Varsha Bhat Kukkala

29 papers A* 4B 1Misc 3Journal 19Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Trans. Dependable Secur. Comput.
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2025 J jnl
Proc. Priv. Enhancing Technol.
Pranav Jangir, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2025 J jnl
IACR Cryptol. ePrint Arch.
Andreas Brüggemann, Nishat Koti, Varsha Bhat Kukkala, Thomas Schneider
2025 J jnl
Proc. Priv. Enhancing Technol.
Andreas Brüggemann, Nishat Koti, Varsha Bhat Kukkala, Thomas Schneider
2025 J jnl
IACR Cryptol. ePrint Arch.
Siddharth Kapoor, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2024 A* conf
CCS
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2024 J jnl
IACR Cryptol. ePrint Arch.
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2024 J jnl
IEEE Trans. Dependable Secur. Comput.
Pranav Jangir, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal, Somya Sangal
2023 J jnl
IACR Cryptol. ePrint Arch.
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2023 J jnl
Proc. Priv. Enhancing Technol.
Pranav Shriram A, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2023 J jnl
Proc. Priv. Enhancing Technol.
Pranav Shriram A, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal, Somya Sangal
2023 J jnl
IACR Cryptol. ePrint Arch.
Pranav Shriram A, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal, Somya Sangal
2023 A* conf
WWW
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2023 J jnl
IACR Cryptol. ePrint Arch.
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2022 J jnl
IACR Cryptol. ePrint Arch.
Aditya Hegde, Nishat Koti, Varsha Bhat Kukkala, Shravani Patil, Arpita Patra, Protik Paul
2022 conf
ASIACRYPT (1)
Aditya Hegde, Nishat Koti, Varsha Bhat Kukkala, Shravani Patil, Arpita Patra, Protik Paul
2022 J jnl
IACR Cryptol. ePrint Arch.
Pranav Shriram A, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2022 A* conf
CCS
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2022 J jnl
IACR Cryptol. ePrint Arch.
Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal
2022 A* conf
CCS
Pranav Jangir, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal, Somya Sangal
2022 J jnl
IACR Cryptol. ePrint Arch.
Pranav Jangir, Nishat Koti, Varsha Bhat Kukkala, Arpita Patra, Bhavish Raj Gopal, Somya Sangal
2020 J jnl
Proc. Priv. Enhancing Technol.
Varsha Bhat Kukkala, S. R. S. Iyengar
2018 B conf
CANS
Varsha Bhat Kukkala, S. R. S. Iyengar
2018 conf
WWW (Companion Volume)
Varsha Bhat Kukkala
2017 J jnl
CoRR
Varsha Bhat Kukkala, S. R. S. Iyengar
2017 Misc conf
ICDCN
Varsha Bhat Kukkala, Jaspal Singh Saini, S. R. S. Iyengar
2016 J jnl
IACR Cryptol. ePrint Arch.
Varsha Bhat Kukkala, Jaspal Singh Saini, S. R. S. Iyengar
2016 Misc conf
ICISS
Varsha Bhat Kukkala, Jaspal Singh Saini, S. R. S. Iyengar
2016 Misc conf
COMSNETS
Varsha Bhat Kukkala, S. R. S. Iyengar, Jaspal Singh Saini
redb/extractors/decompiler/bninja/analysis/cfg.py
← Index redb/extractors/decompiler/bninja/analysis/cfg.py python
from binaryninja.enums import LowLevelILOperation as LLIL_OP

# Support both package and standalone imports
try:
    from . import cfg_features
except ImportError:
    from redb.extractors.decompiler.bninja.analysis import cfg_features


# ---------------------------------------------------------------------------
# Task 2.2: Build LLIL operation maps at import time using real enum values
# ---------------------------------------------------------------------------

# Prime product map: LLIL operation integer value -> small prime
cfg_features.LLIL_OP_PRIMES = {
    # SET_REG, SET_REG_SPLIT
    LLIL_OP.LLIL_SET_REG.value: 2,
    LLIL_OP.LLIL_SET_REG_SPLIT.value: 2,
    # SET_FLAG
    LLIL_OP.LLIL_SET_FLAG.value: 3,
    # LOAD
    LLIL_OP.LLIL_LOAD.value: 5,
    # STORE
    LLIL_OP.LLIL_STORE.value: 7,
    # PUSH, POP
    LLIL_OP.LLIL_PUSH.value: 11,
    LLIL_OP.LLIL_POP.value: 13,
    # CALL, TAILCALL, SYSCALL
    LLIL_OP.LLIL_CALL.value: 17,
    LLIL_OP.LLIL_TAILCALL.value: 17,
    LLIL_OP.LLIL_SYSCALL.value: 19,
    # RET, NORET
    LLIL_OP.LLIL_RET.value: 23,
    LLIL_OP.LLIL_NORET.value: 23,
    # IF, GOTO
    LLIL_OP.LLIL_IF.value: 29,
    LLIL_OP.LLIL_GOTO.value: 31,
    # ADD, SUB
    LLIL_OP.LLIL_ADD.value: 37,
    LLIL_OP.LLIL_SUB.value: 41,
    # AND, OR, XOR
    LLIL_OP.LLIL_AND.value: 43,
    LLIL_OP.LLIL_OR.value: 47,
    LLIL_OP.LLIL_XOR.value: 53,
    # LSL, LSR, ASR, ROL, ROR
    LLIL_OP.LLIL_LSL.value: 59,
    LLIL_OP.LLIL_LSR.value: 61,
    LLIL_OP.LLIL_ASR.value: 67,
    LLIL_OP.LLIL_ROL.value: 71,
    LLIL_OP.LLIL_ROR.value: 73,
    # MUL, DIVU, DIVS, MODU, MODS
    LLIL_OP.LLIL_MUL.value: 79,
    LLIL_OP.LLIL_DIVU.value: 83,
    LLIL_OP.LLIL_DIVS.value: 83,
    LLIL_OP.LLIL_MODU.value: 89,
    LLIL_OP.LLIL_MODS.value: 89,
    # NEG, NOT
    LLIL_OP.LLIL_NEG.value: 97,
    LLIL_OP.LLIL_NOT.value: 101,
    # CMP_E, CMP_NE, CMP_SLT, CMP_ULT, CMP_SLE, CMP_ULE
    # CMP_SGT, CMP_UGT, CMP_SGE, CMP_UGE
    LLIL_OP.LLIL_CMP_E.value: 103,
    LLIL_OP.LLIL_CMP_NE.value: 103,
    LLIL_OP.LLIL_CMP_SLT.value: 107,
    LLIL_OP.LLIL_CMP_ULT.value: 107,
    LLIL_OP.LLIL_CMP_SLE.value: 109,
    LLIL_OP.LLIL_CMP_ULE.value: 109,
    LLIL_OP.LLIL_CMP_SGT.value: 113,
    LLIL_OP.LLIL_CMP_UGT.value: 113,
    LLIL_OP.LLIL_CMP_SGE.value: 127,
    LLIL_OP.LLIL_CMP_UGE.value: 127,
    # NOP
    LLIL_OP.LLIL_NOP.value: 1,
    # SX, ZX, LOW_PART, BOOL_TO_INT
    LLIL_OP.LLIL_SX.value: 131,
    LLIL_OP.LLIL_ZX.value: 137,
    LLIL_OP.LLIL_LOW_PART.value: 139,
    LLIL_OP.LLIL_BOOL_TO_INT.value: 149,
    # JUMP, JUMP_TO
    LLIL_OP.LLIL_JUMP.value: 151,
    LLIL_OP.LLIL_JUMP_TO.value: 151,
}

# Category map: LLIL operation integer value -> category index
_ARITHMETIC = {
    LLIL_OP.LLIL_ADD, LLIL_OP.LLIL_ADC, LLIL_OP.LLIL_SUB, LLIL_OP.LLIL_SBB,
    LLIL_OP.LLIL_MUL, LLIL_OP.LLIL_MULU_DP, LLIL_OP.LLIL_MULS_DP,
    LLIL_OP.LLIL_DIVU, LLIL_OP.LLIL_DIVU_DP, LLIL_OP.LLIL_DIVS,
    LLIL_OP.LLIL_DIVS_DP, LLIL_OP.LLIL_MODU, LLIL_OP.LLIL_MODS,
    LLIL_OP.LLIL_NEG,
}
_LOGIC = {
    LLIL_OP.LLIL_AND, LLIL_OP.LLIL_OR, LLIL_OP.LLIL_XOR, LLIL_OP.LLIL_NOT,
    LLIL_OP.LLIL_LSL, LLIL_OP.LLIL_LSR, LLIL_OP.LLIL_ASR,
    LLIL_OP.LLIL_ROL, LLIL_OP.LLIL_RLC, LLIL_OP.LLIL_ROR, LLIL_OP.LLIL_RRC,
}
_TRANSFER = {
    LLIL_OP.LLIL_SET_REG, LLIL_OP.LLIL_SET_REG_SPLIT, LLIL_OP.LLIL_SET_FLAG,
    LLIL_OP.LLIL_GOTO, LLIL_OP.LLIL_IF, LLIL_OP.LLIL_JUMP, LLIL_OP.LLIL_JUMP_TO,
    LLIL_OP.LLIL_RET, LLIL_OP.LLIL_NORET, LLIL_OP.LLIL_PUSH, LLIL_OP.LLIL_POP,
}
_CALL = {
    LLIL_OP.LLIL_CALL, LLIL_OP.LLIL_TAILCALL, LLIL_OP.LLIL_SYSCALL,
}
_COMPARISON = {
    LLIL_OP.LLIL_CMP_E, LLIL_OP.LLIL_CMP_NE,
    LLIL_OP.LLIL_CMP_SLT, LLIL_OP.LLIL_CMP_ULT,
    LLIL_OP.LLIL_CMP_SLE, LLIL_OP.LLIL_CMP_ULE,
    LLIL_OP.LLIL_CMP_SGE, LLIL_OP.LLIL_CMP_UGE,
    LLIL_OP.LLIL_CMP_SGT, LLIL_OP.LLIL_CMP_UGT,
    LLIL_OP.LLIL_TEST_BIT, LLIL_OP.LLIL_FLAG_COND,
}
_MEMORY = {
    LLIL_OP.LLIL_LOAD, LLIL_OP.LLIL_STORE,
}

cfg_features.LLIL_OP_CATEGORIES = {}
for _op in _ARITHMETIC:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_ARITHMETIC
for _op in _LOGIC:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_LOGIC
for _op in _TRANSFER:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_TRANSFER
for _op in _CALL:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_CALL
for _op in _COMPARISON:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_COMPARISON
for _op in _MEMORY:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_MEMORY

# Set of CALL operation values for counting
_CALL_OPS = {op.value for op in _CALL}


# ---------------------------------------------------------------------------
# Task 2.1 + 2.3: Rewritten CFGAnalysis
# ---------------------------------------------------------------------------

class CFGAnalysis:
    def __init__(self, function, llil_function=None):
        self.function = function
        self.llil_function = llil_function

    def extract_function_cfg(self):
        """Extract function-level CFG features as a flat dictionary."""

        if self.function is None:
            return None

        blocks = list(self.function.basic_blocks)
        if not blocks:
            return None

        n = len(blocks)

        # 1. Build index-based adjacency from Binary Ninja blocks
        addr_to_idx = {b.start: i for i, b in enumerate(blocks)}
        successors = [[] for _ in range(n)]
        predecessors = [[] for _ in range(n)]
        for i, block in enumerate(blocks):
            for edge in block.outgoing_edges:
                if edge.target is None:
                    continue
                target_idx = addr_to_idx.get(edge.target.start)
                if target_idx is not None:
                    successors[i].append(target_idx)
                    predecessors[target_idx].append(i)

        # 2. BFS order (reusable across multiple features)
        bfs = cfg_features.bfs_order(successors, n)

        # 3. Collect per-block LLIL operations (for prime product + ACFG features)
        block_llil_ops = self._collect_block_llil_ops(blocks, addr_to_idx, n)
        all_llil_ops = [op for block_ops in block_llil_ops for op in block_ops]

        # 4. Structural counts
        edge_count = sum(len(s) for s in successors)
        total_llil = sum(len(ops) for ops in block_llil_ops)
        call_count = sum(
            1 for ops in block_llil_ops for op in ops
            if op in _CALL_OPS
        )

        # 5. Compute all features
        bb_features = cfg_features.build_block_features(block_llil_ops, successors, n)

        return {
            "cfg_topology_hash": cfg_features.compute_topology_hash(successors, bfs, n),
            "block_count": n,
            "edge_count": edge_count,
            "llil_total_operations": total_llil,
            "call_count": call_count,
            "cyclomatic_complexity": edge_count - n + 2,
            "loop_count": cfg_features.count_back_edges(successors, n),
            "max_depth": cfg_features.bfs_max_depth(successors, n),
            "max_fan_out": max((len(s) for s in successors), default=0),
            "md_index_topdown": cfg_features.compute_md_index_topdown(successors, predecessors, bfs),
            "md_index_bottomup": cfg_features.compute_md_index_bottomup(successors, predecessors, n),
            "prime_product_llil": cfg_features.compute_prime_product(all_llil_ops),
            "cfg_feature_tlsh": cfg_features.compute_cfg_feature_tlsh(bb_features, bfs),
            "wl_minhash": cfg_features.compute_wl_minhash(successors, predecessors, bb_features, n),
            "bb_features": bb_features,
            "cfg_adjacency": cfg_features.pack_adjacency(successors),
        }

    def _collect_block_llil_ops(self, blocks, addr_to_idx, n):
        """
        Collect LLIL operation integers per native basic block.
        Walks the full expression tree of each instruction so that
        nested operations (e.g. ADD inside SET_REG) are captured.
        Returns list of n lists, one per block.
        """
        block_ops = [[] for _ in range(n)]

        if self.llil_function is None:
            return block_ops

        try:
            for llil_block in self.llil_function.basic_blocks:
                # Map LLIL block to native block via source_block
                if llil_block.source_block is not None:
                    native_idx = addr_to_idx.get(llil_block.source_block.start)
                    if native_idx is not None:
                        for instr in llil_block:
                            self._walk_llil_ops(instr, block_ops[native_idx])
        except Exception:
            pass  # Return empty ops — LLIL-dependent fields will be 0/null

        return block_ops

    @staticmethod
    def _walk_llil_ops(expr, ops_list):
        """Collect operation values from an LLIL expression tree iteratively."""
        stack = [expr]
        while stack:
            node = stack.pop()
            if hasattr(node, 'operation'):
                ops_list.append(node.operation.value)
            if hasattr(node, 'operands'):
                for operand in node.operands:
                    if hasattr(operand, 'operation'):
                        stack.append(operand)