schaekermann, Ariel Dora Stern, Marzyeh Ghassemi
2024 conf
EMNLP (Findings)
Saadia Gabriel, Isha Puri, Xuhai Xu, Matteo Malgaroli, Marzyeh Ghassemi
2024 J jnl
CoRR
Saadia Gabriel, Isha Puri, Xuhai Xu, Matteo Malgaroli, Marzyeh Ghassemi
2024 J jnl
CoRR
Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen
2024 J jnl
Trans. Mach. Learn. Res.
Kyle O'Brien, Nathan Hoyen Ng, Isha Puri, Jorge Mendez-Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen
2022 A* conf
NeurIPS
Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
2022 J jnl
CoRR
Chirag Agarwal, Eshika Saxena, Satyapriya Krishna, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
2021 A* conf
NeurIPS
Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2018 conf
EMBC
Isha Puri, David D. Cox
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"