Nan Wang

28 papers A* 2B 2Journal 23Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Robotics Auton. Syst.
Xuewen Yang, Nan Wang, Guoyu Wang, Aiguo Song
2026 J jnl
IEEE Robotics Autom. Lett.
Xuewen Yang, Le Wang, Fengchang Fang, Nan Wang, Guoyu Wang, Aiguo Song
2026 A* conf
WWW
Ziyue Wu, Nan Wang, Jiqiang Liu, Hairong Dong, Xibin Zhao
2025 A* conf
ICRA
Xuewen Yang, Nan Wang, Jiayang Gu, Yugang Zhang, Guoyu Wang, Aiguo Song
2024 J jnl
Multim. Tools Appl.
Wenjie Hu, Xuewen Yang, Nan Wang, Xing Zhang, Yanni Cui, Jia Yu, Haiyong Zheng, Bing Zheng
2022 J jnl
IEEE Trans. Intell. Transp. Syst.
Biao Yang, Weiqin Zhan, Pin Wang, Ching-Yao Chan, Yingfeng Cai, Nan Wang
2020 J jnl
Neurocomputing
Biao Yang, Weiqin Zhan, Nan Wang, Xiaofeng Liu, Jidong Lv
2020 J jnl
Neural Comput. Appl.
Biao Yang, Jinmeng Cao, Xiaofeng Liu, Nan Wang, Jidong Lv
2020 J jnl
Multim. Tools Appl.
Yan Zhao, Ziqiang Zheng, Chao Wang, Zhaorui Gu, Min Fu, Zhibin Yu, Haiyong Zheng, Nan Wang, Bing Zheng
2020 J jnl
Multim. Tools Appl.
Jinmeng Cao, Biao Yang, Nan Wang, Hai Wang, Yingfeng Cai
2020 J jnl
CoRR
Tingting Zhang, Yushi Lan, Aiguo Song, Kun Liu, Nan Wang
2019 J jnl
IEEE Trans. Cogn. Dev. Syst.
Biao Yang, Jinmeng Cao, Nan Wang, Xiaofeng Liu
2019 J jnl
Neurocomputing
Ziqiang Zheng, Chao Wang, Zhibin Yu, Nan Wang, Haiyong Zheng, Bing Zheng
2019 J jnl
IEEE Access
Jia Yu, Xuewen Yang, Nan Wang, Gavin H. Tilstone, Elaine Fileman, Haiyong Zheng, Zhibin Yu, Min Fu, Bing Zheng
2018 J jnl
Signal Process. Image Commun.
Biao Yang, Jinmeng Cao, Nan Wang, Yuyu Zhang, Ling Zou
2018 J jnl
IEEE Access
Biao Yang, Jinmeng Cao, Nan Wang, Yuyu Zhang, Guozeng Cui
2018 B conf
ICPR
Jing Liu, Angang Du, Chao Wang, Haiyong Zheng, Nan Wang, Bing Zheng
2017 J jnl
BMC Bioinform.
Haiyong Zheng, Ruchen Wang, Zhibin Yu, Nan Wang, Zhaorui Gu, Bing Zheng
2017 B conf
ICIP
Chao Wang, Zhibin Yu, Haiyong Zheng, Nan Wang, Bing Zheng
2017 J jnl
Commun. Inf. Syst.
Biao Yang, Jinmeng Cao, Nan Wang, Yuyu Zhang, Ling Zou
2017 J jnl
CoRR
Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Chao Wang, Nan Wang
2017 J jnl
IET Image Process.
Haiyong Zheng, Nan Wang, Zhibin Yu, Zhaorui Gu, Bing Zheng
2017 J jnl
IEEE Access
Nan Wang, Haiyong Zheng, Bing Zheng
2017 J jnl
Comput. Intell. Neurosci.
Zhibin Yu, Yubo Wang, Bing Zheng, Haiyong Zheng, Nan Wang, Zhaorui Gu
2016 conf
ACCV Workshops (3)
Jialun Dai, Zhibin Yu, Haiyong Zheng, Bing Zheng, Nan Wang
2016 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Nan Wang, Aiguo Song
2015 J jnl
J. Sensors
Changcheng Wu, Aiguo Song, Yun Ling, Nan Wang, Lei Tian
2015 J jnl
Neurocomputing
Nan Wang, Aiguo Song
redb/extractors/decompiler/bninja/analysis/disassembly.py
← Index redb/extractors/decompiler/bninja/analysis/disassembly.py python
import re
import time

import binaryninja
from binaryninja.enums import (
    InstructionTextTokenType,
)

# Support both package and standalone imports
try:
    from ..function_type import FunctionTypeAnalysis
    from ..utils.hashes import calculate_sha256
except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.function_type import FunctionTypeAnalysis
    from redb.extractors.decompiler.bninja.utils.hashes import calculate_sha256


class DisassemblyAnalysis:
    INVALID_STACK_SIZE = -1

    def __init__(self, arch, function, bv, logger):
        self.arch = arch
        self.function = function
        self.bv = bv
        self.logger = logger
        if self.function is not None and hasattr(self.function, "instructions"):
            self.instructions = self.function.instructions
        else:
            self.instructions = []
        self.errors = []
        return

    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 get_json(self):
        try:
            # Build disassembly string and normalized versions
            disassembly_builder = [[], []]  # Address and instruction text

            # Create a dictionary mapping addresses to instruction tokens
            instr_tokens_by_addr = {}
            for instr_tokens, addr in self.instructions:
                instr_tokens_by_addr[addr] = instr_tokens

            addresses = sorted(instr_tokens_by_addr.keys())
            for address in addresses:
                # Original disassembly with addresses
                # instr_tokens, address = instruction
                instr_tokens = instr_tokens_by_addr[address]
                disassembly_builder[0].append(address)
                disassembly_builder[1].append("".join(map(str, instr_tokens)))

            # Join with newlines
            disassembly_str = "\n".join(disassembly_builder[1])
            disassembly_with_addresses = "\n".join(
                f"{hex(address)}: {instr_text}"
                for address, instr_text in zip(
                    disassembly_builder[0], disassembly_builder[1], strict=False
                )
            )

            disassembly_json = {
                "disassembled_function_hash": calculate_sha256(disassembly_str),
                "disassembled_function": disassembly_with_addresses,
                "disassembled_function_no_addresses": disassembly_str,
                "disassembled_function_name": self.function.name,
                "disassembled_function_address": self.function.start,
                "instructions_count": len(instr_tokens_by_addr.keys()),
                "function_type": FunctionTypeAnalysis(self.function)
                .get_function_type()
                .name,
            }

            # Add additional metrics
            type_frequencies = self.collect_instruction_types()
            disassembly_json["instructions_types"] = list(type_frequencies.keys())
            disassembly_json["control_flow_count"] = (
                self.count_control_flow_instructions()
            )
            disassembly_json["memory_access_pattern"] = self.collect_memory_patterns()
            disassembly_json["register_usage"] = self.collect_register_usage()
            disassembly_json["data_references_count"] = self.count_data_references()
            disassembly_json["max_block_size"] = self.compute_max_block_size()
            disassembly_json["num_calls"] = self.compute_num_calls()
            disassembly_json["stack_size"] = self.estimate_stack_size()

            return disassembly_json, self.errors

        except Exception as e:
            self.log_error(
                "Failed to collect instruction types",
                self.function.name,
                self.function.start,
                e,
                "collect_instruction_types",
            )
            raise ValueError(e) from e

    def collect_instruction_types(self):
        """Collect instruction type frequencies from a function."""
        type_frequencies = {}

        try:
            # Iterate through all instructions in the function
            for instruction in self.instructions:
                instr_tokens = instruction[0]  # Get the instruction tokens

                # Extract the mnemonic from the instruction tokens
                mnemonic = None
                for token in instr_tokens:
                    if token.type == InstructionTextTokenType.InstructionToken:
                        mnemonic = token.text
                        break

                if not mnemonic:
                    continue

                # Use normalize_opcode to get standardized opcode
                normalized = self.normalize_opcode(mnemonic)

                # Get category from opcode_categories or use the instruction type directly
                category = self.arch.opcode_categories.get(normalized)
                if category:
                    self._increment_frequency(type_frequencies, category)

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

        return type_frequencies

    def normalize_opcode(self, opcode):
        return opcode.upper()

    def collect_memory_patterns(self):
        """Collect memory access patterns from a function."""
        patterns = []
        try:
            for instruction in self.instructions:
                instr_tokens = instruction[0]

                # We need to capture memory operands between BeginMemoryOperandToken and EndMemoryOperandToken
                in_memory_operand = False
                memory_operand_text = ""

                for token in instr_tokens:
                    if token.type == InstructionTextTokenType.BeginMemoryOperandToken:
                        in_memory_operand = True
                        memory_operand_text = ""
                    elif token.type == InstructionTextTokenType.EndMemoryOperandToken:
                        in_memory_operand = False

                        # Process the captured memory operand text
                        if memory_operand_text:
                            # Categorize memory access pattern
                            if (
                                "+" in memory_operand_text
                                and "*" in memory_operand_text
                            ):
                                if "MEM_SCALED_INDEX" not in patterns:
                                    patterns.append("MEM_SCALED_INDEX")
                            elif (
                                "+" in memory_operand_text or "-" in memory_operand_text
                            ):
                                if "MEM_BASE_OFFSET" not in patterns:
                                    patterns.append("MEM_BASE_OFFSET")
                            else:
                                if "MEM_DIRECT" not in patterns:
                                    patterns.append("MEM_DIRECT")

                            # Check for stack accesses
                            if any(
                                reg in memory_operand_text
                                for reg in ["SP", "BP", "ESP", "EBP", "RSP", "RBP"]
                            ):
                                if "MEM_STACK" not in patterns:
                                    patterns.append("MEM_STACK")
                            # Check for string operations
                            elif (
                                any(
                                    reg in memory_operand_text
                                    for reg in ["SI", "DI", "ESI", "EDI", "RSI", "RDI"]
                                )
                                and "MEM_STRING" not in patterns
                            ):
                                patterns.append("MEM_STRING")
                    elif in_memory_operand:
                        # Accumulate token text while inside a memory operand
                        memory_operand_text += token.text
        except Exception as e:
            self.log_error(
                "Failed to collect memory patterns",
                self.function.name,
                self.function.start,
                e,
                "collect_memory_patterns",
            )
        return patterns

    def collect_register_usage(self):
        """Collect register usage from a function."""
        registers = []
        try:
            # Define register groups we're interested in tracking
            register_groups = {
                "GPR": [
                    "RAX",
                    "RBX",
                    "RCX",
                    "RDX",
                    "R9",
                    "R10",
                    "R11",
                    "R12",
                    "R13",
                    "R14",
                    "R15",
                    "EAX",
                    "EBX",
                    "ECX",
                    "EDX",
                    "R9D",
                    "R10D",
                    "R11D",
                    "R12D",
                    "R13D",
                    "R14D",
                    "AX",
                    "BX",
                    "CX",
                    "DX",
                ],
                "GPR_INDEX": ["RSI", "RDI", "ESI", "EDI", "SI", "DI"],
                "GPR_STACK": ["RSP", "RBP", "ESP", "EBP", "SP", "BP"],
                "SIMD": ["XMM", "YMM", "ZMM"],
                "FPU": ["ST", "ST0", "ST1", "ST2", "ST3", "ST4", "ST5", "ST6", "ST7"],
                "FLAGS": ["FLAGS", "EFLAGS", "RFLAGS"],
                "CONTROL_REGISTER": ["CR0", "CR2", "CR3", "CR4", "CR8"],
                "DEBUG_REGISTER": ["DR0", "DR1", "DR2", "DR3", "DR6", "DR7"],
            }

            # Extract registers from instructions
            for instruction in self.instructions:
                instr_tokens = instruction[0]
                for token in instr_tokens:
                    if token.type == InstructionTextTokenType.RegisterToken:
                        reg = token.text.upper()
                        # Check which group this register belongs to
                        for group, regs in register_groups.items():
                            # if any(r in reg for r in regs) or any(reg.startswith(r) for r in regs):
                            if any(reg == r or reg.startswith(r) for r in regs):
                                if group not in registers:
                                    registers.append(group)
                                break
        except Exception as e:
            self.log_error(
                "Failed to collect register usage",
                self.function.name,
                self.function.start,
                e,
                "collect_register_usage",
            )
        return registers

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

            if self.function.mlil is None:
                return 0

            for block in self.function.mlil:
                for instr in block:
                    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,
                            (
                                binaryninja.mediumlevelil.MediumLevelILConstPtr,
                                binaryninja.mediumlevelil.MediumLevelILConst,
                            ),
                        ):
                            count += 1
                            logged = True

                    # Check full string for hardcoded addresses or symbol-like tokens
                    if re.search(r"\b0x[0-9A-Fa-f]{3,}\b", instr_str) and not logged:
                        count += 1
                        logged = True

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

                    # Only check for MediumLevelILConstPtr if src exists
                    if src is not None and isinstance(
                        src, binaryninja.mediumlevelil.MediumLevelILConstPtr
                    ):
                        addr = src.constant
                        # Check if address is in data sections
                        segment = self.bv.get_segment_at(addr)
                        if segment and segment.writable:
                            # print(f"[{function.name}] Matched data section reference in: {instr_str}")
                            count += 1
                            logged = True
        except Exception as e:
            self.logger.warning(
                f"Failed to use MLIL for counting data references in {self.function.name} at {self.function.start}: {e}"
            )
        return count

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

        for block in self.function.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.function.name,
                    self.function.start,
                    e,
                    "compute_max_block_size",
                )
        return max_size

    def count_control_flow_instructions(self):
        """Count the number of control flow instructions in a function."""
        count = 0
        try:
            for instruction in self.instructions:
                instr_tokens = instruction[0]
                if self.arch.is_control_flow_instruction(instr_tokens):
                    count += 1
        except Exception as e:
            self.log_error(
                "Failed to count control flow instructions",
                self.function.name,
                self.function.start,
                e,
                "count_control_flow_instructions",
            )
        return count

    def compute_num_calls(self) -> int:
        """Compute the number of call instructions in a function."""
        num_calls = 0
        try:
            for instruction in self.instructions:
                instr_tokens = instruction[0]
                # Extract the mnemonic
                for token in instr_tokens:
                    if token.type == InstructionTextTokenType.InstructionToken:
                        if token.text.upper() == "CALL":
                            num_calls += 1
                        break
        except Exception as e:
            self.log_error(
                "Failed to compute number of calls",
                self.function.name,
                self.function.start,
                e,
                "compute_num_calls",
            )
        return num_calls

    def _increment_frequency(self, frequencies, type_name):
        """Increment the frequency count for an instruction type."""
        if type_name in frequencies:
            frequencies[type_name] += 1
        else:
            frequencies[type_name] = 1

    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.function.name,
                self.function.start,
                e,
                "estimate_stack_size",
            )
            return self.INVALID_STACK_SIZE