James W. O'Toole Jr.

20 papers A* 8A 1B 1Journal 1Unranked 8
YearRankTypeTitle / Venue / Authors
2000 A* conf
OSDI
John Jannotti, David K. Gifford, Kirk L. Johnson, M. Frans Kaashoek, James W. O'Toole Jr.
1996 conf
POS
Scott Nettles, James W. O'Toole Jr.
1996
James W. O'Toole Jr.
1995 A* conf
SOSP
Dawson R. Engler, M. Frans Kaashoek, James W. O'Toole Jr.
1995 A conf
HotOS
James W. O'Toole Jr., Liuba Shrira
1995 J jnl
ACM SIGOPS Oper. Syst. Rev.
Dawson R. Engler, M. Frans Kaashoek, James W. O'Toole Jr.
1994 conf
ACM SIGOPS European Workshop
James W. O'Toole Jr., Liuba Shrira
1994 conf
LISP and Functional Programming
James W. O'Toole Jr., Scott Nettles
1994 B conf
EDBT
Mark A. Sheldon, Andrzej Duda, Ron Weiss, James W. O'Toole Jr., David K. Gifford
1994 conf
POS
James W. O'Toole Jr., Liuba Shrira
1994 A* conf
OSDI
James W. O'Toole Jr., Liuba Shrira
1994 A* conf
OSDI
Dawson R. Engler, M. Frans Kaashoek, James W. O'Toole Jr.
1994 conf
ACM SIGOPS European Workshop
Dawson R. Engler, M. Frans Kaashoek, James W. O'Toole Jr.
1993 A* conf
SOSP
James W. O'Toole Jr., Scott Nettles, David K. Gifford
1993 A* conf
PLDI
Scott Nettles, James W. O'Toole Jr.
1992 conf
ACM SIGOPS European Workshop
James W. O'Toole Jr., David K. Gifford
1992 conf
IWMM
Scott Nettles, James W. O'Toole Jr., David Pierce
1991 conf
Operating Systems of the 90s and Beyond
David K. Gifford, James W. O'Toole Jr.
1991 A* conf
SOSP
David K. Gifford, Pierre Jouvelot, Mark A. Sheldon, James W. O'Toole Jr.
1989 A* conf
PLDI
James W. O'Toole Jr., David K. Gifford
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"