Carlos Figueira

13 papers C 5Journal 1Unranked 7
YearRankTypeTitle / Venue / Authors
2014 conf
EEWC
Carlos Figueira, David Aveiro
2012 conf
GIIS
Carlos Figueira, Yudith Cardinale, Franco Silva
2009 conf
ICUMT
Pedro Gonçalves, Carlos Figueira, Ricardo Azevedo, Rui L. Aguiar, José Luís Oliveira
2009 C conf
GPC
Yudith Cardinale, Jesús De Oliveira, Carlos Figueira
2007 C conf
ISPA
Yudith Cardinale, Carlos Figueira
2007 C conf
GPC
Yudith Cardinale, Carlos Figueira, Emilio Hernández, Eduardo Blanco, Jesús De Oliveira
2006 J jnl
CLEI Electron. J.
Carlos Figueira, Emilio Hernández, Eduardo Blanco
2006 C conf
ISPA
Yudith Cardinale, Jesús De Oliveira, Carlos Figueira
2005 C conf
SBAC-PAD
Eduardo Blanco, Yudith Cardinale, Carlos Figueira, Emilio Hernández, Robinson Rivas, Marta Rukoz
2001 conf
HPCN Europe
Yudith Cardinale, Mariela Curiel, Carlos Figueira, P. García, Emilio Hernández
2001 conf
HPCN Europe
Carlos Figueira, Emilio Hernández
1999 conf
PARCO
Emilio Hernández, Yudith Cardinale, Carlos Figueira, Alejandro Teruel
1994 conf
Applications in Parallel and Distributed Computing
Carlos Figueira, Emilio Hernández
redb/extractors/decompiler/apk/smali_normalization.py
← Index redb/extractors/decompiler/apk/smali_normalization.py python
"""Semantic normalization of Dalvik/smali instructions.

Analogous to Binary Ninja's LLIL normalization: strips register allocation
noise and instruction encoding variants while preserving semantic operations.

Three normalization levels (most aggressive to most detailed):
  - 'category':    semantic category only (MOV, ALU, CALL, ...)
  - 'opcode':      base opcode, width-invariant (add, sub, invoke, ...)
  - 'opcode_api':  opcode category + API method/field references for
                   invoke/field/alloc instructions (default for MinHash)

References:
  - Smali+ 12-category reduction (Canfora et al.)
  - MOSDroid opcode family grouping
  - DroidSIFT/DroidSim API-sensitive similarity
"""

import re
from typing import List

# ---------------------------------------------------------------------------
# Dalvik opcode -> semantic category mapping
# ---------------------------------------------------------------------------
# Prefix-matched against instruction opcodes. Order matters for overlapping
# prefixes (longer/more-specific prefixes should come first in iteration,
# but since we use startswith and break on first match, we order by
# specificity within the list).

OPCODE_CATEGORIES = {
    # Arithmetic/logic
    "add": "ALU", "sub": "ALU", "mul": "ALU", "div": "ALU",
    "rem": "ALU", "and": "ALU", "or": "ALU", "xor": "ALU",
    "shl": "ALU", "shr": "ALU", "ushr": "ALU", "neg": "ALU",
    "not": "ALU",
    # Data movement
    "move": "MOV", "const": "CONST",
    # Memory access (field/array)
    "iget": "LOAD", "sget": "LOAD", "aget": "LOAD",
    "iput": "STORE", "sput": "STORE", "aput": "STORE",
    # Invocations
    "invoke": "CALL",
    # Control flow
    "if": "BRANCH", "goto": "JMP",
    "switch": "SWITCH",
    "return": "RET",
    # Object/type
    "new": "ALLOC", "check": "TYPE", "instance": "TYPE",
    # Array
    "fill": "ARR", "array": "ARR",
    # Comparison
    "cmpl": "CMP", "cmpg": "CMP", "cmp": "CMP",
    # Exception / synchronization
    "throw": "EXC", "monitor": "SYNC",
    # Conversion (int-to-long, float-to-int, etc.)
    "int-to": "CONV", "long-to": "CONV", "float-to": "CONV",
    "double-to": "CONV",
}

# Pre-compiled regexes for operand extraction
_METHOD_REF_RE = re.compile(r"(L[\w/$]+;->[\w<>]+\(.*?\)[\w/$;\[]*)")
_FIELD_REF_RE = re.compile(r"(L[\w/$]+;->[\w]+:[\w/$;\[]+)")
_CLASS_REF_RE = re.compile(r"(L[\w/$]+;)")
_CONST_STRING_RE = re.compile(r'^const-string(?:/jumbo)?\s')


def categorize_opcode(opcode: str) -> str:
    """Map a Dalvik opcode to its semantic category.

    Prefix-matched: 'add-int/2addr' matches 'add' -> 'ALU'.
    Returns 'OTHER' for unrecognized opcodes.
    """
    for prefix, cat in OPCODE_CATEGORIES.items():
        if opcode.startswith(prefix):
            return cat
    return "OTHER"


# Mapping from semantic categories to the ACFG feature vector indices
# used by Binary Ninja's build_block_features (cfg_features.py).
# This enables cross-platform ACFG feature comparison.
CATEGORY_TO_ACFG_INDEX = {
    "ALU": 0,       # CAT_ARITHMETIC
    "CONV": 0,      # arithmetic-adjacent
    "CMP": 4,       # CAT_COMPARISON
    "MOV": 2,       # CAT_TRANSFER
    "CONST": 2,     # transfer-adjacent (loading constants)
    "LOAD": 5,      # CAT_MEMORY
    "STORE": 5,     # CAT_MEMORY
    "CALL": 3,      # CAT_CALL
    "BRANCH": 1,    # CAT_LOGIC (conditional logic)
    "JMP": 1,       # CAT_LOGIC
    "SWITCH": 1,    # CAT_LOGIC
    "RET": 2,       # CAT_TRANSFER
    "ALLOC": 5,     # CAT_MEMORY (heap allocation)
    "TYPE": 6,      # CAT_OTHER
    "ARR": 5,       # CAT_MEMORY
    "EXC": 6,       # CAT_OTHER
    "SYNC": 6,      # CAT_OTHER
    "OTHER": 6,     # CAT_OTHER
}


def normalize_instruction(line: str, level: str = "opcode_api") -> str:
    """Normalize a single smali instruction line.

    Args:
        line: A single smali instruction (whitespace-stripped).
        level: Normalization level:
            'category'   - most aggressive: just semantic category
            'opcode'     - base opcode only, width/addressing-mode invariant
            'opcode_api' - category + API references for invoke/field/alloc
                          (default, best for MinHash similarity)

    Returns:
        Normalized instruction string, or empty string for non-instructions.
    """
    stripped = line.strip()
    if not stripped:
        return ""

    parts = stripped.split(None, 1)
    opcode = parts[0]
    operands = parts[1] if len(parts) > 1 else ""

    if level == "category":
        return categorize_opcode(opcode)

    if level == "opcode":
        # Strip type/width suffixes for invariance:
        # add-int, add-long, add-float -> 'add'
        # add-int/2addr -> 'add'
        base = re.split(r"[-/]", opcode)[0]
        return base

    if level == "opcode_api":
        # const-string: preserve string content (encrypted strings are a
        # key malware indicator)
        if _CONST_STRING_RE.match(stripped):
            # Extract the string literal
            str_match = re.search(r'"(.*)"', operands)
            if str_match:
                return f"CONST_STR \"{str_match.group(1)}\""
            return "CONST_STR"

        # invoke-*: preserve method reference
        if opcode.startswith("invoke"):
            ref = _METHOD_REF_RE.search(operands)
            if ref:
                return f"CALL {ref.group(1)}"
            return "CALL"

        # Field access: preserve field reference
        if opcode.startswith(("iget", "iput", "sget", "sput")):
            ref = _FIELD_REF_RE.search(operands)
            if ref:
                cat = "LOAD" if "get" in opcode else "STORE"
                return f"{cat} {ref.group(1)}"
            # Fallback: try space-separated format from androguard
            # e.g. "iget v0, p0, Lcom/Foo;->field Ljava/lang/String;"
            space_ref = re.search(
                r"(L[\w/$]+;->[\w]+)\s+([\w/$;\[]+)", operands
            )
            if space_ref:
                cat = "LOAD" if "get" in opcode else "STORE"
                return f"{cat} {space_ref.group(1)}:{space_ref.group(2)}"
            cat = "LOAD" if "get" in opcode else "STORE"
            return cat

        # new-instance: preserve allocated type
        if opcode.startswith("new-instance") or opcode == "new-array":
            ref = _CLASS_REF_RE.search(operands)
            if ref:
                return f"ALLOC {ref.group(1)}"
            return "ALLOC"

        # Everything else: just the category
        return categorize_opcode(opcode)

    # Unknown level: return raw opcode
    return opcode


def normalize_method_body(
    body: str, level: str = "opcode_api"
) -> List[str]:
    """Normalize all instructions in a smali method body.

    Filters out directives (.), labels (:), comments (#), and blank lines.
    Returns a list of normalized instruction strings.

    Args:
        body: Raw smali method body text.
        level: Normalization level (see normalize_instruction).

    Returns:
        List of normalized instruction strings (no empty strings).
    """
    normalized = []
    for line in body.split("\n"):
        stripped = line.strip()
        # Skip non-instructions
        if not stripped:
            continue
        if stripped.startswith((".",":", "#")):
            continue
        result = normalize_instruction(stripped, level)
        if result:
            normalized.append(result)
    return normalized