Display analysis information

CHANGELOG.md

@@ -10,6 +10,7 @@
 - render maec/* fields #843 @s-ff
 - replace Halo spinner with Rich #2086 @s-ff
 - optimize rule matching #2080 @williballenthin
+- display analysis information to users #857 @s-ff
 
 ### Breaking Changes
 

capa/capabilities/common.py

@@ -37,10 +37,10 @@ def find_file_capabilities(ruleset: RuleSet, extractor: FeatureExtractor, functi
     file_features.update(function_features)
 
     _, matches = ruleset.match(Scope.FILE, file_features, NO_ADDRESS)
-    return matches, len(file_features)
+    return matches, file_features
 
 
-def has_file_limitation(rules: RuleSet, capabilities: MatchResults, is_standalone=True) -> bool:
+def has_file_limitation(rules: RuleSet, capabilities: MatchResults) -> bool:
     file_limitation_rules = list(filter(lambda r: r.is_file_limitation_rule(), rules.rules.values()))
 
     for file_limitation_rule in file_limitation_rules:
@@ -51,9 +51,6 @@ def has_file_limitation(rules: RuleSet, capabilities: MatchResults, is_standalon
         for line in file_limitation_rule.meta.get("description", "").split("\n"):
             logger.warning(" %s", line)
         logger.warning(" Identified via rule: %s", file_limitation_rule.name)
-        if is_standalone:
-            logger.warning(" ")
-            logger.warning(" Use -v or -vv if you really want to see the capabilities identified by capa.")
         logger.warning("-" * 80)
 
         # bail on first file limitation

capa/capabilities/static.py

@@ -21,6 +21,8 @@
 from capa.rules import Scope, RuleSet
 from capa.engine import FeatureSet, MatchResults
 from capa.helpers import redirecting_print_to_tqdm
+from capa.features.file import Import
+from capa.features.insn import API
 from capa.capabilities.common import find_file_capabilities
 from capa.features.extractors.base_extractor import BBHandle, InsnHandle, FunctionHandle, StaticFeatureExtractor
 
@@ -96,7 +98,7 @@ def find_basic_block_capabilities(
 
 def find_code_capabilities(
     ruleset: RuleSet, extractor: StaticFeatureExtractor, fh: FunctionHandle
-) -> Tuple[MatchResults, MatchResults, MatchResults, int]:
+) -> Tuple[MatchResults, MatchResults, MatchResults, FeatureSet]:
     """
     find matches for the given rules within the given function.
 
@@ -129,7 +131,7 @@ def find_code_capabilities(
         function_features[feature].add(va)
 
     _, function_matches = ruleset.match(Scope.FUNCTION, function_features, fh.address)
-    return function_matches, bb_matches, insn_matches, len(function_features)
+    return function_matches, bb_matches, insn_matches, function_features
 
 
 def find_static_capabilities(
@@ -141,6 +143,8 @@ def find_static_capabilities(
 
     feature_counts = rdoc.StaticFeatureCounts(file=0, functions=())
     library_functions: Tuple[rdoc.LibraryFunction, ...] = ()
+    apicall_count: int = 0
+    import_count: int = 0
 
     assert isinstance(extractor, StaticFeatureExtractor)
     with redirecting_print_to_tqdm(disable_progress):
@@ -180,12 +184,18 @@ def pbar(s, *args, **kwargs):
                         pb.set_postfix_str(f"skipped {n_libs} library functions ({percentage}%)")
                     continue
 
-                function_matches, bb_matches, insn_matches, feature_count = find_code_capabilities(
+                function_matches, bb_matches, insn_matches, function_features = find_code_capabilities(
                     ruleset, extractor, f
                 )
+                feature_count = len(function_features)
                 feature_counts.functions += (
                     rdoc.FunctionFeatureCount(address=frz.Address.from_capa(f.address), count=feature_count),
                 )
+                # cumulatively count the total number of API calls
+                for feature, vas in function_features.items():
+                    if isinstance(feature, API):
+                        apicall_count += len(vas)
+
                 t1 = time.time()
 
                 match_count = 0
@@ -223,9 +233,15 @@ def pbar(s, *args, **kwargs):
         rule = ruleset[rule_name]
         capa.engine.index_rule_matches(function_and_lower_features, rule, locations)
 
-    all_file_matches, feature_count = find_file_capabilities(ruleset, extractor, function_and_lower_features)
+    all_file_matches, file_features = find_file_capabilities(ruleset, extractor, function_and_lower_features)
+    feature_count = len(file_features)
     feature_counts.file = feature_count
 
+    # cumulatively count the total number of Import features
+    for feature, _ in file_features.items():
+        if isinstance(feature, Import):
+            import_count += 1
+
     matches: MatchResults = dict(
         itertools.chain(
             # each rule exists in exactly one scope,
@@ -241,6 +257,8 @@ def pbar(s, *args, **kwargs):
     meta = {
         "feature_counts": feature_counts,
         "library_functions": library_functions,
+        "apicall_count": apicall_count,
+        "import_count": import_count,
     }
 
     return matches, meta

capa/ghidra/capa_explorer.py

@@ -240,7 +240,7 @@ def get_capabilities():
 
     capabilities, counts = capa.capabilities.common.find_capabilities(rules, extractor, True)
 
-    if capa.capabilities.common.has_file_limitation(rules, capabilities, is_standalone=False):
+    if capa.capabilities.common.has_file_limitation(rules, capabilities):
         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")
 

capa/ghidra/capa_ghidra.py

@@ -80,7 +80,7 @@ def run_headless():
     meta.analysis.library_functions = counts["library_functions"]
     meta.analysis.layout = capa.loader.compute_layout(rules, extractor, capabilities)
 
-    if capa.capabilities.common.has_file_limitation(rules, capabilities, is_standalone=True):
+    if capa.capabilities.common.has_file_limitation(rules, capabilities):
         logger.info("capa encountered warnings during analysis")
 
     if args.json:
@@ -130,7 +130,7 @@ def run_ui():
     meta.analysis.library_functions = counts["library_functions"]
     meta.analysis.layout = capa.loader.compute_layout(rules, extractor, capabilities)
 
-    if capa.capabilities.common.has_file_limitation(rules, capabilities, is_standalone=False):
+    if capa.capabilities.common.has_file_limitation(rules, capabilities):
         logger.info("capa encountered warnings during analysis")
 
     if verbose == "vverbose":

capa/ghidra/helpers.py

@@ -156,5 +156,7 @@ def collect_metadata(rules: List[Path]):
             ),
             feature_counts=rdoc.StaticFeatureCounts(file=0, functions=()),
             library_functions=(),
+            apicall_count=0,
+            import_count=0,
         ),
     )

capa/ida/helpers.py

@@ -170,6 +170,8 @@ def collect_metadata(rules: List[Path]):
             # ignore these for now - not used by IDA plugin.
             feature_counts=rdoc.StaticFeatureCounts(file=0, functions=()),
             library_functions=(),
+            apicall_count=0,
+            import_count=0,
         ),
     )
 

capa/ida/plugin/form.py

@@ -811,7 +811,7 @@ def slot_progress_feature_extraction(text):
 
                         capa.ida.helpers.inform_user_ida_ui("capa encountered file type warnings during analysis")
 
-                    if capa.capabilities.common.has_file_limitation(ruleset, capabilities, is_standalone=False):
+                    if capa.capabilities.common.has_file_limitation(ruleset, capabilities):
                         capa.ida.helpers.inform_user_ida_ui("capa encountered file limitation warnings during analysis")
                 except Exception as e:
                     logger.exception("Failed to check for file limitations (error: %s)", e)

capa/loader.py

@@ -350,6 +350,8 @@ def get_sample_analysis(format_, arch, os_, extractor, rules_path, counts):
             ),
             feature_counts=counts["feature_counts"],
             library_functions=counts["library_functions"],
+            apicall_count=counts["apicall_count"],
+            import_count=counts["import_count"],
         )
     elif isinstance(extractor, DynamicFeatureExtractor):
         return rdoc.DynamicAnalysis(

capa/main.py

@@ -75,7 +75,7 @@
     FORMAT_RESULT,
 )
 from capa.capabilities.common import find_capabilities, has_file_limitation, find_file_capabilities
-from capa.features.extractors.base_extractor import FeatureExtractor, StaticFeatureExtractor, DynamicFeatureExtractor
+from capa.features.extractors.base_extractor import FeatureExtractor, DynamicFeatureExtractor
 
 RULES_PATH_DEFAULT_STRING = "(embedded rules)"
 SIGNATURES_PATH_DEFAULT_STRING = "(embedded signatures)"
@@ -670,12 +670,6 @@ def find_file_limitations_from_cli(args, rules: RuleSet, file_extractors: List[F
         # file limitations that rely on non-file scope won't be detected here.
         # nor on FunctionName features, because pefile doesn't support this.
         found_file_limitation = has_file_limitation(rules, pure_file_capabilities)
-        if found_file_limitation:
-            # bail if capa encountered file limitation e.g. a packed binary
-            # do show the output in verbose mode, though.
-            if not (args.verbose or args.vverbose or args.json):
-                logger.debug("file limitation short circuit, won't analyze fully.")
-                raise ShouldExitError(E_FILE_LIMITATION)
     return found_file_limitation
 
 
@@ -804,7 +798,7 @@ def main(argv: Optional[List[str]] = None):
         input_format = get_input_format_from_cli(args)
         rules = get_rules_from_cli(args)
         file_extractors = get_file_extractors_from_cli(args, input_format)
-        found_file_limitation = find_file_limitations_from_cli(args, rules, file_extractors)
+        _ = find_file_limitations_from_cli(args, rules, file_extractors)
     except ShouldExitError as e:
         return e.status_code
 
@@ -837,12 +831,6 @@ def main(argv: Optional[List[str]] = None):
         meta = capa.loader.collect_metadata(argv, args.input_file, input_format, os_, args.rules, extractor, counts)
         meta.analysis.layout = capa.loader.compute_layout(rules, extractor, capabilities)
 
-        if isinstance(extractor, StaticFeatureExtractor) and found_file_limitation:
-            # bail if capa's static feature extractor encountered file limitation e.g. a packed binary
-            # do show the output in verbose mode, though.
-            if not (args.verbose or args.vverbose or args.json):
-                return E_FILE_LIMITATION
-
     if args.json:
         print(capa.render.json.render(meta, rules, capabilities))
     elif args.vverbose:
@@ -890,8 +878,10 @@ def ida_main():
 
     meta.analysis.feature_counts = counts["feature_counts"]
     meta.analysis.library_functions = counts["library_functions"]
+    meta.analysis.apicall_count = counts["apicall_count"]
+    meta.analysis.import_count = counts["import_count"]
 
-    if has_file_limitation(rules, capabilities, is_standalone=False):
+    if has_file_limitation(rules, capabilities):
         capa.ida.helpers.inform_user_ida_ui("capa encountered warnings during analysis")
 
     colorama.init(strip=True)
@@ -928,8 +918,10 @@ def ghidra_main():
 
     meta.analysis.feature_counts = counts["feature_counts"]
     meta.analysis.library_functions = counts["library_functions"]
+    meta.analysis.apicall_count = counts["apicall_count"]
+    meta.analysis.import_count = counts["import_count"]
 
-    if has_file_limitation(rules, capabilities, is_standalone=False):
+    if has_file_limitation(rules, capabilities):
         logger.info("capa encountered warnings during analysis")
 
     print(capa.render.default.render(meta, rules, capabilities))

capa/render/default.py

@@ -19,6 +19,9 @@
 
 tabulate.PRESERVE_WHITESPACE = True
 
+MIN_LIBFUNCS_RATIO = 0.4
+MIN_API_CALLS = 10
+
 
 def width(s: str, character_count: int) -> str:
     """pad the given string to at least `character_count`"""
@@ -29,6 +32,27 @@ def width(s: str, character_count: int) -> str:
 
 
 def render_meta(doc: rd.ResultDocument, ostream: StringIO):
+    if isinstance(doc.meta.analysis, rd.StaticAnalysis):
+
+        if doc.meta.analysis.apicall_count < MIN_API_CALLS:
+            ostream.write(
+                rutils.bold(
+                    "The analyzed sample reports very few API calls, this could indicate that it is packed, encrypted, corrupted, or tiny\n"
+                )
+            )
+
+        n_libs: int = len(doc.meta.analysis.library_functions)
+        n_funcs: int = len(doc.meta.analysis.feature_counts.functions)
+        lib_ratio: float = n_libs / (n_funcs + n_libs) if (n_funcs + n_libs) > 0 else 0
+
+        if lib_ratio < MIN_LIBFUNCS_RATIO:
+            ostream.write(
+                rutils.bold(
+                    "Few library functions (%.2f%% of all functions) recognized by FLIRT signatures, results may contain false positives\n"
+                )
+                % (100 * lib_ratio)
+            )
+
     rows = [
         (width("md5", 22), width(doc.meta.sample.md5, 82)),
         ("sha1", doc.meta.sample.sha1),

capa/render/proto/__init__.py

@@ -703,6 +703,8 @@ def static_analysis_from_pb2(analysis: capa_pb2.StaticAnalysis) -> rd.StaticAnal
         library_functions=tuple(
             [rd.LibraryFunction(address=addr_from_pb2(lf.address), name=lf.name) for lf in analysis.library_functions]
         ),
+        apicall_count=analysis.apicall_count,
+        import_count=analysis.import_count,
     )
 
 

capa/render/proto/capa.proto

@@ -403,6 +403,9 @@ message StaticAnalysis {
   StaticLayout layout = 7;
   StaticFeatureCounts feature_counts = 8;
   repeated LibraryFunction library_functions = 9;
+  uint64 apicall_count = 10;
+  uint64 import_count = 11;
+
 }
 
 message StaticFeatureCounts {