R. Vijayakumar

14 papers B 1Journal 7Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Internet Technol. Lett.
R. Vijayakumar, Manisha Mali, Sonali A. Patil, V. Gomathy, Harishchander Anandaram
2025 J jnl
Clust. Comput.
Akshya Jothi, M. Sundarrajan, R. Vijayakumar, Rajesh Kumar Dhanaraj, Anand Nayyar
2023 J jnl
Int. J. Wirel. Mob. Comput.
Jobin Varghese P., R. Vijayakumar
2020 conf
FICTA (1)
Leena C. Sekhar, R. Vijayakumar
2015 conf
ICARA
Sreekanth M, Abraham T. Mathew, R. Vijayakumar
2014 conf
SOFA (1)
Anju Pratap, C. S. Kanimozhiselvi, R. Vijayakumar, K. V. Pramod
2010 conf
ICWET
P. Muhamed Ilyas, R. Vijayakumar
2010 ed.
BAIP
Vinu V. Das, R. Vijayakumar, Narayan C. Debnath, Janahanlal Stephen, Natarajan Meghanathan, Suresh Sankaranarayanan, P. M. Thankachan, Ford Lumban Gaol, Nessy Thankachan
2010 ed.
ICT
Vinu V. Das, R. Vijayakumar, K. G. Srinivasa, Hatim A. Aboalsamh, Mohammad Hammoudeh, Vahid Salmani, Dinesh Kumar Tyagi, Anjali Mohapatra, Bharatheesh Jaysimha, Eliathamby Ambikairajah, Jonathan M. Blackledge
2010 J jnl
Eng. Appl. Artif. Intell.
K. G. Jolly, R. Sreerama Kumar, R. Vijayakumar
2009 J jnl
Robotics Auton. Syst.
K. G. Jolly, R. Sreerama Kumar, R. Vijayakumar
2009 J jnl
Neurocomputing
K. G. Jolly, R. Sreerama Kumar, R. Vijayakumar
2007 J jnl
Robotics Auton. Syst.
K. G. Jolly, K. P. Ravindran, R. Vijayakumar, R. Sreerama Kumar
2006 B conf
FPL
Christos A. Papachristou, J. Weaver, R. Vijayakumar, Francis G. Wolff
redb/extractors/decompiler/bninja/analysis/medium_level.py
← Index redb/extractors/decompiler/bninja/analysis/medium_level.py python
import time

from binaryninja import (
    MediumLevelILOperation as MLIL_OP,
)

try:
    from ..function_type import FunctionTypeAnalysis
    from ..similarity.minhasher import MinHasher, TokenKind
    from ..utils.hashes import calculate_sha256, calculate_tlsh
    from .medium_level_normalization import MediumLevelNormalization
except ImportError:
    from redb.extractors.decompiler.bninja.analysis.medium_level_normalization import MediumLevelNormalization
    from redb.extractors.decompiler.bninja.similarity.minhasher import MinHasher
    from redb.extractors.decompiler.bninja.function_type import FunctionTypeAnalysis
    from redb.extractors.decompiler.bninja.utils.hashes import calculate_sha256, calculate_tlsh


_MLIL_CALL_OPS = (
    MLIL_OP.MLIL_CALL,
    MLIL_OP.MLIL_CALL_SSA,
    MLIL_OP.MLIL_CALL_UNTYPED,
    MLIL_OP.MLIL_CALL_UNTYPED_SSA,
    MLIL_OP.MLIL_TAILCALL,
    MLIL_OP.MLIL_TAILCALL_SSA,
    MLIL_OP.MLIL_TAILCALL_UNTYPED,
    MLIL_OP.MLIL_TAILCALL_UNTYPED_SSA,
)

_MLIL_CONTROL_FLOW_OPS = (
    MLIL_OP.MLIL_IF,
    MLIL_OP.MLIL_GOTO,
    MLIL_OP.MLIL_JUMP,
    MLIL_OP.MLIL_JUMP_TO,
    MLIL_OP.MLIL_RET,
    MLIL_OP.MLIL_RET_HINT,
    MLIL_OP.MLIL_NORET,
) + _MLIL_CALL_OPS


class MediumLevelAnalysis:
    def __init__(self, function, bv, logger):
        self.function = function
        self.name = function.name
        self.start = function.start
        self.mlil_func = function.mlil
        self.bv = bv
        self.logger = logger
        self.errors = []

    def log_error(self, message, function_name, address, exception=None, error_location="unknown"):
        error_msg = f"Error in function {function_name} at {address}: {message}"
        if exception:
            error_msg += f" - {str(exception)}"
        self.logger.error(error_msg)

        error = {
            "function_name": function_name,
            "function_address": str(address),
            "error_location": error_location,
            "error_message": message,
            "error_details": str(exception) if exception else "",
            "error_type": type(exception).__name__ if exception else "Unknown",
            "timestamp": int(time.time() * 1000),
        }
        self.errors.append(error)

    def _collect_mlil_skeleton_and_typed(self):
        mlil = self.mlil_func
        if not mlil:
            return [], [], [], []

        start = self.start
        norm = MediumLevelNormalization()

        skeleton = []
        skeleton_with_addr = []
        typed = []
        typed_with_addr = []

        for il in mlil.instructions:
            skel_norm = norm.normalize_instruction_all_levels(il)
            typed_norm = norm.normalize_instr_with_operands(il)

            skeleton.append(skel_norm)
            typed.append(typed_norm)

            offset = il.address - start
            if offset < 0:
                offset = 0

            skeleton_with_addr.append((offset, skel_norm))
            typed_with_addr.append((offset, typed_norm))

        return skeleton, skeleton_with_addr, typed, typed_with_addr

    def analyze(self):
        (
            instr_skeleton,
            body_mlil_skeleton_vector,
            instr_typed,
            body_mlil_typed_vector,
        ) = self._collect_mlil_skeleton_and_typed()

        instr_skeleton_str = str(instr_skeleton)
        sha256_skeleton = calculate_sha256(instr_skeleton_str)
        tlsh_skeleton = calculate_tlsh(instr_skeleton_str)

        instr_typed_str = str(instr_typed)
        sha256_typed = calculate_sha256(instr_typed_str)
        tlsh_typed = calculate_tlsh(instr_typed_str)

        seed = 0xdeadbeef
        minhash_mlil_skeleton = MinHasher(seed, self.mlil_func, TokenKind.MLIL).calculateMinHash()
        minhash_mlil_typed = MinHasher(seed, self.mlil_func, TokenKind.TYPED_MLIL).calculateMinHash()

        medium_level_json = {
            "function_address": self.start,
            "body_mlil_skeleton_vector": body_mlil_skeleton_vector,
            "sha256_mlil_skeleton": sha256_skeleton,
            "tlsh_mlil_skeleton": tlsh_skeleton,
            "minhash_mlil_skeleton": minhash_mlil_skeleton,
            "body_mlil_typed_vector": body_mlil_typed_vector,
            "sha256_mlil_typed": sha256_typed,
            "tlsh_mlil_typed": tlsh_typed,
            "minhash_mlil_typed": minhash_mlil_typed,
        }

        return medium_level_json, self.errors