Maciej Komosinski

39 papers A 4B 2C 3Misc 1Journal 15Unranked 13
YearRankTypeTitle / Venue / Authors
2025 A conf
GECCO
Maciej Komosinski, Agnieszka Mensfelt
2025 conf
GECCO Companion
Maciej Komosinski, Konrad Miazga
2024 conf
GECCO Companion
Maciej Komosinski, Marcin Leszczynski, Konrad Miazga, Dawid Siera
2024 A conf
GECCO
Maciej Komosinski, Agnieszka Mensfelt
2024 A conf
GECCO
Sofya Aksenyuk, Szymon Bujowski, Maciej Komosinski, Konrad Miazga
2023 conf
GECCO Companion
Maciej Komosinski, Konrad Miazga
2022 conf
GECCO Companion
Adam Klejda, Maciej Komosinski, Agnieszka Mensfelt
2022 conf
GECCO Companion
Kamil Basiukajc, Maciej Komosinski, Konrad Miazga
2021 B conf
CEC
Piotr Kaszuba, Maciej Komosinski, Agnieszka Mensfelt
2021 C conf
ALIFE
Maciej Komosinski, Konrad Miazga
2019 B conf
EvoApplications
Maciej Komosinski, Agnieszka Mensfelt
2019 J jnl
J. Comput. Sci.
Maciej Komosinski, Konrad Miazga
2019 C conf
ALIFE
Maciej Komosinski, Konrad Miazga
2019 A conf
GECCO
Maciej Komosinski, Konrad Miazga
2017 J jnl
J. Comput. Sci.
Maciej Komosinski
2017 J jnl
ACM Trans. Comput. Log.
Szymon Chlebowski, Maciej Komosinski, Adam Kups
2017 J jnl
J. Comput. Sci.
Pawel Topa, Lukasz Faber, Jaroslaw Tyszka, Maciej Komosinski
2017 J jnl
J. Comput. Sci.
Maciej Komosinski, Agnieszka Mensfelt, Jaroslaw Tyszka, Jan Golen
2017 J jnl
J. Supercomput.
Maciej Komosinski, Szymon Ulatowski
2017 conf
PPAM (2)
Maciej Komosinski, Konrad Miazga
2015 Misc conf
ICCS
Maciej Kazirod, Wojciech Korczynski, Elias Fernández, Aleksander Byrski, Marek Kisiel-Dorohinicki, Pawel Topa, Jaroslaw Tyszka, Maciej Komosinski
2015 conf
ICMMI
Maciej Komosinski, Agnieszka Mensfelt, Pawel Topa, Jaroslaw Tyszka
2015 conf
ICMMI
Pawel Topa, Maciej Komosinski, Maciej Bassara, Jaroslaw Tyszka
2015 conf
PPAM (2)
Pawel Topa, Maciej Komosinski, Jaroslaw Tyszka, Agnieszka Mensfelt, Sebastian Rokitta, Aleksander Byrski, Maciej Bassara
2014 J jnl
ACM Trans. Comput. Log.
Maciej Komosinski, Adam Kups, Dorota Leszczynska-Jasion, Mariusz Urbanski
2012 J jnl
Theory Biosci.
Maciej Komosinski
2011 J jnl
Bio Algorithms Med Syst.
Maciej Komosinski, Adam Kups
2011 J jnl
Complex.
Maciej Komosinski, Marek Kubiak
2009 book
Andrew Adamatzky, Maciej Komosinski
2008 J jnl
Artif. Life
Wojciech Jaskowski, Maciej Komosinski
2006 conf
KES (3)
Jacek Jelonek, Maciej Komosinski
2004 J jnl
Theory Biosci.
Maciej Komosinski, Szymon Ulatowski
2001 J jnl
Artif. Life
Ádám Rotaru-Varga, Maciej Komosinski
2001 J jnl
Theory Biosci.
Maciej Komosinski, Grzegorz Koczyk, Marek Kubiak
2001 conf
ECAL
Maciej Komosinski, Marek Kubiak
2000 J jnl
Artif. Intell. Medicine
Maciej Komosinski, Krzysztof Krawiec
2000 conf
Virtual Worlds
Maciej Komosinski
1999 conf
ECAL
Maciej Komosinski, Szymon Ulatowski
1999 C conf
ISMIS
Jacek Jelonek, Maciej Komosinski
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"