Carson M. Andorf

23 papers Journal 19Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Database J. Biol. Databases Curation
Elly Poretsky, Victoria C. Blake, Carson M. Andorf, Taner Z. Sen
2024 J jnl
Bioinform.
Carson M. Andorf, Olivia C. Haley, Rita K. Hayford, John L. Portwood II, Stephen Harding, Shatabdi Sen, Ethalinda K. S. Cannon, Jack M. Gardiner, Hye-Seon Kim, Margaret Woodhouse
2023 J jnl
Database J. Biol. Databases Curation
Shatabdi Sen, Margaret Woodhouse, John L. Portwood II, Carson M. Andorf
2022 J jnl
Frontiers Artif. Intell.
Kyoung Tak Cho, Taner Z. Sen, Carson M. Andorf
2021 J jnl
BMC Bioinform.
Sagnik Banerjee, Priyanka Bhandary, Margaret Woodhouse, Taner Z. Sen, Roger P. Wise, Carson M. Andorf
2021 J jnl
Bioinform.
Margaret Woodhouse, Shatabdi Sen, David A. Schott, John L. Portwood II, Michael Freeling, Justin W. Walley, Carson M. Andorf, James C. Schnable
2020 conf
BCB
Sagnik Banerjee, Margaret Woodhouse, Roger P. Wise, Priyanka Bhandary, Taner Z. Sen, Carson M. Andorf
2019 J jnl
Nucleic Acids Res.
John L. Portwood II, Margaret Woodhouse, Ethalinda K. S. Cannon, Jack M. Gardiner, Lisa C. Harper, Mary L. Schaeffer, Jesse R. Walsh, Taner Z. Sen, Kyoung Tak Cho, David A. Schott, Bremen L. Braun, Miranda Dietze, Brittney Dunfee, Christine G. Elsik, Nancy Manchanda, Ed Coe, Marty Sachs, Philip Stinard, Josh Tolbert, Shane Zimmerman, Carson M. Andorf
2019 J jnl
Bioinform.
Bremen L. Braun, David A. Schott, John L. Portwood II, Carson M. Andorf, Taner Z. Sen
2018 J jnl
Database J. Biol. Databases Curation
Lisa C. Harper, Jacqueline D. Campbell, Ethalinda K. S. Cannon, Sook Jung, Monica Poelchau, Ramona L. Walls, Carson M. Andorf, Elizabeth Arnaud, Tanya Z. Berardini, Clayton L. Birkett, Steven B. Cannon, James D. Carson, Bradford Condon, Laurel Cooper, Nathan A. Dunn, Christine G. Elsik, Andrew D. Farmer, Stephen P. Ficklin, David M. Grant, Emily S. Grau, Nic Herndon, Zhi-Liang Hu, Jodi L. Humann, Pankaj Jaiswal, Clément Jonquet, Marie-Angélique Laporte, Pierre Larmande, Gerard R. Lazo, Fiona McCarthy, Naama Menda, Christopher J. Mungall, Monica C. Munoz-Torres, Sushma Naithani, Rex T. Nelson, Daureen Nesdill, Carissa A. Park, James M. Reecy, Leonore Reiser, Lacey-Anne Sanderson, Taner Z. Sen, Margaret Staton, Sabarinath Subramaniam, Marcela Karey Tello-Ruiz, Victor Unda, Deepak R. Unni, Liya Wang, Doreen Ware, Jill L. Wegrzyn, Jason Williams, Margaret Woodhouse, Jing Yu, Doreen Main
2018 J jnl
PLoS Comput. Biol.
Naihui Zhou, Zachary D. Siegel, Scott Zarecor, Nigel Lee, Darwin A. Campbell, Carson M. Andorf, Dan Nettleton, Carolyn J. Lawrence-Dill, Baskar Ganapathysubramanian, Jonathan W. Kelly, Iddo Friedberg
2018 J jnl
Database J. Biol. Databases Curation
David A. Schott, Abhinav G. Vinnakota, John L. Portwood II, Carson M. Andorf, Taner Z. Sen
2017 J jnl
Database J. Biol. Databases Curation
Taner Z. Sen, Bremen L. Braun, David A. Schott, John L. Portwood II, Mary L. Schaeffer, Lisa C. Harper, Jack M. Gardiner, Ethalinda K. S. Cannon, Carson M. Andorf
2016 J jnl
Nucleic Acids Res.
Carson M. Andorf, Ethalinda K. S. Cannon, John L. Portwood II, Jack M. Gardiner, Lisa C. Harper, Mary L. Schaeffer, Bremen L. Braun, Darwin A. Campbell, Abhinav G. Vinnakota, Venktanaga V. Sribalusu, Miranda Huerta, Kyoung Tak Cho, Kokulapalan Wimalanathan, Jacqueline D. Richter, Emily D. Mauch, Bhavani S. Rao, Scott M. Birkett, Taner Z. Sen, Carolyn J. Lawrence-Dill
2011 J jnl
Database J. Biol. Databases Curation
Mary L. Schaeffer, Lisa C. Harper, Jack M. Gardiner, Carson M. Andorf, Darwin A. Campbell, Ethalinda K. S. Cannon, Taner Z. Sen, Carolyn J. Lawrence
2011 J jnl
Database J. Biol. Databases Curation
Lisa C. Harper, Mary L. Schaeffer, Jordan Thistle, Jack M. Gardiner, Carson M. Andorf, Darwin A. Campbell, Ethalinda K. S. Cannon, Bremen L. Braun, Scott M. Birkett, Carolyn J. Lawrence, Taner Z. Sen
2010 J jnl
Database J. Biol. Databases Curation
Taner Z. Sen, Lisa C. Harper, Mary L. Schaeffer, Carson M. Andorf, Trent E. Seigfried, Darwin A. Campbell, Carolyn J. Lawrence
2010 J jnl
Bioinform.
Carson M. Andorf, Carolyn J. Lawrence, Lisa C. Harper, Mary L. Schaeffer, Darwin A. Campbell, Taner Z. Sen
2009 J jnl
Database J. Biol. Databases Curation
Taner Z. Sen, Carson M. Andorf, Mary L. Schaeffer, Lisa C. Harper, Michael E. Sparks, Jon Duvick, Volker P. Brendel, Ethalinda K. S. Cannon, Darwin A. Campbell, Carolyn J. Lawrence
2007 J jnl
BMC Bioinform.
Carson M. Andorf, Drena Dobbs, Vasant G. Honavar
2005 conf
DILS
Doina Caragea, Jyotishman Pathak, Jie Bao, Adrian Silvescu, Carson M. Andorf, Drena Dobbs, Vasant G. Honavar
2005 conf
DEXA Workshops
Doina Caragea, Jie Bao, Jyotishman Pathak, Adrian Silvescu, Carson M. Andorf, Drena Dobbs, Vasant G. Honavar
2002 conf
JCIS
Carson M. Andorf, Drena Dobbs, Vasant G. Honavar
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