binaryninja-api/python/basedetection.py at dev · Vector35/binaryninja-api · GitHub

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# coding=utf-8

# Permission is hereby granted, free of charge, to any person obtaining a copy

# of this software and associated documentation files (the "Software"), to

# deal in the Software without restriction, including without limitation the

# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or

# sell copies of the Software, and to permit persons to whom the Software is

# furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in

# all copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR

# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,

# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE

# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER

# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING

# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS

# IN THE SOFTWARE.

import os

import ctypes

from typing import Optional, Union, Literal

from dataclasses import dataclass

from .enums import BaseAddressDetectionPOIType, BaseAddressDetectionConfidence, BaseAddressDetectionPOISetting, \

BaseAddressDetectionAnalysisMode

from .binaryview import BinaryView

from . import _binaryninjacore as core

from . import architecture

@dataclass

class BaseAddressDetectionReason:

"""``class BaseAddressDetectionReason`` is a class that stores information used to understand why a base address

is a candidate. It consists of a pointer, the offset of the point-of-interest that the pointer aligns with, and the

type of point-of-interest (string, function, or data variable)"""

pointer: int

offset: int

type: BaseAddressDetectionPOIType

class BaseAddressDetection:

"""

``class BaseAddressDetection`` is a class that is used to detect candidate base addresses for position-dependent

raw binaries

:Example:

>>> from binaryninja import *

>>> bad = BaseAddressDetection("firmware.bin")

>>> bad.detect_base_address()

True

>>> hex(bad.preferred_base_address)

'0x4000000'

"""

def __init__(self, view: Union[str, os.PathLike, BinaryView]) -> None:

if isinstance(view, str) or isinstance(view, os.PathLike):

view = BinaryView.load(str(view), update_analysis=False)

_handle = core.BNCreateBaseAddressDetection(view.handle)

assert _handle is not None, "core.BNCreateBaseAddressDetection returned None"

self._handle = _handle

self._view_arch = view.arch

self._scores = list()

self._confidence = 0

self._last_tested_base_address = None

def __del__(self):

if core is not None:

core.BNFreeBaseAddressDetection(self._handle)

@property

def scores(self) -> list[tuple[int, int]]:

"""

``scores`` returns a list of candidate base addresses and their scores

.. note:: The score is set to the number of times a pointer pointed to a point-of-interest at that base address

:Example:

>>> from binaryninja import *

>>> bad = BaseAddressDetection("firmware.bin")

>>> bad.detect_base_address()

True

>>> for addr, score in bad.scores:

... print(f"0x{addr:x}: {score}")

...

0x4000000: 7

0x400dc00: 1

0x400d800: 1

0x400cc00: 1

0x400c400: 1

0x400bc00: 1

0x400b800: 1

0x3fffc00: 1

:return: list of tuples containing each base address and score

:rtype: list[tuple[int, int]]

"""

return self._scores

@property

def confidence(self) -> BaseAddressDetectionConfidence:

"""

``confidence`` returns an enum that indicates confidence the preferred candidate base address is correct

:return: confidence of the base address detection results

:rtype: BaseAddressDetectionConfidence

"""

return self._confidence

@property

def last_tested_base_address(self) -> int:

"""

``last_tested_base_address`` returns the last candidate base address that was tested

.. note:: This is useful for situations where the user aborts the analysis and wants to restart from the last \

tested base address by setting the ``low_boundary`` parameter in :py:func:`BaseAddressDetection.detect_base_address`

:return: last candidate base address tested

:rtype: int

"""

return self._last_tested_base_address

@property

def preferred_base_address(self) -> Optional[int]:

"""

``preferred_base_address`` returns the candidate base address which contains the most amount of pointers that

align with discovered points-of-interest in the binary

.. note:: :py:attr:`BaseAddressDetection.confidence` reports a confidence level that the preferred base is correct

.. note:: :py:attr:`BaseAddressDetection.scores` returns a list of the top 10 candidate base addresses and their \

scores and can be used to discover other potential candidates

:return: preferred candidate base address

:rtype: int

"""

if not self._scores:

return None

return self._scores[0][0]

@property

def aborted(self) -> bool:

"""

``aborted`` indicates whether or not base address detection analysis was aborted early

:return: True if the analysis was aborted, False otherwise

:rtype: bool

"""

return core.BNIsBaseAddressDetectionAborted(self._handle)

def _resolve_arch(self, arch: Optional[Union['architecture.Architecture', str]]) -> Optional['architecture.Architecture']:

if isinstance(arch, str):

arch = architecture.Architecture[arch]

if not arch and self._view_arch:

arch = self._view_arch

return arch

def _collect_results(self) -> bool:

max_candidates = 10

scores = (core.BNBaseAddressDetectionScore * max_candidates)()

confidence = core.BaseAddressDetectionConfidenceEnum()

last_base = ctypes.c_ulonglong()

num_candidates = core.BNGetBaseAddressDetectionScores(

self._handle, scores, max_candidates, ctypes.byref(confidence), ctypes.byref(last_base)

)

if num_candidates == 0:

return False

self._scores.clear()

for i in range(num_candidates):

self._scores.append((scores[i].BaseAddress, scores[i].Score))

self._confidence = confidence.value

self._last_tested_base_address = last_base.value

return True

def detect_base_address_with_instruction_analysis(

self,

arch: Optional[Union['architecture.Architecture', str]] = None,

analysis: Literal["basic", "controlFlow", "full"] = "full",

min_strlen: int = 10,

alignment: int = 1024,

low_boundary: int = 0,

high_boundary: int = 0xFFFFFFFFFFFFFFFF,

poi_analysis: BaseAddressDetectionPOISetting = BaseAddressDetectionPOISetting.POIAnalysisAll,

max_pointers: int = 128,

) -> bool:

"""

``detect_base_address_with_instruction_analysis`` uses instruction analysis to identify candidate base addresses.

"""

arch = self._resolve_arch(arch)

if analysis not in ["basic", "controlFlow", "full"]:

raise ValueError("invalid analysis setting")

if alignment <= 0:

raise ValueError("alignment must be greater than 0")

if max_pointers < 2:

raise ValueError("max pointers must be at least 2")

if high_boundary < low_boundary:

raise ValueError("upper boundary must be greater than lower boundary")

archname = arch.name if arch else "auto detect"

settings = core.BNBaseAddressDetectionSettings(

archname.encode(),

analysis.encode(),

min_strlen,

alignment,

low_boundary,

high_boundary,

poi_analysis,

max_pointers,

BaseAddressDetectionAnalysisMode.InstructionAnalysisBaseAddressDetection,

)

if not core.BNDetectBaseAddress(self._handle, settings):

return False

return self._collect_results()

def detect_base_address_with_sampling(

self,

arch: Optional[Union['architecture.Architecture', str]] = None,

min_strlen: int = 10,

low_boundary: int = 0,

high_boundary: int = 0xFFFFFFFFFFFFFFFF,

) -> bool:

"""

``detect_base_address_with_sampling`` samples raw binary contents to identify candidate base addresses.

"""

arch = self._resolve_arch(arch)

if high_boundary < low_boundary:

raise ValueError("upper boundary must be greater than lower boundary")

archname = arch.name if arch else "auto detect"

settings = core.BNBaseAddressDetectionSettings(

archname.encode(),

b"full",

min_strlen,

low_boundary,

high_boundary,

BaseAddressDetectionPOISetting.POIAnalysisStringsOnly,

BaseAddressDetectionAnalysisMode.SamplingBaseAddressDetection,

)

if not core.BNDetectBaseAddress(self._handle, settings):

return False

return self._collect_results()

def detect_base_address(

self,

arch: Optional[Union['architecture.Architecture', str]] = None,

analysis: Literal["basic", "controlFlow", "full"] = "full",

min_strlen: int = 10,

alignment: int = 1024,

low_boundary: int = 0,

high_boundary: int = 0xFFFFFFFFFFFFFFFF,

poi_analysis: BaseAddressDetectionPOISetting = BaseAddressDetectionPOISetting.POIAnalysisAll,

max_pointers: int = 128,

analysis_mode: BaseAddressDetectionAnalysisMode = BaseAddressDetectionAnalysisMode.InstructionAnalysisBaseAddressDetection,

) -> bool:

"""

``detect_base_address`` runs initial analysis and attempts to identify candidate base addresses

.. note:: This operation can take a long time to complete depending on the size and complexity of the binary \

and the settings used

:param Architecture arch: CPU architecture of the binary (defaults to using auto-detection)

:param str analysis: analysis mode (``basic``, ``controlFlow``, or ``full``)

:param int min_strlen: minimum length of a string to be considered a point-of-interest

:param int alignment: byte boundary to align the base address to while brute-forcing

:param int low_boundary: lower boundary of the base address range to test

:param int high_boundary: upper boundary of the base address range to test

:param BaseAddressDetectionPOISetting poi_analysis: specifies types of points-of-interest to use for analysis

:param int max_pointers: maximum number of candidate pointers to collect per pointer cluster

:param BaseAddressDetectionAnalysisMode analysis_mode: base address detection algorithm to use

:return: True if initial analysis completed with results, False otherwise

:rtype: bool

"""

if analysis_mode == BaseAddressDetectionAnalysisMode.InstructionAnalysisBaseAddressDetection:

return self.detect_base_address_with_instruction_analysis(

arch, analysis, min_strlen, alignment, low_boundary, high_boundary, poi_analysis, max_pointers)

return self.detect_base_address_with_sampling(arch, min_strlen, low_boundary, high_boundary)

def abort(self) -> None:

"""

``abort`` aborts base address detection analysis

.. note:: ``abort`` does not stop base address detection until after initial analysis has completed and it is \

in the base address enumeration phase

:rtype: None

"""

core.BNAbortBaseAddressDetection(self._handle)

def get_reasons(self, base_address: int) -> list[BaseAddressDetectionReason]:

"""

``get_reasons`` returns a list of reasons that can be used to determine why a base address is a candidate

:param int base_address: base address to get reasons for

:return: list of reasons for the specified base address

:rtype: list[BaseAddressDetectionReason]

"""

count = ctypes.c_size_t()

reasons = core.BNGetBaseAddressDetectionReasons(self._handle, base_address, ctypes.byref(count))

if count.value == 0:

return []

try:

result = list()

for i in range(count.value):

result.append(BaseAddressDetectionReason(reasons[i].Pointer, reasons[i].POIOffset, reasons[i].POIType))

return result

finally:

core.BNFreeBaseAddressDetectionReasons(reasons)

def _get_data_hits_by_type(self, base_address: int, poi_type: int) -> int:

reasons = self.get_reasons(base_address)

if not reasons:

return 0

hits = 0

for reason in reasons:

if reason.type == poi_type:

hits += 1

return hits

def get_string_hits(self, base_address: int) -> int:

"""

``get_string_hits`` returns the number of times a pointer pointed to a string at the specified

base address

.. note:: Data variables are only used as points-of-interest if analysis doesn't discover enough strings and \

functions

:param int base_address: base address to get string hits for

:return: number of string hits for the specified base address

:rtype: int

"""

return self._get_data_hits_by_type(base_address, BaseAddressDetectionPOIType.POIString)

def get_function_hits(self, base_address: int) -> int:

"""

``get_function_hits`` returns the number of times a pointer pointed to a function at the

specified base address

:param int base_address: base address to get function hits for

:return: number of function hits for the specified base address

:rtype: int

"""

return self._get_data_hits_by_type(base_address, BaseAddressDetectionPOIType.POIFunction)

def get_data_hits(self, base_address: int) -> int:

"""

``get_data_hits`` returns the number of times a pointer pointed to a data variable at the

specified base address

:param int base_address: base address to get data hits for

:return: number of data hits for the specified base address

:rtype: int

"""

return self._get_data_hits_by_type(base_address, BaseAddressDetectionPOIType.POIDataVariable)

binaryninja-api/python/basedetection.py at dev · Vector35/binaryninja-api · GitHub

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