Ingrid Scharlau

19 papers C 1Misc 3Journal 9Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
AI Ethics
Suzana Alpsancar, Heike M. Buhl, Tobias Matzner, Ingrid Scharlau
2025 J jnl
Cogn. Syst. Res.
Hendrik Buschmeier, Heike M. Buhl, Friederike Kern, Angela Grimminger, Helen Beierling, Josephine Beryl Fisher, André Groß, Ilona Horwath, Nils Oliver Klowait, Stefan Lazarov, Michael Lenke, Vivien Lohmer, Katharina J. Rohlfing, Ingrid Scharlau, Amit Singh, Lutz Terfloth, Anna-Lisa Vollmer, Yu Wang, Annedore Wilmes, Britta Wrede
2025 J jnl
CoRR
Benjamin Paaßen, Suzana Alpsancar, Tobias Matzner, Ingrid Scharlau
2025 J jnl
CoRR
Leandra Fichtel, Maximilian Spliethöver, Eyke Hüllermeier, Patricia Jimenez, Nils Oliver Klowait, Stefan Kopp, Axel-Cyrille Ngonga Ngomo, Amelie Sophie Robrecht, Ingrid Scharlau, Lutz Terfloth, Anna-Lisa Vollmer, Henning Wachsmuth
2025 J jnl
Cogn. Syst. Res.
Roel Visser, Tobias M. Peters, Ingrid Scharlau, Barbara Hammer
2024 conf
ApPLIED@PODC
Lukas Stratmann, Ngoc Chi Banh, Ingrid Scharlau, Falko Dressler
2024 conf
PETRA
Kai Biermeier, Ingrid Scharlau, Enes Yigitbas
2023 J jnl
CoRR
Hendrik Buschmeier, Heike M. Buhl, Friederike Kern, Angela Grimminger, Helen Beierling, Josephine Beryl Fisher, André Groß, Ilona Horwath, Nils Oliver Klowait, Stefan Lazarov, Michael Lenke, Vivien Lohmer, Katharina J. Rohlfing, Ingrid Scharlau, Amit Singh, Lutz Terfloth, Anna-Lisa Vollmer, Yu Wang, Annedore Wilmes, Britta Wrede
2023 conf
EMNLP (Findings)
Meghdut Sengupta, Milad Alshomary, Ingrid Scharlau, Henning Wachsmuth
2023 J jnl
Frontiers Robotics AI
André Groß, Amit Singh, Ngoc Chi Banh, Birte Richter, Ingrid Scharlau, Katharina J. Rohlfing, Britta Wrede
2023 J jnl
CoRR
Roel Visser, Tobias M. Peters, Ingrid Scharlau, Barbara Hammer
2021 J jnl
IEEE Trans. Cogn. Dev. Syst.
Katharina J. Rohlfing, Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, Angela Grimminger, Barbara Hammer, Reinhold Häb-Umbach, Ilona Horwath, Eyke Hüllermeier, Friederike Kern, Stefan Kopp, Kirsten Thommes, Axel-Cyrille Ngonga Ngomo, Carsten Schulte, Henning Wachsmuth, Petra Wagner, Britta Wrede
2019 C conf
WOWMOM
Julian Heinovski, Lukas Stratmann, Dominik S. Buse, Florian Klingler, Mario Franke, Marie-Christin H. Oczko, Christoph Sommer, Ingrid Scharlau, Falko Dressler
2019 conf
GI-Jahrestagung (Workshops)
Lukas Stratmann, Dominik S. Buse, Julian Heinovski, Florian Klingler, Christoph Sommer, Jan Tünnermann, Ingrid Scharlau, Falko Dressler
2011 conf
GI-Jahrestagung
Gitta Domik, Stephan Arens, Ingrid Scharlau, Frederic Hilkenmeier
2011 conf
SIGGRAPH Posters
Gitta Domik, Felix Steffen, Stephan Arens, Ingrid Scharlau
2009 Misc conf
KI
Katharina Weiß, Ingrid Scharlau
2009 Misc conf
KI
Frederic Hilkenmeier, Jan Tünnermann, Ingrid Scharlau
2009 Misc conf
KI
Heinz-Werner Priess, Ingrid Scharlau
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