Nancy F. Glenn

26 papers C 8Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
CoRR
Sureka Thiruchittampalam, Bikram Pratap Banerjee, Nancy F. Glenn, Simit Raval
2024 J jnl
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Brenton A. Wilder, Christine M. Lee, Adam Chlus, Hans-Peter Marshall, Jodi Brandt, Alicia M. Kinoshita, Josh Enterkine, Thomas Van Der Weide, Nancy F. Glenn
2023 C conf
IGARSS
Sureka Thiruchittampalam, Bikram Pratap Banerjee, Sarvesh Kumar Singh, Nancy F. Glenn, Simit Raval
2023 C conf
IGARSS
Brenton A. Wilder, Nancy F. Glenn, Christine M. Lee, Hans-Peter Marshall, Jodi Brandt, Alicia M. Kinoshita, Thomas Van Der Weide, Josh Enterkine
2021 C conf
IGARSS
David R. Thompson, David Bearden, Ian Brosnan, Kerry Cawse-Nicholson, Jonathan Chrone, Robert O. Green, Nancy F. Glenn, Liane S. Guild, Simon J. Hook, Raymond F. Kokaly, Christine M. Lee, Jeffrey Luvall, Charles E. Miller, Jamie Nastal, Ryan Pavlick, Benjamin Poulter, David S. Schimel, Fabian Schneider, Stephanie Schollaert Uz, Amit Sen, Shawn P. Serbin, Natasha Stavros, Kurt J. Thome, Philip A. Townsend, Woody Turner, Kevin R. Turpie, Weile Wang
2020 C conf
IGARSS
David R. Thompson, David S. Schimel, Benjamin Poulter, Ian Brosnan, Simon J. Hook, Robert O. Green, Nancy F. Glenn, Liane S. Guild, Christopher Henn, Kerry Cawse-Nicholson, Raymond F. Kokaly, Christine M. Lee, Jeffrey Luvall, Charles E. Miller, Jamie Nastal, Ryan Pavlick, Benjamin Phillips, Fabian Schneider, Stephanie Schollaert Uz, Shawn P. Serbin, Natasha Stavros, Philip A. Townsend, Woody Turner, Kevin R. Turpie, Weile Wang
2019 conf
eScience
Ravi Shankar, Nayani T. Ilangakoon, Aaron Orenstein, Floriana Ciaglia, Nancy F. Glenn, Catherine Olschanowsky
2019 J jnl
IEEE Trans. Geosci. Remote. Sens.
Hamid Dashti, Nancy F. Glenn, Susan L. Ustin, Jessica J. Mitchell, Yi Qi, Nayani T. Ilangakoon, Alejandro N. Flores, José Luis Silván-Cárdenas, Kaiguang Zhao, Lucas P. Spaete, Marie-Anne de Graaff
2019 J jnl
Remote. Sens.
Hamid Dashti, Andrew Poley, Nancy F. Glenn, Nayani T. Ilangakoon, Lucas P. Spaete, Dar A. Roberts, Josh Enterkine, Alejandro N. Flores, Susan L. Ustin, Jessica J. Mitchell
2018 J jnl
Remote. Sens.
Yi Qi, Susan L. Ustin, Nancy F. Glenn
2018 C conf
IGARSS
Ludovic Brucker, Christopher A. Hiemstra, Hans-Peter Marshall, Kelly Elder, Roger D. De Roo, Mohammad Mousavi, Francis Bliven, Walt Peterson, Jeffrey Deems, Peter Gadomski, Arthur Gelvin, Lucas P. Spaete, Theodore B. Barnhart, Ty Brandt, John F. Burkhart, Christopher J. Crawford, Tri Datta, Havard Erikstrod, Nancy F. Glenn, Katherine Hale, Brent Holben, Paul R. Houser, Keith Jennings, Richard E. J. Kelly, Jason Kraft, Alexandre Langlois, Daniel McGrath, Chelsea Merriman, Noah P. Molotch, Anne W. Nolin, Chris Polashenski, Mark Raleigh, Karl Rittger, Chago Rodriguez, Alexandre Roy, S. McKenzie Skiles, Eric Small, Marco Tedesco, Chris Tennant, Aaron Thompson, Zach Uhlmann, Ryan Webb, Matt Wingo
2018 C conf
IGARSS
Zach Uhlmann, Nancy F. Glenn, Lucas P. Spaete, Christopher A. Hiemstra, Chris Tennant, Jim McNamara
2017 C conf
IGARSS
Ludovic Brucker, Christopher A. Hiemstra, Hans-Peter Marshall, Kelly Elder, Roger D. De Roo, Mohammad Mousavi, Francis Bliven, Walt Peterson, Jeffrey S. Deems, Peter Gadomski, Arthur Gelvin, Lucas P. Spaete, Theodore B. Barnhart, Ty Brandt, John F. Burkhart, Christopher J. Crawford, Tri Datta, Havard Erikstrod, Nancy F. Glenn, Katherine Hale, Brent Holben, Paul R. Houser, Keith Jennings, Richard E. J. Kelly, Jason Kraft, Alexandre Langlois, Daniel McGrath, Chelsea Merriman, Noah P. Molotch, Anne W. Nolin, Chris Polashenski, Mark Raleigh, Karl Rittger, Chago Rodriguez, Alexandre Roy, S. McKenzie Skiles, Eric Small, Marco Tedesco, Chris Tennant, Aaron Thompson, Liuxi Tian, Zach Uhlmann, Ryan Webb, Matt Wingo
2017 J jnl
Remote. Sens.
Peter J. Olsoy, Jessica J. Mitchell, Nancy F. Glenn, Alejandro N. Flores
2017 J jnl
Remote. Sens.
Aihua Li, Shital Dhakal, Nancy F. Glenn, Lucas P. Spaete, Douglas J. Shinneman, David S. Pilliod, Robert S. Arkle, Susan K. McIlroy
2016 conf
WHISPERS
Aihua Li, Ryan Will, Nancy F. Glenn, Shawn Benner, Lucas P. Spaete
2014 J jnl
Trans. GIS
Jayson J. Murgoitio, Rupesh Shrestha, Nancy F. Glenn, Lucas P. Spaete
2014 J jnl
Environ. Model. Softw.
Ping Yang, Daniel P. Ames, André Fonseca, Danny Anderson, Rupesh Shrestha, Nancy F. Glenn, Yang Cao
2013 J jnl
Int. J. Geogr. Inf. Sci.
Jayson J. Murgoitio, Rupesh Shrestha, Nancy F. Glenn, Lucas P. Spaete
2013 J jnl
Remote. Sens.
Jessica J. Mitchell, Rupesh Shrestha, Carol A. Moore-Ellison, Nancy F. Glenn
2012 J jnl
Remote. Sens.
Ryan C. Hruska, Jessica J. Mitchell, Matthew O. Anderson, Nancy F. Glenn
2012 conf
WHISPERS
Jessica J. Mitchell, Nancy F. Glenn, Matthew O. Anderson, Ryan C. Hruska, Anne Halford, Charlie Baun, Nick Nydegger
2011 J jnl
Remote. Sens.
Wade T. Tinkham, Hongyu Huang, Alistair M. S. Smith, Rupesh Shrestha, Michael J. Falkowski, Andrew Thomas Hudak, Timothy E. Link, Nancy F. Glenn, Danny G. Marks
2009 J jnl
IEEE Geosci. Remote. Sens. Lett.
Cheng Wang, Nancy F. Glenn
2009 J jnl
Int. J. Appl. Earth Obs. Geoinformation
Jill Norton, Nancy F. Glenn, Matt Germino, Keith T. Weber, Steven Seefeldt
2002 C conf
IGARSS
Vern Singhroy, Hiroshi Ohkura, Nancy F. Glenn
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