Ram Shringar Raw

42 papers Journal 30Unranked 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
SN Comput. Sci.
Ashish Kumari, Shailender Kumar, Ram Shringar Raw, Navdeep Bohra
2024 J jnl
J. Supercomput.
Ashish Kumari, Shailender Kumar, Ram Shringar Raw
2024 J jnl
Sensors
Priyanka Gaba, Ram Shringar Raw, Omprakash Kaiwartya, Mohammad Aljaidi
2024 J jnl
Clust. Comput.
Ashish Kumari, Shailender Kumar, Ram Shringar Raw
2024 J jnl
Sensors
Manish Kumar, Ram Shringar Raw
2023 J jnl
Clust. Comput.
Arun Kumar Yadav, Ram Shringar Raw, Rajendra Kumar Bharti
2023 J jnl
J. Ambient Intell. Humaniz. Comput.
Kamlesh Kumar Rana, Sachin Tripathi, Ram Shringar Raw
2023 J jnl
Trans. Emerg. Telecommun. Technol.
Priyanka Gaba, Ram Shringar Raw
2023 J jnl
Int. J. Commun. Syst.
Sudesh Kumar, Ram Shringar Raw, Abhishek Bansal
2023 J jnl
Trans. Emerg. Telecommun. Technol.
Sudesh Kumar, Ram Shringar Raw, Abhishek Bansal, Pawan Singh
2022 J jnl
Peer-to-Peer Netw. Appl.
Priyanka Gaba, Ram Shringar Raw
2022 J jnl
IEEE Access
Priyanka Gaba, Ram Shringar Raw, Mazin Abed Mohammed, Jan Nedoma, Radek Martinek
2022 J jnl
J. Ambient Intell. Humaniz. Comput.
Pawan Singh, Ram Shringar Raw, Suhel Ahmad Khan
2022 J jnl
IEEE Access
Pawan Singh, Ram Shringar Raw, Suhel Ahmad Khan, Mazin Abed Mohammed, Ayman A. Aly, Dac-Nhuong Le
2021 J jnl
IEEE Access
Sudesh Kumar, Ram Shringar Raw, Abhishek Bansal, Mazin Abed Mohammed, Pattaraporn Khuwuthyakorn, Orawit Thinnukool
2020 J jnl
J. Ambient Intell. Humaniz. Comput.
Kamlesh Kumar Rana, Sachin Tripathi, Ram Shringar Raw
2020 J jnl
Peer-to-Peer Netw. Appl.
Kamlesh Kumar Rana, Sachin Tripathi, Ram Shringar Raw
2020 J jnl
Wirel. Pers. Commun.
Kamlesh Kumar Rana, Sachin Tripathi, Ram Shringar Raw
2018 J jnl
Wirel. Pers. Commun.
Kamlesh Kumar Rana, Sachin Tripathi, Ram Shringar Raw
2018 J jnl
Wirel. Pers. Commun.
Ahmed Nazar Hassan, Omprakash Kaiwartya, Abdul Hanan Abdullah, Dalya Khalid Sheet, Ram Shringar Raw
2017 J jnl
Wirel. Pers. Commun.
Rupender Singh, Sanjay Kumar Soni, Ram Shringar Raw, Sandeep Kumar
2017 J jnl
Int. J. Commun. Syst.
Kavita Pandey, Saurabh Kumar Raina, Ram Shringar Raw, Buddha Singh
2016 conf
ICTCS
Harsh Kumar Singh, Ram Shringar Raw, Sanjeev Kumar, Arvind Kumar Singh, Sanjay Kumar Soni
2016 conf
ICTCS
Ram Shringar Raw, Loveleen, Arvind Kumar, Arushi Kadam, Nanhay Singh
2016 J jnl
Int. J. Commun. Networks Distributed Syst.
Kavita Pandey, Saurabh Kumar Raina, Ram Shringar Raw
2016 conf
ICTCS
Pradeep Kamboj, Ram Shringar Raw, Anil Kumar Gautam
2016 conf
ICTCS
Varun Prabahkar, Annapurna Singh, Ram Shringar Raw
2016 conf
ICTCS
Lincolin Nhapi, Arun Kumar Yadav, Ram Shringar Raw
2015 J jnl
Int. J. Comput. Appl. Technol.
Ram Shringar Raw, Daya Krishan Lobiyal, Sanjoy Das
2015 J jnl
Wirel. Pers. Commun.
Ram Shringar Raw, D. K. Lobiyal, Sanjoy Das, Sushil Kumar
2014 J jnl
CoRR
Rajesh Kumar, Sushil Kumar, Diksha Shukla, Ram Shringar Raw
2014 J jnl
Wirel. Pers. Commun.
Rajesh Kumar, Sushil Kumar, Diksha Shukla, Ram Shringar Raw, Omprakash Kaiwartya
2013 conf
ICACNI
Ram Shringar Raw, Shailender Kumar, Sonia Mann, Sambit Bakshi
2013 conf
ICACNI
Nanhay Singh, Achin Jain, Ram Shringar Raw, Rahul Raman
2013 conf
ICACCI
Nanhay Singh, Arvind Panwar, Ram Shringar Raw
2013 J jnl
Wirel. Pers. Commun.
Ram Shringar Raw, Sanjoy Das
2013 conf
ICACNI
Sanjoy Das, Ram Shringar Raw, Indrani Das, Rajib Sarkar
2012 conf
SNDS
Ram Shringar Raw, Daya Krishan Lobiyal, Sanjoy Das
2012 conf
ACITY (2)
Ram Shringar Raw, Vikas Toor, N. Singh
2012 J jnl
CoRR
Ram Shringar Raw, Sanjoy Das, Nanhay Singh, Sanjeet Kumar, Shailender Kumar
2011 J jnl
Int. J. Inf. Commun. Technol.
Ram Shringar Raw, D. K. Lobiyal
2011 conf
ACC (3)
Ram Shringar Raw, D. K. Lobiyal
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"