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fix(detector): detect bool method replay #153

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fix(detector): detect bool method replay #153

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106 changes: 105 additions & 1 deletion kernelguard.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2462,6 +2462,104 @@ def _has_ver(expr: ast.AST | None) -> bool:
return []


def detect_bool_method_replay(code: str | SubmissionFacts) -> list[dict]:
"""Pattern: object truthiness guards replay from its stored state."""
facts = ensure_submission_facts(code)
tree = facts.ast_tree
if tree is None:
return []
entrypoint_name = entrypoint_label(facts.entrypoint_name)

bool_classes = {
stmt.name
for stmt in tree.body
if isinstance(stmt, ast.ClassDef)
and any(
isinstance(item, ast.FunctionDef) and item.name == "__bool__"
for item in stmt.body
)
}
instances = {
stmt.targets[0].id: stmt.value.func.id
for stmt in tree.body
if isinstance(stmt, ast.Assign)
and len(stmt.targets) == 1
and isinstance(stmt.targets[0], ast.Name)
and isinstance(stmt.value, ast.Call)
and isinstance(stmt.value.func, ast.Name)
and stmt.value.func.id in bool_classes
}

def _param_names(node: ast.FunctionDef | ast.AsyncFunctionDef) -> set[str]:
params = {arg.arg for arg in node.args.args}
params.update(arg.arg for arg in node.args.posonlyargs)
params.update(arg.arg for arg in node.args.kwonlyargs)
return params

def _instance_attr(expr: ast.AST | None) -> tuple[str, str] | None:
if isinstance(expr, ast.Subscript):
return _instance_attr(expr.value)
if not (
isinstance(expr, ast.Attribute)
and isinstance(expr.value, ast.Name)
and expr.value.id in instances
):
return None
return expr.value.id, expr.attr

for node in ast.walk(tree):
if not isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
continue
if not is_entrypoint_name(node.name):
continue

params = _param_names(node)
mutated = {
key
for expr in ast.walk(node)
if isinstance(expr, ast.Call)
and isinstance(expr.func, ast.Attribute)
and expr.func.attr in {"append", "extend", "insert", "update", "setdefault"}
and any(bool(_expr_names(arg) & params) for arg in expr.args)
for key in [_instance_attr(expr.func.value)]
if key is not None
}
if not mutated:
continue

for child in ast.walk(node):
if not isinstance(child, ast.If):
continue
if _body_has_calls(child.body):
continue
if _expr_names(child.test) & params:
continue
tested_instances = {
expr.id
for expr in ast.walk(child.test)
if isinstance(expr, ast.Name) and expr.id in instances
}
returned = {
key
for stmt in child.body
if isinstance(stmt, ast.Return)
for key in [_instance_attr(stmt.value)]
if key is not None
}
if any(root == instance for root, _attr in returned for instance in tested_instances):
if returned & mutated:
return [{
"pattern": "BOOL_METHOD_REPLAY",
"severity": "critical",
"evidence": (
f"{entrypoint_name} returns state behind an object "
"__bool__ replay guard"
),
}]

return []


RE_OBJECT_ID_DATA = re.compile(r"\bdata_id\s*=\s*id\s*\(\s*data\s*\)")
RE_RESULT_BANK_SET = re.compile(r"_superbatch_results\s*\[\s*(?:did|data_id)\s*\]\s*=")
RE_RESULT_BANK_RETURN = re.compile(r"return\s+_superbatch_results\s*\[\s*data_id\s*\]")
Expand Down Expand Up @@ -3479,6 +3577,10 @@ class RulePolicy:
"LAST_CALL_REPLAY", "result_reuse", "hard", AUTO_FILTER, (),
AMD_MANUAL_LAST_CALL_REPLAY_FIXTURES, "keep",
),
"BOOL_METHOD_REPLAY": RulePolicy(
"BOOL_METHOD_REPLAY", "result_reuse", "hard", AUTO_FILTER, (),
(), "keep",
),
"SHAPE_OUTPUT_REPLAY": RulePolicy(
"SHAPE_OUTPUT_REPLAY", "result_reuse", "hard", AUTO_FILTER, (),
AMD_PACKAGE_SHAPE_REPLAY_FIXTURES, "keep",
Expand Down Expand Up @@ -3762,6 +3864,7 @@ def support_only_patterns(matched_patterns: list[dict]) -> bool:
detect_decode_mm_ref,
detect_result_caching,
detect_last_call_replay,
detect_bool_method_replay,
detect_shape_output_replay,
detect_timed_input_replay,
detect_cuda_graph_replay,
Expand Down Expand Up @@ -3800,6 +3903,7 @@ def support_only_patterns(matched_patterns: list[dict]) -> bool:
("decode_mm_ref", detect_decode_mm_ref),
("result_caching", detect_result_caching),
("last_call_replay", detect_last_call_replay),
("bool_method_replay", detect_bool_method_replay),
("shape_output_replay", detect_shape_output_replay),
("timed_input_replay", detect_timed_input_replay),
("cuda_graph_replay", detect_cuda_graph_replay),
Expand Down Expand Up @@ -4696,7 +4800,7 @@ def _worker_parquet(args: tuple) -> dict:
"EVALUATOR_EXPLOIT", "HARNESS_RUNTIME_PATCHING", "MODULE_MUTATION", "GLOBALS_MUTATION", "CODE_REPLACEMENT",
"FRAME_WALK_ACCESS", "FRAME_WALK_MUTATION", "SYS_MODULES_ACCESS", "GLOBALS_ACCESS", "CODE_ACCESS",
"TRUSTED_MODULE_IMPORT",
"OUTPUT_REPLAY_CACHE", "LAST_CALL_REPLAY", "SHAPE_OUTPUT_REPLAY", "TIMED_INPUT_REPLAY", "CONFIG_CACHE_EXPLOIT", "POINTER_REPLAY", "RESULT_BANK_REPLAY", "PREPROCESS_CACHE", "WORKSPACE_CACHE",
"OUTPUT_REPLAY_CACHE", "LAST_CALL_REPLAY", "BOOL_METHOD_REPLAY", "SHAPE_OUTPUT_REPLAY", "TIMED_INPUT_REPLAY", "CONFIG_CACHE_EXPLOIT", "POINTER_REPLAY", "RESULT_BANK_REPLAY", "PREPROCESS_CACHE", "WORKSPACE_CACHE",
"RUNNER_PLAN_CACHE", "CUDA_GRAPH_PYTHON", "CUDA_GRAPH_REPLAY",
"TIMER_MONKEYPATCH", "FAKE_BENCHMARK_EMIT", "STDIO_REDIRECT", "UNSYNC_MULTISTREAM", "CUDA_EVENT_DISABLE_TIMING",
"SCALED_MM_REF", "DECODE_MM_REF", "SILENT_FALLBACK", "REFERENCE_PRECOMPUTE_REPLAY", "TORCH_COMPILE_CACHE",
Expand Down