Nataly Zhukova

62 papers Misc 10Journal 18Unranked 34
YearRankTypeTitle / Venue / Authors
2026 J jnl
Expert Syst. Appl.
Tianxing Man, Igor Kulikov, Yang Jiafeng, Nataly Zhukova
2025 J jnl
Frontiers Comput. Sci.
Radhakrishnan Delhibabu, Pham Tuan Anh, Nataly Zhukova, Alexey Subbotin
2025 conf
ICCSA (Workshops 9)
Alexey Nikolayevich Subbotin, Nataly Zhukova, Elena N. Stankova
2025 J jnl
Future Gener. Comput. Syst.
Alexander Vodyaho, Radhakrishnan Delhibabu, Dmitry I. Ignatov, Nataly Zhukova
2024 J jnl
Adv. Artif. Intell. Mach. Learn.
Alexey Subbotin, Radhakrishnan Delhibabu, Nataly Zhukova
2024 J jnl
Future Gener. Comput. Syst.
Alexander Vodyaho, Nataly Zhukova, Radhakrishnan Delhibabu, Alexey Nikolayevich Subbotin
2024 J jnl
Inf. Fusion
Tianxing Man, Vasiliy Osipov, Nataly Zhukova, Alexey Nikolayevich Subbotin, Dmitry I. Ignatov
2024 conf
SAI (3)
Alexey Nikolayevich Subbotin, Nataly Zhukova, Mikhail Gudilov
2023 conf
ICCSA (2)
Vladislav Kovalevsky, Elena N. Stankova, Nataly Zhukova, Oksana Ogiy, Alexander Tristanov
2023 conf
ICCSA (Workshops 1)
Nikita Olimpiev, Alexander Vodyaho, Nataly Zhukova
2023 conf
AICCC
Nataly Zhukova, Anna I. Motienko, Dmitriy Levonevskiy, Alexey Nikolayevich Subbotin, Pham Tuan Anh
2023 J jnl
Eng. Appl. Artif. Intell.
Tianxing Man, Alexander Vodyaho, Dmitry I. Ignatov, Igor Kulikov, Nataly Zhukova
2023 conf
MECO
Nataly Zhukova, Alexey Nikolayevich Subbotin
2022 J jnl
Int. J. Embed. Real Time Commun. Syst.
Yang Jiafeng, Nataly Zhukova, Sergey Lebedev, Tianxing Man
2022 Misc conf
FRUCT
Nataly Zhukova, Alexey Nikolayevich Subbotin
2022 conf
MECO
Nataly Zhukova, Alexey Nikolayevich Subbotin
2022 J jnl
Int. J. Embed. Real Time Commun. Syst.
Kirill Krinkin, Alexander Ivanovich Vodyaho, Igor Kulikov, Nataly Zhukova
2022 J jnl
J. Comput. Networks Commun.
Alexander Vodyaho, Nataly Zhukova, Yulia A. Shichkina, Saddam Abbas, Vladimir Chernokulsky
2022 J jnl
Sensors
Alexander Vodyaho, Nataly Zhukova, Alexey Nikolayevich Subbotin, Fahem Anaam
2022 conf
ICCSA (Workshops 4)
Alexander Vodyaho, Elena N. Stankova, Nataly Zhukova, Alexey Nikolayevich Subbotin, Michael Chervontsev
2021 Misc conf
FRUCT
Tianxing Man, Myo Myint, Wang Guan, Nataly Zhukova, Nikolay Mustafin
2021 J jnl
Int. J. Embed. Real Time Commun. Syst.
Tianxing Man, Nataly Zhukova, Alexander Vodyaho, Tin Tun Aung
2021 Misc conf
FRUCT
Kirill Krinkin, Igor Kulikov, Alexander Vodyaho, Nataly Zhukova
2021 conf
MECO
Alexey Nikolayevich Subbotin, Nataly Zhukova, Tianxing Man
2021 J jnl
Int. J. Embed. Real Time Commun. Syst.
Kirill Krinkin, Alexander Ivanovich Vodyaho, Igor Kulikov, Nataly Zhukova
2021 conf
ICCSA (8)
Igor Kulikov, Alexander Vodyaho, Elena N. Stankova, Nataly Zhukova
2021 conf
ICCSA (8)
Tianxing Man, Sergey Lebedev, Alexander Vodyaho, Nataly Zhukova, Yulia A. Shichkina
2021 Misc conf
FRUCT
Kirill Krinkin, Igor Kulikov, Alexander Vodyaho, Nataly Zhukova
2021 conf
IntelliSys (2)
Tianxing Man, Nataly Zhukova
2021 J jnl
Comput.
Alexander Vodyaho, Nataly Zhukova, Igor Kulikov, Saddam Abbas
2020 conf
IEEE Conf. on Intelligent Systems
Tianxing Man, Nataly Zhukova, Georgi Tsochev
2020 conf
ICCSA (6)
Igor Kulikov, Gerhard Wohlgenannt, Yulia A. Shichkina, Nataly Zhukova
2020 Misc conf
FRUCT
Kirill Krinkin, Igor Kulikov, Alexander Vodyaho, Nataly Zhukova
2020 conf
MECO
Alexander Vodyaho, Abbas Saddam Ahmed, Nataly Zhukova, Aung Myo Thaw
2020 conf
ICCSA (1)
Tianxing Man, Elena N. Stankova, Alexander Vodyaho, Nataly Zhukova, Yulia A. Shichkina
2020 conf
IEEE Conf. on Intelligent Systems
Alexander Vodyaho, Radoslav Yoshinov, Nataly Zhukova, Aung Myo Thaw, Abbas Saddam Ahmed
2020 Misc conf
FRUCT
Nataly Zhukova, Aung Myo Thaw, Tianxing Man, Nikolay Mustafin
2020 J jnl
Comput.
Alexander Vodyaho, Saddam Abbas, Nataly Zhukova, Michael Chervoncev
2020 conf
MECO
Kirill Krinkin, Alexander Vodyaho, Igor Kulikov, Nataly Zhukova
2020 J jnl
Neural Comput. Appl.
Vasiliy Osipov, Victor Nikiforov, Nataly Zhukova, Dmitriy Miloserdov
2019 conf
ICCSA (1)
Ildar R. Baimuratov, Yulia A. Shichkina, Elena N. Stankova, Nataly Zhukova, Nguyen Than
2019 conf
ICCSA (1)
Tianxing Man, Nataly Zhukova, Vasily Meltsov, Yulia A. Shichkina
2019 conf
ICINCO (1)
Tianxing Man, Nataly Zhukova, Nguyen Than, Alexander Nechaev, Sergey Lebedev
2019 conf
ICCSA (2)
Vasiliy Osipov, Elena N. Stankova, Alexander Vodyaho, Mikhail Lushnov, Yulia A. Shichkina, Nataly Zhukova
2019 Misc conf
FRUCT
Vasily Meltsov, Pavel Novokshonov, Dmitry Repkin, Alexander Nechaev, Nataly Zhukova
2019 J jnl
Int. J. Knowl. Syst. Sci.
Tianxing Man, Vasily Osipov, Alexander Vodyaho, Sergey Lebedev, Nataly Zhukova
2019 conf
MICSECS
Alexander Nechaev, Nataly Zhukova, Vasily Meltsov
2018 Misc conf
FRUCT
Ildar R. Baimuratov, Nataly Zhukova
2018 conf
AIST (Supplement)
Ildar R. Baimuratov, Stefan Morozov, Nataly Zhukova
2017 conf
AIST (Supplement)
Nataly Zhukova, Maksim Berezov, Sergey Lebedev, Ekaterina Zavadskaya
2017 conf
WDAM
Alexander Vodyaho, Nataly Zhukova, Dmitry Kurapeev, Mikhail Lushnov
2016 conf
AIST (Supplement)
Nataly Zhukova, Alexander Vodyaho, Maxim Lapaev
2016 conf
KESW
Mikhail Lushnov, Vyacheslav Kudashov, Alexander Vodyaho, Maxim Lapaev, Nataly Zhukova, Denis Korobov
2016 conf
EMSA-RMed@ESWC
Mikhail Lushnov, Timur Safin, Maxim Lapaev, Nataly Zhukova
2016 conf
EEML@CLA
Nataly Zhukova, Mikhail Navrotskiy
2015 conf
IF&GIS
Nataly Zhukova, Alexander Vodyaho
2015 Misc conf
AIST
Alexander Vodyaho, Nataly Zhukova
2014 J jnl
Int. J. Concept. Struct. Smart Appl.
Alexander Vodyaho, Nataly Zhukova
2014 conf
AIST (Supplement)
Alexander Vodyaho, Nataly Zhukova
2013 conf
IF&GIS
Andrey Pankin, Alexander Vitol, Nataly Zhukova
2013 conf
IF&GIS
Oksana Smirnova, Nataly Zhukova
2013 Misc conf
ICCS
Alexander Vitol, Nataly Zhukova, Andrey Pankin
redb/extractors/decompiler/bninja/analysis/low_level.py
← Index redb/extractors/decompiler/bninja/analysis/low_level.py python
import time

from binaryninja import (
    LowLevelILInstruction,
)
from binaryninja import (
    LowLevelILOperation as LLIL_OP,
)
from binaryninja.lowlevelil import (
    LowLevelILAdd,
    LowLevelILConst,
    LowLevelILConstPtr,
    LowLevelILLoad,
    LowLevelILLsl,
    LowLevelILMul,
    LowLevelILPop,
    LowLevelILPush,
    LowLevelILReg,
    LowLevelILStore,
    LowLevelILSub,
)

# Support both package and standalone imports
try:
    from ..function_type import FunctionTypeAnalysis
    from ..similarity.minhasher import MinHasher, TokenKind
    from ..utils.hashes import calculate_sha256, calculate_tlsh
    from .low_level_normalization import LowLevelNormalization

except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.analysis.low_level_normalization import LowLevelNormalization
    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

class LowLevelAnalysis:
    def __init__(self, function, bv, logger):
        self.function = function
        self.name = function.name
        self.start = function.start
        self.llil_func = function.llil
        self.bv = bv
        self.logger = logger
        self.errors = []

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

        # Add to errors list
        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 count_control_flow_instructions(self):
        if self.llil_func is None:
            return 0

        count = 0
        for basic_block in self.llil_func.basic_blocks:
            for ins in basic_block:
                op = ins.operation
                if op in (
                    LLIL_OP.LLIL_IF,
                    LLIL_OP.LLIL_GOTO,
                    LLIL_OP.LLIL_JUMP,
                    LLIL_OP.LLIL_JUMP_TO,
                    LLIL_OP.LLIL_CALL,
                    LLIL_OP.LLIL_CALL_SSA,
                ):
                    count += 1

        return count

    def collect_memory_patterns(self):
        """ """
        patterns = set()

        try:
            llil = self.llil_func
            arch = self.bv.arch
            sp_name = arch.stack_pointer if arch and arch.stack_pointer else "sp"

            def analyze_addr(addr_expr, might_be_direct):
                """
                Visit the expression for the address and understand whether it has a direct, scaled, base offset, etc.
                access to memory
                """
                found = {
                    "direct": False,
                    "scaled": False,
                    "base_off": False,
                    "stack": False,
                    "string": False,
                }

                def addr_cb(n):
                    # stack (SP/BP-like)
                    match n:
                        case LowLevelILReg(src=reg):
                            if reg == sp_name:
                                found["stack"] = True

                        case LowLevelILConst() | LowLevelILConstPtr():
                            if might_be_direct:
                                found["direct"] = True

                        # base +/- const
                        case (
                            LowLevelILAdd(left=l, right=r)
                            | LowLevelILSub(left=l, right=r)
                        ):
                            l_is_reg = isinstance(l, LowLevelILReg)
                            r_is_reg = isinstance(r, LowLevelILReg)
                            l_is_cst = isinstance(
                                l, (LowLevelILConst, LowLevelILConstPtr)
                            )
                            r_is_cst = isinstance(
                                r, (LowLevelILConst, LowLevelILConstPtr)
                            )
                            if (l_is_reg and r_is_cst) or (r_is_reg and l_is_cst):
                                found["base_off"] = True

                        # scaled index (index*scale) or shift (index << k)
                        case LowLevelILMul(left=l, right=r):
                            if (
                                isinstance(l, LowLevelILReg)
                                and isinstance(r, LowLevelILConst)
                            ) or (
                                isinstance(r, LowLevelILReg)
                                and isinstance(l, LowLevelILConst)
                            ):
                                found["scaled"] = True

                        case LowLevelILLsl(left, right):
                            if isinstance(left, LowLevelILReg) and isinstance(
                                right, LowLevelILConst
                            ):
                                found["scaled"] = True

                    return None

                _ = list(addr_expr.traverse(addr_cb))

                if found["direct"]:
                    patterns.add("MEM_DIRECT")
                if found["scaled"]:
                    patterns.add("MEM_SCALED_INDEX")
                if found["base_off"]:
                    patterns.add("MEM_BASE_OFFSET")
                if found["stack"]:
                    patterns.add("MEM_STACK")
                elif found["string"]:
                    patterns.add("MEM_STRING")

            def func_cb(i):
                match i:
                    case LowLevelILPush(src=addr):
                        analyze_addr(addr, False)
                    case LowLevelILPop(src=addr):
                        analyze_addr(addr, False)
                    case LowLevelILLoad(src=addr):
                        analyze_addr(addr, True)
                    case LowLevelILStore(dest=addr, src=_):
                        analyze_addr(addr, True)

                return None

            # complete visit for the single instruction
            _ = list(llil.traverse(func_cb))

            return sorted(patterns)

        except Exception as e:
            self.log_error(
                "Failed to collect memory patterns via LLIL.traverse",
                self.name,
                self.start,
                e,
                "collect_memory_patterns",
            )
            return []

    def collect_register_usage(self):
        """
        Collect frequencies for register usage
        """
        try:
            llil = self.llil_func

            register_usage = {}

            def inc(reg, kind):
                if reg is None:
                    return
                entry = register_usage.setdefault(reg, {"reads": 0, "writes": 0})
                entry[kind] += 1

            if not llil:
                return {}, 0, 0

            for top_il in llil.instructions:
                registers_read = self.function.get_regs_read_by(
                    top_il.address, self.bv.arch
                )
                registers_write = self.function.get_regs_written_by(
                    top_il.address, self.bv.arch
                )

                for reg_read in registers_read:
                    inc(reg_read, "reads")

                for reg_write in registers_write:
                    inc(reg_write, "writes")

            total_reads = sum(entry["reads"] for entry in register_usage.values())
            total_writes = sum(entry["writes"] for entry in register_usage.values())

            return register_usage, total_reads, total_writes

        except Exception as e:
            self.log_error(
                "Failed to collect register usage via LLIL.traverse",
                self.name,
                self.start,
                e,
                "collect_register_usage",
            )
            return {}, 0, 0

    def _classify_address(self, bv, addr):
        """
        Classification of the address
        """
        info = {
            "address": addr,
            "section": None,
            "segment_writable": None,
            "symbol": None,
            "kind": None,  # "string", "function_ptr", "data_var", "symbol", "unknown"
            "datatype": None,  # es. "char *", "int32_t", "my_struct", ...
            "note": None,
        }

        # section / segment
        sec = bv.get_section_at(addr)
        seg = bv.get_segment_at(addr)
        if sec:
            info["section"] = sec.name
        if seg:
            info["segment_writable"] = bool(seg.writable)

        sym = bv.get_symbol_at(addr)
        if sym:
            info["symbol"] = sym.full_name

        # function pointer
        try:
            fns = list(bv.get_functions_at(addr))
        except Exception:
            # some versions have get_function_at(addr) that returns a single object or None
            fns = [bv.get_function_at(addr)] if hasattr(bv, "get_function_at") else []
        fns = [f for f in fns if f]
        if fns:
            info["kind"] = "function_ptr"
            info["datatype"] = "func"
            info["note"] = f"points to function {fns[0].name}"
            return info

        # string
        sref = bv.get_string_at(addr)
        if sref:
            info["kind"] = "string"
            # sref.type:
            info["datatype"] = (
                getattr(sref, "type", None).__class__.__name__
                if hasattr(sref, "type")
                else "string"
            )
            return info

        # data typed variable
        dv = bv.get_data_var_at(addr)
        if dv:
            info["kind"] = "data_var"
            info["datatype"] = str(dv.type) if getattr(dv, "type", None) else None
            if getattr(dv, "name", None):
                info["symbol"] = dv.name if not info["symbol"] else info["symbol"]
            return info

        # only symbol (no data var)
        if sym and not info["kind"]:
            info["kind"] = "symbol"
            return info

        # unknown
        info["kind"] = "unknown"
        return info

    def count_data_references(self):
        """Count the number of data references in a function using LLIL."""
        count = 0

        if self.llil_func is None:
            return 0

        try:
            # Iterate LLIL basic blocks and instructions
            for instr in self.llil_func.instructions:
                instr_str = str(instr)
                logged = False
                src = None

                # Check for constant dereferencing or symbolic refs
                if hasattr(instr, "src"):
                    src = instr.src
                    if isinstance(src, (LowLevelILConstPtr, LowLevelILConst)):
                        count += 1
                        logged = True

                if not logged and "_" in instr_str:
                    count += 1

                # If src is a pointer constant, check if it lands in a writable data segment
                if src is not None and isinstance(src, LowLevelILConstPtr):
                    addr = src.constant
                    segment = self.bv.get_segment_at(addr)
                    if segment and segment.writable:
                        count += 1

        except Exception as e:
            self.logger.warning(
                f"Failed to use LLIL for counting data references in "
                f"{self.name} at {self.start}: {e}"
            )
        return count

    def compute_num_calls(self):
        c = 0

        if not self.llil_func:
            return 0

        for instr in self.llil_func.instructions:
            if instr.operation in (LLIL_OP.LLIL_CALL, LLIL_OP.LLIL_TAILCALL):
                c += 1
        return c

    def compute_max_block_size(self):
        """Compute the maximum basic block size in a function."""
        if self.llil_func is None:
            return 0

        max_size = 0
        for block in self.llil_func.basic_blocks:
            try:
                # Count instructions in this block using the direct length approach
                # This avoids UTF-8 decoding issues entirely
                block_size = block.instruction_count
                max_size = max(max_size, block_size)
            except Exception as e:
                self.log_error(
                    f"[HandledError] computing max block size: {e}",
                    self.name,
                    self.start,
                    e,
                    "compute_max_block_size",
                )
        return max_size

    def estimate_stack_size(self):
        """Estimate the stack size used by a function."""
        try:
            # Binary Ninja provides a stack adjustment value for functions
            # Need to convert OffsetWithConfidence to a plain integer
            stack_adjust = self.function.stack_adjustment
            if hasattr(stack_adjust, "value"):  # Handle OffsetWithConfidence objects
                return stack_adjust.value
            return stack_adjust
        except Exception as e:
            self.log_error(
                "Failed to estimate stack size",
                self.name,
                self.start,
                e,
                "estimate_stack_size",
            )
            return -1

    def collect_instruction_types(self):
        def iter_llil_tree(root_il):
            stack = [root_il]
            while stack:
                il_single_op = stack.pop()
                if not isinstance(il_single_op, LowLevelILInstruction):
                    continue
                yield il_single_op
                for il_operand in il_single_op.operands:
                    if isinstance(il_operand, LowLevelILInstruction):
                        stack.append(il_operand)
                    elif isinstance(il_operand, (list, tuple)):
                        for sub in il_operand:
                            if isinstance(sub, LowLevelILInstruction):
                                stack.append(sub)

        type_frequencies = {}
        try:
            if self.llil_func is None:
                return type_frequencies

            il_func = self.llil_func

            for top_il in il_func.instructions:
                for il in iter_llil_tree(top_il):
                    op = getattr(il, "operation", None)
                    if op is None:
                        continue

                    category = str(op)

                    if category in type_frequencies:
                        type_frequencies[category] += 1
                    else:
                        type_frequencies[category] = 1

        except Exception as e:
            self.log_error(
                "Failed to collect LLIL instruction types",
               self.name,
                self.start,
                e,
                "collect_instruction_types_llil",
            )

        return type_frequencies

    def _collect_low_level_with_type(self):
        llil = self.llil_func
        if not llil:
            return [], []

        start = self.start

        low_level = LowLevelNormalization()

        instrs_with_addr = []

        for il in llil.instructions:
            norm = low_level.normalize_instr_with_operands(il)

            # Clamp negative offsets to 0 for UInt32 compatibility.
            # Negative offsets (instruction before function start) may occur with
            # overlapping functions or tail-calls in obfuscated/malware binaries.
            # Multiple instructions at offset 0 indicates this anomaly and can be
            # queried to identify such samples easily than by checking logs.
            # Triggered by 590ecad54cd9e1c8681509420ad56edde8b064ffbf884ce6cd8dd28eebb95ae1
            offset = il.address - start
            if offset < 0:
                offset = 0

            instrs_with_addr.append((offset, norm))

        return instrs_with_addr

    def _collect_low_level_and_with_addr(self):
        llil = self.llil_func
        if not llil:
            return [], []

        start = self.start

        low_level = LowLevelNormalization()

        instrs = []
        instrs_with_addr = []

        for il in llil.instructions:
            norm = low_level.normalize_instruction_all_levels(il)

            instrs.append(norm)

            # Clamp negative offsets to 0 for UInt32 compatibility.
            # Negative offsets (instruction before function start) may occur with
            # overlapping functions or tail-calls in obfuscated/malware binaries.
            # Multiple instructions at offset 0 indicates this anomaly and can be
            # queried to identify such samples easily than by checking logs.
            # Triggered by 590ecad54cd9e1c8681509420ad56edde8b064ffbf884ce6cd8dd28eebb95ae1
            offset = il.address - start
            if offset < 0:
                offset = 0

            instrs_with_addr.append((offset, norm))

        return instrs, instrs_with_addr


    def analyze(self):
        registers_uses, total_reads, total_written = self.collect_register_usage()
        instr_low_level, body_llil_vector = self._collect_low_level_and_with_addr()
        instr_low_level_str = str(instr_low_level)
        instructions_low_level = calculate_sha256(instr_low_level_str)
        instructions_low_level_tlsh = calculate_tlsh(instr_low_level_str)

        instr_typed_llil = self._collect_low_level_with_type()
        instr_typed_low_level_str = str(instr_typed_llil)
        instructions_typed_low_level = calculate_sha256(instr_typed_low_level_str)
        instructions_typed_low_level_tlsh = calculate_tlsh(instr_typed_low_level_str)

        seed = 0xdeadbeef
        minhash_llil_skeleton = MinHasher(seed, self.llil_func, TokenKind.LLIL).calculateMinHash()
        minhash_llil_typed = MinHasher(seed, self.llil_func, TokenKind.TYPED_LLIL).calculateMinHash()

        low_level_json = {
            "function_address": self.start,
            "function_type": FunctionTypeAnalysis(self.function)
            .get_function_type()
            .name,
            "body_llil_vector": body_llil_vector,
            "sha256_llil": instructions_low_level,
            "tlsh_llil": instructions_low_level_tlsh,
            "minhash_llil_skeleton": minhash_llil_skeleton,
            "instructions_types_llil": list(self.collect_instruction_types()),
            "instruction_typed_llil": instructions_typed_low_level,
            "tlsh_instruction_typed_llil": instructions_typed_low_level_tlsh,
            "minhash_llil_typed": minhash_llil_typed,
            "control_flow_count_llil": self.count_control_flow_instructions(),
            "memory_access_pattern_llil": self.collect_memory_patterns(),
            "register_usage": registers_uses,
            "total_reg_reads": total_reads,
            "total_reg_written": total_written,
            "data_references_count": self.count_data_references(),
            "max_block_size": self.compute_max_block_size(),
            "num_calls": self.compute_num_calls(),
            "stack_size": self.estimate_stack_size(),
        }

        return low_level_json, self.errors