Repository: mandiant/capa
File: capa/ghidra/capa_explorer.py (Python)

Code before:
        # grab second dict, containing additional matches
        # and node data
        matches = this_capability["matches"][0][1]
        for m in get_locations(matches):
            this_locs.append(m[0])
            this_node.append(m[1])

        ghidra_data.append(CapaMatchData(this_namespace, this_scope, rule, this_locs, this_node, this_attack, this_mbc))

    return ghidra_data


def main():
    logging.basicConfig(level=logging.INFO)
    logging.getLogger().setLevel(logging.INFO)

    if not capa.ghidra.helpers.is_supported_ghidra_version():
        return capa.main.E_UNSUPPORTED_GHIDRA_VERSION

    if not capa.ghidra.helpers.is_supported_file_type():
        return capa.main.E_INVALID_FILE_TYPE

    if not capa.ghidra.helpers.is_supported_arch_type():
        return capa.main.E_INVALID_FILE_ARCH

    if not isRunningHeadless():  # type: ignore [name-defined] # noqa: F821
        capa_data = json.loads(get_capabilities())
        for item in parse_json(capa_data):
            item.tag_functions()
            item.bookmark_locations()
    return 0


if __name__ == "__main__":
    if sys.version_info < (3, 8):
        from capa.exceptions import UnsupportedRuntimeError

        raise UnsupportedRuntimeError("This version of capa can only be used with Python 3.8+")
    sys.exit(main())


Review comment (suggestion):
Let's make this check first and return a (new) error code named `E_UNSUPPORTED_GHIDRA_EXECUTION_MODE`. Please include a log message that explains what happened.

Code after:
        if selected_dir:
            rules_dir = selected_dir.getPath()
    except RuntimeError:
        # RuntimeError thrown when user selects "Cancel"
        pass

    if not rules_dir:
        logger.info("You must choose a capa rules directory before running capa.")
        return ""  # return empty str to avoid handling both int and str types

    rules_path: pathlib.Path = pathlib.Path(rules_dir)
    logger.info("running capa using rules from %s", str(rules_path))

    rules = capa.main.get_rules([rules_path])
    meta = capa.ghidra.helpers.collect_metadata([rules_path])
    extractor = capa.features.extractors.ghidra.extractor.GhidraFeatureExtractor()

    capabilities, counts = capa.main.find_capabilities(rules, extractor, True)

    if capa.main.has_file_limitation(rules, capabilities, is_standalone=False):
        popup("capa explorer encountered warnings during analysis. Please check the console output for more information.")  # type: ignore [name-defined] # noqa: F821
        logger.info("capa encountered warnings during analysis")

    return capa.render.json.render(meta, rules, capabilities)


def get_locations(match_dict):
    """recursively collect match addresses and associated nodes"""

    for loc in match_dict.get("locations", {}):
        # either an rva (absolute)
        # or an offset into a file (file)
        if loc.get("type", "") in ("absolute", "file"):
            yield loc.get("value"), match_dict.get("node")

    for child in match_dict.get("children", {}):
        yield from get_locations(child)


def parse_node(node_data):
    """pull match descriptions and sub features by parsing node dicts"""

    node = node_data.get(node_data.get("type"))

    if "description" in node:
        yield "description", node.get("description")

    data = node.get(node.get("type"))
    if isinstance(data, (str, int)):
        feat_type = node.get("type")
        if isinstance(data, int):