Oleksandr A. Letychevskyi

24 papers A 1Misc 3Journal 2Unranked 18
YearRankTypeTitle / Venue / Authors
2023 conf
IDAACS
Oleksandr A. Letychevskyi, Yuliia Tarasich, Volodymyr Peschanenko
2023 conf
DESSERT
Oleg Odarushchenko, Oleksiy Striuk, Viacheslav Shamanskyi, Oleksandr A. Letychevskyi, Aleksandr Ivasiuk, Elena Odarushchenko
2022 conf
IntelITSIS
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Serhii Horbatiuk
2021 conf
ICTERI (Revised Selected Papers)
Oleksandr A. Letychevskyi, Yuliia Tarasich, Volodymyr Peschanenko, Vladislav Volkov, Hanna Sokolova, Maksym Poltoratskiy
2021 conf
ICTERI (Revised Selected Papers)
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Vlad Volkov
2021 conf
IDAACS
Serhii Naumenko, Viktoriia Moskalets, Oleg Odarushchenko, Elena Odarushchenko, Volodymyr Peschanenko, Larysa Degtyareva, Oleksandr A. Letychevskyi
2020 conf
IDAACS-SWS
Oleksandr A. Letychevskyi, Serhii Horbatiuk, Viktor Horbatiuk
2020 conf
IEEE BigData
Oleksandr A. Letychevskyi, Yaroslav Hryniuk
2020 conf
ICTERI Workshops
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Maksym Poltoratskiy, Yuliia Tarasich
2019 conf
IECC
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Viktor Radchenko, Maxim Orlovsky, Andrey Sobol
2019 J jnl
ISC Int. J. Inf. Secur.
Oleksandr A. Letychevskyi, Yaroslav Hryniuk, Viktor Yakovlev, Volodymyr Peschanenko, Viktor Radchenko
2019 conf
DESSERT
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Viktor Radchenko, Yaroslav Hryniuk, Viktor Yakovlev
2019 conf
IEEE BigData
Oleksandr A. Letychevskyi, Tetiana Polhul
2019 conf
ICTERI Workshops
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Viktor Radchenko, Maksym Poltoratskiy, Yulia Tarasich
2019 conf
ICTERI (Revised Selected Papers)
Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Maksym Poltoratskiy, Yulia Tarasich
2019 conf
ICTERI Workshops
Andrey Sobol, Volodymyr G. Skobelev, Julian Konchunas, Viktor Radchenko, Sabina Sachtachtinskagia, Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Maxim Orlovsky
2019 conf
IDAACS
Oleksandr A. Letychevskyi
2017 conf
RE Workshops
Alexander A. Letichevsky, Oleksandr A. Letychevskyi, Vladimir S. Peschanenko, Maxsim Poltorackij
2017 Misc conf
ICTERI
Alexander Godlevskyi, Aleksander Letichevskyi, Vladimir S. Peschanenko, Oleksandr A. Letychevskyi, Maryna Morokhovets, Volodymyr G. Skobelev, Maksym Poltorackiy
2017 Misc conf
ICTERI
Michael Lvov, Vladimir S. Peschanenko, Oleksandr A. Letychevskyi, Yulia Tarasich
2016 J jnl
Comput. Sci. J. Moldova
Alexander A. Letichevsky, Oleksandr A. Letychevskyi, Vladimir S. Peschanenko
2015 Misc conf
ICTERI
Alexander A. Letichevsky, Oleksandr A. Letychevskyi, Vladimir S. Peschanenko
2015 conf
SDL Forum
Alexander A. Letichevsky, Oleksandr A. Letychevskyi, Volodymyr Peschanenko, Thomas Weigert
2014 A conf
RE
Oleksandr A. Letychevskyi, Thomas Weigert
redb/extractors/js_extractors/js_suspicious_apis.py
← Index redb/extractors/js_extractors/js_suspicious_apis.py python
import inspect
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 CATEGORIES, PATTERNS


# Backwards-compatible export: `{category: [(raw_pattern_string, api_name), ...]}`
# in canonical PATTERNS insertion order (code_execution, network, filesystem,
# process, registry, crypto_encoding, dom_manipulation). Kept so external
# callers (notably JSDeobfuscationExtractor pre-cleanup) keep working until
# they are migrated to PATTERNS directly.
SUSPICIOUS_APIS: "dict[str, list[tuple[str, str]]]" = {}
for _name, _compiled in PATTERNS.items():
    SUSPICIOUS_APIS.setdefault(CATEGORIES[_name], []).append((_compiled.pattern, _name))


class JSSuspiciousAPIsExtractor(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.api_findings = None
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _get_context_snippet(self, line, max_len=200):
        """Get a truncated context snippet around a match."""
        line = line.strip()
        if len(line) > max_len:
            return line[:max_len] + "..."
        return line

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

        # Pass 1: shared per-sample scan over the raw source. The dict contains
        # entries for both PATTERNS and FEATURE_PATTERNS; the loop below only
        # consults PATTERNS keys, so feature-only entries are ignored.
        raw_scan = self._context.scan or {}
        raw_lines = self.lines

        # Pass 2: same patterns over the deobfuscated text, when the
        # deobfuscator produced something meaningfully different. APIs hidden
        # behind one obfuscation layer (Vjw0rm-style array.join + eval,
        # Dean-Edwards packers, jjencode, ...) only surface here. The scan is
        # cached on JSContext so JSDeobfuscationExtractor (which computes the
        # new_apis_found diff) reuses the same result.
        deobf_scan = self._context.scan_deobfuscated
        if deobf_scan:
            deobf_text, _ = self._context.deobfuscated
            deobf_lines = deobf_text.splitlines()
        else:
            deobf_lines = []

        findings = []
        # Iterate PATTERNS in canonical order so output is deterministic and
        # matches the historical category/pattern ordering. For each api_name,
        # raw findings take precedence; if an API is found only in the
        # deobfuscated text, we surface it as a row tagged revealed_by_deobf=1
        # with line numbers / snippets pulled from the deobfuscated source.
        for api_name in PATTERNS:
            raw_info = raw_scan.get(api_name)
            if raw_info:
                line_numbers = raw_info["lines"]
                lines_for_snippets = raw_lines
                revealed_by_deobf = 0
            else:
                deobf_info = deobf_scan.get(api_name)
                if not deobf_info:
                    continue
                line_numbers = deobf_info["lines"]
                lines_for_snippets = deobf_lines
                revealed_by_deobf = 1

            snippets = [
                self._get_context_snippet(lines_for_snippets[ln - 1])
                for ln in line_numbers[:3]
                if 0 < ln <= len(lines_for_snippets)
            ]
            findings.append({
                "api_name": api_name,
                "api_category": CATEGORIES[api_name],
                # Historical semantics: count = number of unique lines with a
                # match, not total in-source match count.
                "call_count": len(line_numbers),
                "line_numbers": line_numbers,
                "context_snippet": " | ".join(snippets),
                "revealed_by_deobf": revealed_by_deobf,
            })

        if not findings:
            return None

        self.api_findings = findings
        return findings

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

            current_time = datetime.now(timezone.utc)
            data = []
            for f in self.api_findings:
                data.append([
                    self.sha256,
                    f['api_name'],
                    f['api_category'],
                    f['call_count'],
                    f['line_numbers'],
                    f['context_snippet'],
                    f['revealed_by_deobf'],
                    current_time,
                ])

            column_names = [
                "sha256", "api_name", "api_category",
                "call_count", "line_numbers", "context_snippet",
                "revealed_by_deobf",
                "analysis_date",
            ]

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

            return (data, column_names, column_type_names)

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