Carsten Konrad

12 papers Journal 12
YearRankTypeTitle / Venue / Authors
2019 J jnl
CoRR
Claas Flint, Katharina Förster, Sophie A. Koser, Carsten Konrad, Pienie Zwitserlood, Klaus Berger, Marco Hermesdorf, Tilo Kircher, Igor Nenadic, Axel Krug, Bernhard T. Baune, Katharina Dohm, Ronny Redlich, Nils Opel, Tim Hahn, Xiaoyi Jiang, Udo Dannlowski, Dominik Grotegerd
2013 J jnl
NeuroImage
Christian Beste, Carsten Konrad, Christina Uhlmann, Volker Arolt, Peter Zwanzger, Katharina Domschke
2011 J jnl
NeuroImage
Martin Pyka, Markus Burgmer, Thomas Lenzen, Regina Pioch, Udo Dannlowski, Bettina Pfleiderer, A. W. Ewert, Gereon Heuft, Volker Arolt, Carsten Konrad
2011 J jnl
NeuroImage
René J. Huster, Tom Eichele, Stefanie Enriquez-Geppert, Andreas Wollbrink, Harald Kugel, Carsten Konrad, Christo Pantev
2010 J jnl
NeuroImage
Stefanie Enriquez-Geppert, Carsten Konrad, Christo Pantev, René J. Huster
2010 J jnl
NeuroImage
Christian Beste, Katharina Domschke, Michael Falkenstein, Carsten Konrad
2010 J jnl
NeuroImage
Christian Beste, Bernhard T. Baune, Katharina Domschke, Michael Falkenstein, Carsten Konrad
2010 J jnl
NeuroImage
Udo Dannlowski, Carsten Konrad, Harald Kugel, Pienie Zwitserlood, Katharina Domschke, Sonja Schöning, Patricia Ohrmann, Jochen Bauer, Martin Pyka, Christa Hohoff, Weiqi Zhang, Bernhard T. Baune, Walter Heindel, Volker Arolt, Thomas Suslow
2010 J jnl
NeuroImage
Maximilian Bruchmann, Kristin Herper, Carsten Konrad, Christo Pantev, René J. Huster
2010 J jnl
Neuroinformatics
Martin Pyka, Matthias Hertog, Raul Fernandez, Sascha Hauke, Dominik Heider, Udo Dannlowski, Carsten Konrad
2009 J jnl
NeuroImage
Carsten Konrad, T. Ukas, C. Nebel, Volker Arolt, Arthur W. Toga, Katherine L. Narr
2006 J jnl
NeuroImage
Markus Burgmer, Carsten Konrad, Andreas Jansen, Harald Kugel, Jens Sommer, Walter Heindel, Erich Bernd Ringelstein, Gereon Heuft, Stefan Knecht
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