Rama Vuyyuru

25 papers A* 1B 2C 1Journal 4Unranked 17
YearRankTypeTitle / Venue / Authors
2015 B conf
WCNC
Hui Liu, Jialin He, Onur Altintas, Rama Vuyyuru, Joseph Camp, Dinesh Rajan
2014 conf
INFOCOM Workshops
Giulio Grassi, Davide Pesavento, Giovanni Pau, Rama Vuyyuru, Ryuji Wakikawa, Lixia Zhang
2013 J jnl
ACM SIGMOBILE Mob. Comput. Commun. Rev.
Giulio Grassi, Davide Pesavento, Lucas Wang, Giovanni Pau, Rama Vuyyuru, Ryuji Wakikawa, Lixia Zhang
2013 B conf
WiMob
Si Chen, Rama Vuyyuru
2013 conf
WiVeC
Pengfei Cui, Hui Liu, Jialin He, Onur Altintas, Rama Vuyyuru, Dinesh Rajan, Joseph David Camp
2013 J jnl
IEEE Veh. Technol. Mag.
Srikanth Pagadarai, Bennett A. Lessard, Alexander M. Wyglinski, Rama Vuyyuru, Onur Altintas
2013 J jnl
CoRR
Giulio Grassi, Davide Pesavento, Lucas Wang, Giovanni Pau, Rama Vuyyuru, Ryuji Wakikawa, Lixia Zhang
2012 conf
INFOCOM Workshops
Lucas Wang, Ryuji Wakikawa, Romain Kuntz, Rama Vuyyuru, Lixia Zhang
2012 A* conf
INFOCOM
Jialin He, Hui Liu, Pengfei Cui, Jonathan Landon, Onur Altintas, Rama Vuyyuru, Dinesh Rajan, Joseph David Camp
2012 conf
VNC
Sean Rocke, Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski
2012 conf
VTC Fall
Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski
2011 conf
Vehicular Ad Hoc Networks
Joseph David Camp, Onur Altintas, Rama Vuyyuru, Dinesh Rajan
2011 conf
VTC Fall
Onur Altintas, Mitsuhiro Nishibori, Takuro Oshida, Chikara Yoshimura, Youhei Fujii, Kota Nishida, Yutaka Ihara, Masahiro Saito, Kazuya Tsukamoto, Masato Tsuru, Yuji Oie, Rama Vuyyuru, AbdulRahman Al-Abbasi, Masaaki Ohtake, Mai Ohta, Takeo Fujii, Si Chen, Srikanth Pagadarai, Alexander M. Wyglinski
2011 J jnl
IEEE Commun. Mag.
Si Chen, Alexander M. Wyglinski, Srikanth Pagadarai, Rama Vuyyuru, Onur Altintas
2011 conf
ISPACS
Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski
2011 conf
VNC
Si Chen, Rama Vuyyuru, Onur Altintas, Alexander M. Wyglinski
2011 conf
VTC Spring
Dusan Borota, Goran Ivkovic, Rama Vuyyuru, Onur Altintas, Ivan Seskar, Predrag Spasojevic
2010 conf
VNC
Junichiro Fukuyama, Rama Vuyyuru, Ratul K. Guha, Wai Chen, John Lee
2010 conf
VNC
Wai Chen, Ratul K. Guha, Jasmine Chennikara-Varghese, Marcus Pang, Rama Vuyyuru, Junichiro Fukuyama
2010 conf
VNC
Si Chen, Alexander M. Wyglinski, Rama Vuyyuru, Onur Altintas
2009 conf
VNC
Wai Chen, Ratul K. Guha, John Lee, Ryokichi Onishi, Rama Vuyyuru
2009 conf
VNC
Srikanth Pagadarai, Alexander M. Wyglinski, Rama Vuyyuru
2008 conf
ICVES
Sanjit K. Kaul, Marco Gruteser, Ryokichi Onishi, Rama Vuyyuru
2006 C conf
MobiQuitous
Rama Vuyyuru, Kentaro Oguchi, Clay Collier, Ed Koch
2003 conf
Web Intelligence
Zonghuan Wu, Vijay V. Raghavan, Hua Qian, Rama Vuyyuru, Weiyi Meng, Hai He, Clement T. Yu
redb/extractors/ioc_extractor/ioc_extractor.py
← Index redb/extractors/ioc_extractor/ioc_extractor.py python
"""
IOC Extractor - Extractor class for extracting IOCs from decompilation results.

This extractor works with in-memory data from DecompileBinja, following the
standard Extractor pattern to support both ClickHouse and PrintExporter (dry-run).

Usage:
    # After DecompileBinja completes:
    ioc_extractor = IOCExtractorFromResults(
        analysis_results=decompiler.analysis_results,
        sha256=sha256,
        log=logger,
        exporters=exporters,
        index_prefix=index_prefix
    )
    ioc_extractor.export_data()
"""

import inspect
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, List, Dict, Optional

from redb.extractors.enum import Tag
from redb.extractors.database_exporters import DatabaseExporter

# Import the IOCScraper and related classes from standalone module
from redb.extractors.ioc_extractor.standalone_ioc_extractor import (
    IOCScraper,
    IOCType,
    SourceType,
    ExtractedIOC,
)
from typing import Set


class IOCExtractorFromResults:
    """
    Extracts IOCs from in-memory decompilation results.

    This follows a simplified Extractor pattern but doesn't inherit from Extractor
    since it doesn't read from a binary file - instead it takes already-processed
    analysis results from DecompileBinja.
    """

    def __init__(
        self,
        analysis_results: Dict[str, Any],
        sha256: str,
        log: Any,
        exporters: Optional[List[DatabaseExporter]] = None,
        index_prefix: Optional[str] = None,
        tld_file: Optional[Path] = None,
        suppress_types: Optional[Set[IOCType]] = None,
        js_context: bool = False,
    ):
        """
        Initialize IOC Extractor with analysis results.

        Args:
            analysis_results: Dict containing 'strings' and 'decompiled' lists from DecompileBinja
            sha256: Sample SHA256 hash
            log: Logger instance
            exporters: List of database exporters (ClickHouse, Print, etc.)
            index_prefix: Index prefix for database
            tld_file: Optional path to TLD list file
            js_context: When True, the underlying IOCScraper rejects FQDN
                candidates that match JS object-access syntax (see
                JS_FP_TLDS / JS_FP_SLDS). Set this for the JS pipeline only;
                APK suppresses FQDN entirely via suppress_types and binary
                callers leave it disabled.
        """
        self.log = log
        self.log.debug(f"Creating {self.__class__.__name__}")
        self.analysis_results = analysis_results
        self.sha256 = sha256
        self.exporters = exporters or []
        self.index_prefix = index_prefix
        self.scraper = IOCScraper(
            tld_file, suppress_types=suppress_types, js_context=js_context,
        )
        self.extracted_iocs: List[ExtractedIOC] = []

    def extract(self) -> List[ExtractedIOC]:
        """
        Extract IOCs from strings and decompiled functions in analysis_results.

        Returns:
            List of ExtractedIOC objects
        """
        self.log.debug(inspect.currentframe().f_code.co_name)
        self.extracted_iocs = []

        # Extract from strings
        strings_count = self._extract_from_strings()

        # Extract from decompiled functions
        functions_count = self._extract_from_decompiled()

        # Extract from text-based artefact surfaces (JS, PowerShell, etc.)
        text_count = self._extract_from_text()

        self.log.info(
            f"Extracted {len(self.extracted_iocs)} IOCs for {self.sha256[:16]}... "
            f"(strings: {strings_count}, functions: {functions_count}, "
            f"text: {text_count})"
        )

        return self.extracted_iocs

    def _extract_from_strings(self) -> int:
        """Extract IOCs from sample's strings."""
        count = 0
        strings = self.analysis_results.get("strings", [])

        for s in strings:
            string_value = s.get("string", "")
            string_offset = s.get("string_offset", 0)

            if isinstance(string_value, bytes):
                string_value = string_value.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(string_value, SourceType.STRING, str(string_offset)):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_decompiled(self) -> int:
        """Extract IOCs from sample's decompiled functions.

        Supports both Binja format (key: "decompiled", fields: "decompiled_function",
        "decompiled_function_hash", "function_type") and APK format (key:
        "decompiled_content", fields: "decompiled_method", "decompiled_method_hash",
        "method_type").
        """
        count = 0

        # Binja format
        decompiled = self.analysis_results.get("decompiled", [])
        for func in decompiled:
            func_type = func.get("function_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_function", "")
            func_hash = func.get("decompiled_function_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        # APK format (decompiled_content with method-level fields)
        decompiled_content = self.analysis_results.get("decompiled_content", [])
        for func in decompiled_content:
            func_type = func.get("method_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_method", "")
            func_hash = func.get("decompiled_method_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_text(self) -> int:
        """Extract IOCs from text-based artefact surfaces.

        Walks `analysis_results["text_raw"]` and `analysis_results["text_normalized"]`,
        each a list of `{"content": str, "content_hash": str}` dicts. Each
        list is routed through its own SourceType (`TEXT_RAW` /
        `TEXT_NORMALIZED`) so analysts can distinguish IOCs that were already
        present in the raw source from those exposed only after normalisation
        (deobfuscation/beautification). Generic across text-based formats —
        used by JS today, intended for PowerShell, Python, email body,
        extracted PDF/Office text in the future.
        """
        count = 0

        for key, source_type in (
            ("text_raw", SourceType.TEXT_RAW),
            ("text_normalized", SourceType.TEXT_NORMALIZED),
        ):
            for entry in self.analysis_results.get(key, []):
                content = entry.get("content", "")
                content_hash = entry.get("content_hash", "unknown")

                if isinstance(content, bytes):
                    content = content.decode('utf-8', errors='replace')

                for ioc in self.scraper.scrape(content, source_type, content_hash):
                    self.extracted_iocs.append(ioc)
                    count += 1

        return count

    def prepare_export_data(self, exporter_type: str) -> Any:
        """
        Prepare data for specific export type.

        Returns tuple for ClickHouse or list of dicts for Print/Elasticsearch.
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.extracted_iocs:
            return None

        now = datetime.now(timezone.utc)

        if exporter_type == "ClickHouseExporter":
            data = [
                [
                    self.sha256,
                    ioc.ioc_type.value,
                    ioc.ioc_value,
                    ioc.source_type.value,
                    ioc.source_identifier,
                    now,
                ]
                for ioc in self.extracted_iocs
            ]

            column_names = [
                "sha256",
                "ioc_type",
                "ioc_value",
                "source_type",
                "source_identifier",
                "extracted_at",
            ]

            column_type_names = [
                "FixedString(64)",
                "Enum8('ipv4'=1, 'ipv6'=2, 'fqdn'=3, 'url'=4, 'email'=5, 'server'=6, "
                "'hash_md5'=10, 'hash_sha1'=11, 'hash_sha256'=12, 'cve'=20, 'cwe'=21, 'cpe'=22, "
                "'crypto_btc'=30, 'crypto_eth'=31, 'crypto_xrp'=32, 'crypto_bch'=33, "
                "'crypto_ada'=34, 'crypto_substrate'=35, 'path_linux'=40, 'path_windows'=41, "
                "'registry_key'=42, 'onion'=50)",
                "String",
                "Enum8('decompiled_function'=1, 'disassembled_function'=2, 'string'=3, "
                "'text_raw'=4, 'text_normalized'=5)",
                "String",
                "DateTime64(3, 'UTC')",
            ]

            return (data, column_names, column_type_names)

        else:
            # For PrintExporter and others - return list of dicts
            return [
                {
                    "sha256": self.sha256,
                    "ioc_type": ioc.ioc_type.value,
                    "ioc_value": ioc.ioc_value,
                    "source_type": ioc.source_type.value,
                    "source_identifier": ioc.source_identifier,
                    "extracted_at": now.isoformat(),
                }
                for ioc in self.extracted_iocs
            ]

    def get_clickhouse_table(self) -> str:
        """Return the ClickHouse table name for IOCs."""
        return "redb_iocs"

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.IOC.value if hasattr(Tag, 'IOC') else "ioc"

    def export_data(self) -> bool:
        """
        Export extracted IOCs to all configured exporters.

        Returns:
            True if export succeeded, False if failed, None if no data
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        # First extract the IOCs
        extracted = self.extract()

        if not extracted:
            self.log.debug("No IOCs extracted, skipping export")
            return None

        success = True

        from redb.extractors.database_exporters import PrintExporter, ClickHouseExporter

        for exporter in self.exporters:
            try:
                if isinstance(exporter, PrintExporter):
                    # For PrintExporter, pass the list of dicts
                    export_data = self.prepare_export_data("PrintExporter")
                    success &= exporter.export(export_data)

                elif isinstance(exporter, ClickHouseExporter):
                    # For ClickHouse, pass tuple with table info
                    export_data = self.prepare_export_data("ClickHouseExporter")
                    if export_data:
                        success &= exporter.export(
                            export_data,
                            table=self.get_clickhouse_table(),
                            column_names=export_data[1],
                            column_type_names=export_data[2]
                        )

            except Exception as e:
                self.log.error(f"Error exporting IOCs to {exporter.__class__.__name__}: {e}")
                success = False

        return success