Omar Sharif

52 papers A* 2A 3B 1C 1Journal 29Unranked 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Omar Sharif, Eftekhar Hossain, Patrick Ng
2026 J jnl
J. Imaging
Md Easin Hasan, Md. Tahmid Hasan Fuad, Omar Sharif, Amy Wagler
2025 A conf
DATE
Omar Sharif, Christos-Savvas Bouganis
2025 conf
ACL (Findings)
Kawsar Ahmed, Md Osama, Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
2025 conf
ACL (1)
Joseph Gatto, Omar Sharif, Parker Seegmiller, Sarah Masud Preum
2025 conf
EMNLP (Findings)
Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah Masud Preum
2025 J jnl
CoRR
Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah M. Preum
2025 J jnl
CoRR
Madhusudan Basak, Omar Sharif, Jessica Hulsey, Elizabeth C. Saunders, Daisy J. Goodman, Luke J. ArchiBald, Sarah M. Preum
2024 A conf
DATE
Omar Sharif, Christos-Savvas Bouganis
2024 conf
EACL (1)
Shawly Ahsan, Eftekhar Hossain, Omar Sharif, Avishek Das, Mohammed Moshiul Hoque, M. Ali Akber Dewan
2024 J jnl
CoRR
Madhusudan Basak, Omar Sharif, Sarah E. Lord, Jacob T. Borodovsky, Lisa A. Marsch, Sandra A. Springer, Edward Nunes, Charlie D. Brackett, Luke J. ArchiBald, Sarah M. Preum
2024 conf
EACL (Student Research Workshop)
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Sarah Masud Preum
2024 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Sarah Masud Preum
2024 A* conf
AAAI
Omar Sharif, Madhusudan Basak, Tanzia Parvin, Ava Scharfstein, Alphonso Bradham, Jacob T. Borodovsky, Sarah E. Lord, Sarah Masud Preum
2024 conf
ACL (1)
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Sarah Masud Preum
2024 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Sarah Masud Preum
2024 J jnl
CoRR
Parker Seegmiller, Joseph Gatto, Omar Sharif, Madhusudan Basak, Sarah Masud Preum
2024 A* conf
EMNLP
Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah Masud Preum
2024 J jnl
CoRR
Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah M. Preum
2024 J jnl
CoRR
Joseph Gatto, Parker Seegmiller, Omar Sharif, Sarah Masud Preum
2024 conf
PAKDD (3)
Morteza Mohammady Gharasuie, Fengjiao Wang, Omar Sharif, Ravi Mukkamala
2024 A conf
ICWSM
William Romano, Omar Sharif, Madhusudan Basak, Joseph Gatto, Sarah Masud Preum
2023 conf
EMNLP (Findings)
Joseph Gatto, Omar Sharif, Sarah Preum
2023 J jnl
CoRR
Joseph Gatto, Omar Sharif, Sarah Masud Preum
2023 J jnl
CoRR
Omar Sharif, Madhusudan Basak, Tanzia Parvin, Ava Scharfstein, Alphonso Bradham, Jacob T. Borodovsky, Sarah E. Lord, Sarah Masud Preum
2023 J jnl
IEEE Access
Avishek Das, Mohammed Moshiul Hoque, Omar Sharif, M. Ali Akber Dewan, Nazmul H. Siddique
2023 J jnl
CoRR
Joseph Gatto, Omar Sharif, Parker Seegmiller, Philip Bohlman, Sarah Masud Preum
2023 J jnl
CoRR
William Romano, Omar Sharif, Madhusudan Basak, Joseph Gatto, Sarah Masud Preum
2022 J jnl
J. Heal. Informatics Res.
Omar Sharif, Md. Rafiqul Islam, Md Zobaer Hasan, Muhammad Ashad Kabir, Md Emran Hasan, Salman A. AlQahtani, Guandong Xu
2022 J jnl
SN Comput. Sci.
Md. Asif Iqbal, Avishek Das, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2022 J jnl
SN Comput. Sci.
Md. Mashiur Rahaman Mamun, Omar Sharif, Mohammed Moshiul Hoque
2022 J jnl
J. King Saud Univ. Comput. Inf. Sci.
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, M. Ali Akber Dewan, Nazmul H. Siddique, Md. Azad Hossain
2022 conf
AACL/IJCNLP 2022 (Student Research Workshop)
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2022 B conf
LREC
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2022 J jnl
SN Comput. Sci.
Tanzia Parvin, Omar Sharif, Mohammed Moshiul Hoque
2022 J jnl
Neurocomputing
Omar Sharif, Mohammed Moshiul Hoque
2021 conf
ICO
Fatima Jahara, Omar Sharif, Mohammed Moshiul Hoque
2021 J jnl
CoRR
Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
2021 conf
NAACL-HLT (Student Research Workshop)
Avishek Das, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2021 J jnl
CoRR
Avishek Das, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2021 conf
CONSTRAINT@AAAI
Omar Sharif, Mohammed Moshiul Hoque
2021 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2021 J jnl
CoRR
Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
2021 conf
LT-EDI@EACL
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2021 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2020 conf
ICO
Avishek Das, Md. Asif Iqbal, Omar Sharif, Mohammed Moshiul Hoque
2020 C conf
HIS
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2020 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2020 J jnl
CoRR
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
2020 J jnl
CoRR
Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
2020 conf
ICO
Fatima Jahara, Adrita Barua, Md. Asif Iqbal, Avishek Das, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
2019 conf
ICO
Omar Sharif, Mohammed Moshiul Hoque
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"