Hanieh Shakeri

11 papers A* 2A 1B 1Misc 1Unranked 6
YearRankTypeTitle / Venue / Authors
2026 A* conf
CHI
Reese Muntean, Hanieh Shakeri, Carman Neustaedter
2024 A conf
Conference on Designing Interactive Systems
Hanieh Shakeri, Ye Yuan, Benett Axtell, Denise Y. Geiskkovitch, Carman Neustaedter
2024 conf
CHI Extended Abstracts
Hanieh Shakeri, Carman Neustaedter
2023 A* conf
CHI
Hanieh Shakeri, Denise Y. Geiskkovitch, Radhika Garg, Carman Neustaedter
2021 B conf
Graphics Interface
Hanieh Shakeri, Hannah Elbaggari, Paul Bucci, Robert Xiao, Karon E. MacLean
2021 conf
CHI Extended Abstracts
Hanieh Shakeri, Carman Neustaedter
2021 conf
CSCW Companion
Hanieh Shakeri, Carman Neustaedter, Steve DiPaola
2021 conf
CSCW Companion
Hanieh Shakeri, Carman Neustaedter, William Odom
2019 conf
CSCW Companion
Hanieh Shakeri, Carman Neustaedter
2018 conf
HVEI
Hanieh Shakeri, Michael Nixon, Steve DiPaola
2017 Misc conf
CHI PLAY
Hanieh Shakeri, Samarth Singhal, Rui Pan, Carman Neustaedter, Anthony Tang
redb/extractors/decompiler/bninja/analysis/medium_level.py
← Index redb/extractors/decompiler/bninja/analysis/medium_level.py python
import time

from binaryninja import (
    MediumLevelILOperation as MLIL_OP,
)

try:
    from ..function_type import FunctionTypeAnalysis
    from ..similarity.minhasher import MinHasher, TokenKind
    from ..utils.hashes import calculate_sha256, calculate_tlsh
    from .medium_level_normalization import MediumLevelNormalization
except ImportError:
    from redb.extractors.decompiler.bninja.analysis.medium_level_normalization import MediumLevelNormalization
    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


_MLIL_CALL_OPS = (
    MLIL_OP.MLIL_CALL,
    MLIL_OP.MLIL_CALL_SSA,
    MLIL_OP.MLIL_CALL_UNTYPED,
    MLIL_OP.MLIL_CALL_UNTYPED_SSA,
    MLIL_OP.MLIL_TAILCALL,
    MLIL_OP.MLIL_TAILCALL_SSA,
    MLIL_OP.MLIL_TAILCALL_UNTYPED,
    MLIL_OP.MLIL_TAILCALL_UNTYPED_SSA,
)

_MLIL_CONTROL_FLOW_OPS = (
    MLIL_OP.MLIL_IF,
    MLIL_OP.MLIL_GOTO,
    MLIL_OP.MLIL_JUMP,
    MLIL_OP.MLIL_JUMP_TO,
    MLIL_OP.MLIL_RET,
    MLIL_OP.MLIL_RET_HINT,
    MLIL_OP.MLIL_NORET,
) + _MLIL_CALL_OPS


class MediumLevelAnalysis:
    def __init__(self, function, bv, logger):
        self.function = function
        self.name = function.name
        self.start = function.start
        self.mlil_func = function.mlil
        self.bv = bv
        self.logger = logger
        self.errors = []

    def log_error(self, message, function_name, address, exception=None, error_location="unknown"):
        error_msg = f"Error in function {function_name} at {address}: {message}"
        if exception:
            error_msg += f" - {str(exception)}"
        self.logger.error(error_msg)

        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 _collect_mlil_skeleton_and_typed(self):
        mlil = self.mlil_func
        if not mlil:
            return [], [], [], []

        start = self.start
        norm = MediumLevelNormalization()

        skeleton = []
        skeleton_with_addr = []
        typed = []
        typed_with_addr = []

        for il in mlil.instructions:
            skel_norm = norm.normalize_instruction_all_levels(il)
            typed_norm = norm.normalize_instr_with_operands(il)

            skeleton.append(skel_norm)
            typed.append(typed_norm)

            offset = il.address - start
            if offset < 0:
                offset = 0

            skeleton_with_addr.append((offset, skel_norm))
            typed_with_addr.append((offset, typed_norm))

        return skeleton, skeleton_with_addr, typed, typed_with_addr

    def analyze(self):
        (
            instr_skeleton,
            body_mlil_skeleton_vector,
            instr_typed,
            body_mlil_typed_vector,
        ) = self._collect_mlil_skeleton_and_typed()

        instr_skeleton_str = str(instr_skeleton)
        sha256_skeleton = calculate_sha256(instr_skeleton_str)
        tlsh_skeleton = calculate_tlsh(instr_skeleton_str)

        instr_typed_str = str(instr_typed)
        sha256_typed = calculate_sha256(instr_typed_str)
        tlsh_typed = calculate_tlsh(instr_typed_str)

        seed = 0xdeadbeef
        minhash_mlil_skeleton = MinHasher(seed, self.mlil_func, TokenKind.MLIL).calculateMinHash()
        minhash_mlil_typed = MinHasher(seed, self.mlil_func, TokenKind.TYPED_MLIL).calculateMinHash()

        medium_level_json = {
            "function_address": self.start,
            "body_mlil_skeleton_vector": body_mlil_skeleton_vector,
            "sha256_mlil_skeleton": sha256_skeleton,
            "tlsh_mlil_skeleton": tlsh_skeleton,
            "minhash_mlil_skeleton": minhash_mlil_skeleton,
            "body_mlil_typed_vector": body_mlil_typed_vector,
            "sha256_mlil_typed": sha256_typed,
            "tlsh_mlil_typed": tlsh_typed,
            "minhash_mlil_typed": minhash_mlil_typed,
        }

        return medium_level_json, self.errors