Raffaele Parisi

76 papers B 2C 8Misc 4Journal 22Unranked 32
YearRankTypeTitle / Venue / Authors
2020 ch.
Neural Advances in Processing Nonlinear Dynamic Signals
Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini
2020 ch.
Neural Advances in Processing Nonlinear Dynamic Signals
Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2019 Misc conf
ICASSP
Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2018 ch.
Multidisciplinary Approaches to Neural Computing
Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2018 J jnl
IEEE Trans. Signal Process.
Elio D. Di Claudio, Raffaele Parisi, Giovanni Jacovitti
2017 J jnl
CoRR
Elio D. Di Claudio, Raffaele Parisi, Giovanni Jacovitti
2016 ch.
Recent Advances in Nonlinear Speech Processing
Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini
2016 ch.
Advances in Neural Networks
Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2016 J jnl
CoRR
Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2016 J jnl
IEEE Trans. Signal Process.
Michele Scarpiniti, Danilo Comminiello, Gaetano Scarano, Raffaele Parisi, Aurelio Uncini
2016 J jnl
J. Comput. Aided Mol. Des.
Stefano Piotto, Luigi Di Biasi, Riccardo Fino, Raffaele Parisi, Lucia Sessa, Simona Concilio
2015 B conf
IJCNN
Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2015 J jnl
Neural Networks
Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini
2015 ch.
Advances in Neural Networks
Raffaele Parisi, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini
2015 J jnl
Signal Process.
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2015 J jnl
IEEE Trans. Circuits Syst. I Regul. Pap.
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2015 ch.
Advances in Neural Networks
Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2014 J jnl
IEEE Wirel. Commun.
Enzo Baccarelli, Francesco Chiti, Nicola Cordeschi, Romano Fantacci, Dania Marabissi, Raffaele Parisi, Aurelio Uncini
2014 J jnl
Signal Process.
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2013 J jnl
Signal Process.
Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2013 conf
TSP
Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2013 C conf
ISPA
Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2013 conf
DSP
Raffaele Parisi, Riccardo Russo, Michele Scarpiniti, Aurelio Uncini
2013 J jnl
Signal Process.
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2013 conf
WIRN
Michele Scarpiniti, Danilo Comminiello, Simone Scardapane, Raffaele Parisi, Aurelio Uncini
2012 conf
WIRN
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2012 J jnl
IEEE Signal Process. Lett.
Raffaele Parisi, Flavia Camoes, Michele Scarpiniti, Aurelio Uncini
2012 conf
WIRN
Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2011 conf
WIRN
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2011 conf
DSP
Cecilia Maria Zannini, Raffaele Parisi, Aurelio Uncini
2011 conf
DSP
Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini
2010 conf
WIRN
Michele Scarpiniti, Francesco Di Palma, Raffaele Parisi, Aurelio Uncini
2010 conf
WIRN
Michele Scarpiniti, Gabriele Bunkheila, Raffaele Parisi, Aurelio Uncini
2010 C conf
ISCAS
Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2010 C conf
ISCAS
Cecilia Maria Zannini, Albenzio Cirillo, Raffaele Parisi, Aurelio Uncini
2010 conf
EUSIPCO
Albenzio Cirillo, Raffaele Parisi, Michele Scarpiniti, Aurelio Uncini
2009 conf
WIRN
Michele Scarpiniti, Andrea Picaro, Raffaele Parisi, Aurelio Uncini
2009 conf
DPS
Albenzio Cirillo, Raffaele Parisi, Aurelio Uncini
2009 conf
DPS
Gabriele Bunkheila, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2008 conf
WIRN
Michele Scarpiniti, Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2008 J jnl
Int. J. Inf. Commun. Technol.
Stefano Laoreti, Davide Renzi, Raffaele Parisi, Aurelio Uncini
2008 J jnl
Int. J. Neural Syst.
Daniele Vigliano, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2008 J jnl
Neurocomputing
Michele Scarpiniti, Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2008 C conf
ISCAS
Gabriele Bunkheila, Raffaele Parisi, Aurelio Uncini
2008 Misc conf
ICASSP
Albenzio Cirillo, Raffaele Parisi, Aurelio Uncini
2007 conf
DSP
Michele Scarpiniti, Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2007 conf
ICASSP (1)
Raffaele Parisi, Albenzio Cirillo, Massimo Panella, Aurelio Uncini
2006 C conf
ISCAS
Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2006 conf
EUSIPCO
Daniele Vigliano, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini
2006 C conf
ISCAS
Raffaele Parisi, P. Croene, Aurelio Uncini
2005 conf
WIRN/NAIS
Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2005 J jnl
Signal Process.
Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2004 conf
WIRN
Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2004 conf
ICASSP (5)
Daniele Vigliano, Raffaele Parisi, Aurelio Uncini
2004 conf
ISCAS (5)
Daniele Vigliano, Aurelio Uncini, Raffaele Parisi
2003 conf
WIRN
Claudio Sistopaoli, Raffaele Parisi, Aurelio Uncini
2003 conf
WIRN
Francesca Vitagliano, Raffaele Parisi, Aurelio Uncini
2003 J jnl
IEEE Trans. Signal Process.
Elio D. Di Claudio, Raffaele Parisi
2002 conf
EUSIPCO
Aurelio Uncini, Andrea Nalin, Raffaele Parisi
2002 conf
EUSIPCO
Raffaele Parisi, Riccardo Gazzetta, Elio D. Di Claudio
2002 Misc conf
ICASSP
Raffaele Parisi, Riccardo Gazzetta, Elio D. Di Claudio
2002 conf
WIRN
Lorenzo Topi, Raffaele Parisi, Aurelio Uncini
2001 J jnl
Signal Process.
Mirko Solazzi, Aurelio Uncini, Elio D. Di Claudio, Raffaele Parisi
2001 ch.
Microphone Arrays
Elio D. Di Claudio, Raffaele Parisi
2001 J jnl
IEEE Trans. Signal Process.
Elio D. Di Claudio, Raffaele Parisi
2000 B conf
ESANN
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
2000 C conf
ISCAS
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
2000 Misc conf
ICASSP
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
2000 conf
EUSIPCO
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
2000 conf
EUSIPCO
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
2000 conf
IJCNN (5)
Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi
1999 conf
ISCAS (5)
Mirko Solazzi, Aurelio Uncini, Elio D. Di Claudio, Raffaele Parisi
1997 J jnl
IEEE Trans. Signal Process.
Raffaele Parisi, Elio D. Di Claudio, Gianni Orlandi, Bhaskar D. Rao
1996 J jnl
IEEE Trans. Neural Networks
Raffaele Parisi, Elio D. Di Claudio, Gianni Orlandi, Bhaskar D. Rao
1996 conf
ICNN
Raffaele Parisi, Elio D. Di Claudio, A. Rapagnetta, Gianni Orlandi
1995 C conf
ISCAS
Raffaele Parisi, Elio D. Di Claudio, Gianni Orlandi
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