Nasir Hayat

14 papers A* 1Journal 10Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
CoRR
Praveen K. Kanithi, Clément Christophe, Marco AF Pimentel, Tathagata Raha, Nada Saadi, Hamza Javed, Svetlana Maslenkova, Nasir Hayat, Ronnie Rajan, Shadab Khan
2024 J jnl
CoRR
Clément Christophe, Praveen K. Kanithi, Prateek Munjal, Tathagata Raha, Nasir Hayat, Ronnie Rajan, Ahmed Al-Mahrooqi, Avani Gupta, Muhammad Umar Salman, Gurpreet Gosal, Bhargav Kanakiya, Charles Chen, Natalia Vassilieva, Boulbaba Ben Amor, Marco AF Pimentel, Shadab Khan
2024 J jnl
CoRR
Wadood M. Abdul, Marco AF Pimentel, Muhammad Umar Salman, Tathagata Raha, Clément Christophe, Praveen K. Kanithi, Nasir Hayat, Ronnie Rajan, Shadab Khan
2022 conf
MLHC
Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
2022 J jnl
CoRR
Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
2022 A* conf
CVPR
Prateek Munjal, Nasir Hayat, Munawar Hayat, Jamshid Sourati, Shadab Khan
2021 conf
MLHC
Nasir Hayat, Hazem Lashen, Farah E. Shamout
2021 J jnl
CoRR
Nasir Hayat, Hazem Lashen, Farah E. Shamout
2021 J jnl
CoRR
Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
2020 J jnl
CoRR
Ghadeer O. Ghosheh, Bana Alamad, Kai-Wen Yang, Faisil Syed, Nasir Hayat, Imran Iqbal, Fatima Al Kindi, Sara Al Junaibi, Maha Al Safi, Raghib Ali, Walid Zaher, Mariam Al Harbi, Farah E. Shamout
2020 conf
ACCV (3)
Nasir Hayat, Munawar Hayat, Shafin Rahman, Salman H. Khan, Syed Waqas Zamir, Fahad Shahbaz Khan
2020 J jnl
CoRR
Nasir Hayat, Munawar Hayat, Shafin Rahman, Salman H. Khan, Syed Waqas Zamir, Fahad Shahbaz Khan
2020 J jnl
CoRR
Prateek Munjal, Nasir Hayat, Munawar Hayat, Jamshid Sourati, Shadab Khan
2019 J jnl
Artif. Intell. Eng. Des. Anal. Manuf.
Ghulam Moeen Uddin, Syed Muhammad Arafat, Ali Hussain Kazim, Muhammad Farhan, Sajawal Gul Niazi, Nasir Hayat, Ibrahim Zeid, Sagar V. Kamarthi
redb/extractors/decompiler/bninja/similarity/minhasher.py
← Index redb/extractors/decompiler/bninja/similarity/minhasher.py python
import logging
import random
from enum import Enum

from ..analysis.medium_level_normalization import MediumLevelNormalization

try:
    from .minhashcustom import MinHashCustom
    from ..analysis.low_level_normalization import LowLevelNormalization
except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.similarity.minhashcustom import MinHashCustom
    from redb.extractors.decompiler.bninja.analysis.low_level_normalization import LowLevelNormalization

## Values for this configuration were extracted from https://github.com/danielplohmann/mcrit/blob/main/mcrit/config/MinHashConfig.py#L10
# Length in number of Shingles of which a minhash consists
# this value represents the length of sha256sum hash truncated
MINHASH_SIGNATURE_LENGTH: int = 64
# Number of bits per signature element (1-32 bits)
MINHASH_SIGNATURE_BITS: int = 8


class TokenKind(Enum):
    LLIL = "llil"
    TYPED_LLIL = "typed_llil"
    MLIL = "mlil"
    TYPED_MLIL = "typed_mlil"


class MinHasher:
    # stick to the default method
    MINHASH_STRATEGY_HASH_ALL = 1

    def __init__(self, seed, il_function, kind: TokenKind = TokenKind.LLIL):
        self._minhash_seeds = []
        self.il_func = il_function
        self.kind = kind
        self._minhash_permutation = []
        self._signature_segments = []
        self._initMinhashing(seed)

    def _initMinhashing(self, MINHASH_SEED=None):
        random.seed(MINHASH_SEED)
        # init sequence of seeds
        self._minhash_seeds = [
            random.randint(0, MinHashCustom.getHashMax()) for _ in range(MINHASH_SIGNATURE_LENGTH)
        ]

    def make_ngrams(self, tokens, n=3):
        """Take the ngrams of the IL we try to pass into the functions"""
        return [tuple(tokens[i:i+n]) for i in range(len(tokens) - n + 1)]

    def _extract_tokens(self):
        """Extract the IL tokens from the IL function, picking the right
        normalizer (LLIL/MLIL) and the right normalization mode
        (skeleton/typed) based on self.kind."""
        if self.kind in (TokenKind.LLIL, TokenKind.TYPED_LLIL):
            normalizer = LowLevelNormalization()
        elif self.kind in (TokenKind.MLIL, TokenKind.TYPED_MLIL):
            normalizer = MediumLevelNormalization()
        else:
            raise ValueError(f"Unsupported token kind: {self.kind}")

        # typed variants include operand type info, skeleton variants don't
        if self.kind in (TokenKind.TYPED_LLIL, TokenKind.TYPED_MLIL):
            normalize = normalizer.normalize_instr_with_operands
        else:
            normalize = normalizer.normalize_instruction_all_levels

        instructions = []
        for basic_block in self.il_func.basic_blocks:
            for il in basic_block:
                instructions.append(normalize(il))

        return instructions

    def calculateMinHash(self):
        """Calculate hash function every time, then take minimum shingle per shingler"""
        minhash_result = MinHashCustom(minhash_bits=MINHASH_SIGNATURE_BITS)
        minhash_signature = []

        tokens = self._extract_tokens()
        shingles = self.make_ngrams(tokens, n=3)

        # Functions with fewer than 3 IL instructions can't produce n-grams
        # Return empty minhash for such small functions (thunks, stubs, etc.)
        # Triggered by 39d8ad95b0323c37bd3134ab93ac4af44c66a1a8443a41c1ac02cec19bb2816a
        if not shingles:
            return []

        # Generate the MinHash
        for seed in self._minhash_seeds:
            hashed_shingles = [
                self.shingle_hash(shingle, seed) for shingle in shingles
            ]
            min_value = min(hashed_shingles)

            if MINHASH_SIGNATURE_BITS < 32:
                min_value %= (2 ** MINHASH_SIGNATURE_BITS)

            minhash_signature.append(min_value)

        minhash_result.setMinHash(minhash_signature)
        return minhash_result.getMinHashInt()

    def shingle_hash(self, shingle, hash_seed=0):
        """Produce a single 32bit UINT hash for a given shingle"""
        return MinHashCustom.hashData(shingle, hash_seed)