Verena Henrich

21 papers A 1B 6C 1Misc 2Journal 2Unranked 8
YearRankTypeTitle / Venue / Authors
2017 conf
EACL (Software Demonstrations)
Verena Henrich, Alexander Lang
2016 conf
SIGMORPHON
Jianqiang Ma, Verena Henrich, Erhard W. Hinrichs
2015
Verena Henrich
2014 C conf
GWC
Verena Henrich, Erhard W. Hinrichs, Reinhild Barkey
2014 B conf
LREC
Corina Dima, Verena Henrich, Erhard W. Hinrichs, Christina Hoppermann
2013 conf
GSCL
Verena Henrich, Erhard W. Hinrichs
2013 J jnl
Lang. Resour. Evaluation
Erhard W. Hinrichs, Verena Henrich, Reinhild Barkey
2012 B conf
LREC
Verena Henrich, Erhard W. Hinrichs
2012 B conf
LREC
Emanuel Dima, Verena Henrich, Erhard W. Hinrichs, Marie Hinrichs, Christina Hoppermann, Thorsten Trippel, Thomas Zastrow, Claus Zinn
2012 conf
DH
Anne Brock, Verena Henrich, Erhard W. Hinrichs, Yannick Versley
2012 J jnl
J. Lang. Technol. Comput. Linguistics
Verena Henrich, Erhard W. Hinrichs, Klaus Suttner
2012 conf
KONVENS
Yannick Versley, Anne Brock, Verena Henrich, Erhard W. Hinrichs
2012 conf
SPMRL@ACL 2012
Yannick Versley, Verena Henrich
2012 A conf
EACL
Verena Henrich, Erhard W. Hinrichs, Tatiana Vodolazova
2011 conf
LTC
Verena Henrich, Erhard W. Hinrichs, Tatiana Vodolazova
2011 Misc conf
RANLP
Verena Henrich, Erhard W. Hinrichs
2010 conf
ACL (System Demonstrations)
Verena Henrich, Erhard W. Hinrichs
2010 B conf
LREC
Verena Henrich, Erhard W. Hinrichs
2010 B conf
COLING
Verena Henrich, Erhard W. Hinrichs
2010 B conf
LREC
Erhard W. Hinrichs, Verena Henrich, Thomas Zastrow
2009 Misc conf
FLAIRS
Verena Henrich, Timo Reuter, Hrafn Loftsson
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"