def import_annotation(binary: Binary, type_: FileType,
path: Path) -> Annotation:
"""Imports functions from annotation file and creates Annotation object.
Args:
binary: The Binary to which to import functions.
Returns:
the Annotation, with newly created functions.
"""
if not path.is_file():
raise FileNotFoundError
logger.info(f"Importing {type_.name} file from {path}")
ann_cls, fnc_gen = FileTypeMapping[type_]
binary.partition()
annotation = ann_cls(binary=binary, path=str(path))
meta = fnc_gen(path)
for name, addr, size, mode in meta:
if not binary.range_is_valid(addr, addr + size):
logger.debug(
f"{name} @{addr:#08X}-{addr+size:#08X} not in valid range")
continue
if len(name) > 0 and binary.range_is_valid(addr, addr + size):
fnc = Function.get(binary=binary, addr=addr)
if not fnc:
fnc = binary.functions.create(addr=addr,
size=size,
name=name,
mode=mode)
annotation.functions.add(fnc)
binary.annotations.add(annotation)
return annotation
def _cli_list(
list_history: bool,
list_targets: bool,
):
def format_binary_list(
binary_list: Iterable[Binary],
is_annotated: Optional[bool] = False) -> Iterable[dict]:
keys = ["id", "name", "filepath"]
data = []
for binary in list(binaries):
b_dict = binary.to_dict(only=keys)
if is_annotated is True:
b_dict["#annotations"] = binary.annotations.count()
b_dict["#functions"] = binary.functions.count()
data.append(b_dict)
return data
if list_history is True:
typer.echo("History Files")
binaries = Binary.select_annotated()
formatted = format_binary_list(binaries, is_annotated=True)
table = tabulate(formatted, headers="keys")
typer.echo(table)
if list_history is True and list_targets is True:
typer.echo() # additional newline for readability
if list_targets is True:
typer.echo("Target Files")
binaries = Binary.select_unannotated()
formatted = format_binary_list(binaries, is_annotated=False)
table = tabulate(formatted, headers="keys")
typer.echo(table)
def _binary_ops(binary: str, comment: str, export_csv: str, remove: bool):
b = Binary.get(name=binary)
if comment is not None:
b.comment = comment
if export_csv is not None:
export_csv_combined(b, export_csv)
if remove is True:
Binary.delete(b)
def find_starts(target: Binary, start_cut: int = 8) -> Iterable[Match]:
match_finder = make_start_scout()
itree = target.partition_without_matches()
matches = []
for interval in itree:
data = target.read()[interval.begin:interval.end]
for addr, matcher in match_finder(data, interval.begin):
match, new = Match.deduplicate(target, addr, matcher.cut_size,
dict(certainty=1))
match.matched_by.add(matcher)
if new:
target.matches.add(match)
matches.append(match)
return matches
def prepare_graph(histories: List[Path], annotations: List[Path],
min_size: int, max_rel_fuzz: float) -> Optional[Graph]:
logger.debug("Importing history")
for history, annotation in zip(histories, annotations):
bin_ = get_or_create_binary(history)
get_or_create_annotation(bin_, annotation)
logger.debug(f"Imported history {bin_.serialize()}")
if Binary.select_annotated().count() == 0:
typer.echo("No history entries in database")
return None
if histories:
logger.debug("Clearing matchers")
Matcher.reset()
logger.debug("Grouping function symbols")
groups = Function.common_functions(min_size, 1)
logger.debug("finished grouping")
logger.debug("make matchers")
matchers = create_matchers(groups, min_size, max_rel_fuzz)
logger.debug(f"{len(matchers)} matchers generated")
graph = makeGraph(matchers)
logger.debug("finish making matchers")
return graph
def match_matchers_against(target: Binary,
graph=None,
parallelize=True) -> Iterable[Match]:
"""match_candidates_against matches all candidates against the given
Binary.
Args:
target: the target binary to match the candidates against
"""
settings = SettingsStorage.get_settings()
parallelize = parallelize or settings.get("matcher_parallelization", False)
if graph is None:
graph = makeGraph()
bin_ = target.read()
partitions = target.partition()
if parallelize:
matches = parallel_prepartioned_graph_match(graph, bin_, partitions)
else:
matches = prepartioned_graph_match(graph, bin_, partitions)
match_results = []
for matchers, size, end in matches:
start = end - size
match, new = Match.deduplicate(target, start, size,
dict(certainty=1 / len(matchers)))
for matcher in matchers:
match.matched_by.add(matcher)
if new:
target.matches.add(match)
match_results.append(match)
orm.commit()
if settings.get("find_fnc_starts", False):
starts = find_starts(target,
start_cut=settings.get("fnc_start_size", 8))
match_results.extend(starts)
orm.commit()
return match_results
def get_or_create_binary(path: Path, make_target=False) -> Binary:
"""import_binary creates a Binary and stores it in database
Args:
binary_path: the file path of the binary
Returns: Binary
"""
logger.info(f"retrieving binary for path {path}")
binary = Binary.get(filepath=str(path))
if not binary:
if not path.is_file():
raise FileNotFoundError
binary = Binary(filepath=str(path), name=path.name)
elif make_target:
binary.is_target = True
binary.partition()
return binary