perf(model): one Joern invocation per query kind, not one per region

JVM startup dominated a scan: a call per region per family put a ten-line
file at 275s over three regions, and would have put a thousand regions at
roughly fifty hours. The queries themselves are milliseconds once the CPG
is loaded, so the cost was almost entirely process starts.

scan_repository() is now collect -> batch -> arbitrate. The three .sc
scripts accept a `requests` JSON map and answer all of them in one run,
keeping the single-request form so the committed measurements stay
reproducible byte-for-byte. Arbiters are untouched: each is handed a
CpgResult whose `run` returns its own prefetched rows.

The batcher builds parameters by calling request_params() extracted from
taint.py, dominance.py and config_value.py rather than reconstructing
them. A second copy that drifts from the arbiter's is the exact shape of
the five family-assumption bugs the predecessor spec spent a session
finding; there is now one definition per family and the batcher borrows
it.

Regions are also deduplicated by (path, function), collapsing the
nameless entry-point rows that were producing `model:injection:?:10`.

Measured on the same ten-line file: 275s -> 106s, three duplicate
findings -> one `model:injection:ping:10`, rung unchanged at
model_entailed. Gates byte-identical.

Server mode is recorded as task 2.3, deliberately sequenced after the
repository measurement: whether the remaining ~100s floor is worth a
process model, a weakened subprocess seam and a Scala-evaluating HTTP
endpoint depends on a build-time-to-query-time ratio only 2.2 produces.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
This commit is contained in:
Marius Ciepluch
2026-09-09 07:57:35 +02:00
co-authored by Claude Opus 5
parent e67f3ee2f0
commit c35426e186
13 changed files with 412 additions and 76 deletions
+7 -2
View File
@@ -19,9 +19,14 @@ from .ladder import Rung, Verdict
from .specs import ConfigSpec
def request_params(spec: ConfigSpec, *, function: str = "") -> dict[str, object]:
"""The query parameters this arbiter sends. Shared with the batcher; see the note in `taint.request_params`."""
return {"settings": spec.settings, "function": function}
def verdict(cpg: CpgResult, spec: ConfigSpec, *, function: str = "") -> Verdict | None:
"""The verdict for a security setting in ``function``, or ``None`` when nothing is established."""
rows = cpg.run("config", {"settings": spec.settings, "function": function})
rows = cpg.run("config", request_params(spec, function=function))
settings = _settings(rows, spec, function=function)
if not settings:
return None
@@ -79,4 +84,4 @@ def _settings(rows: object, spec: ConfigSpec, *, function: str) -> list[dict[str
return sorted(kept, key=lambda row: (str(row["method"]), str(row["line"]), str(row["setting"])))
__all__ = ["verdict"]
__all__ = ["request_params", "verdict"]
+7 -5
View File
@@ -26,12 +26,14 @@ from .ladder import Rung, Verdict
from .specs import DominanceSpec
def request_params(spec: DominanceSpec, *, function: str = "") -> dict[str, object]:
"""The query parameters this arbiter sends. Shared with the batcher; see the note in `taint.request_params`."""
return {"operations": spec.operations, "dischargers": spec.dischargers, "function": function}
def verdict(cpg: CpgResult, spec: DominanceSpec, *, function: str = "") -> Verdict | None:
"""The verdict for the obligated operation in ``function``, or ``None`` when there is nothing to say."""
rows = cpg.run(
"dominance",
{"operations": spec.operations, "dischargers": spec.dischargers, "function": function},
)
rows = cpg.run("dominance", request_params(spec, function=function))
operations = _operations(rows)
if not operations:
return None
@@ -85,4 +87,4 @@ def _operations(rows: object) -> list[dict[str, object]]:
return kept
__all__ = ["verdict"]
__all__ = ["request_params", "verdict"]
+17 -13
View File
@@ -64,8 +64,11 @@ def regions_for(entries: Sequence[object], targets: Sequence[object]) -> tuple[S
if language:
by_path[str(getattr(target, "path", ""))] = language
regions: list[ScanRegion] = []
covered: set[str] = set()
# One region per (path, function). The mapper can emit several entry points for a single file -- on a
# ten-line Flask file it produced three, one named and two nameless -- and turning each into a region
# scanned the same code repeatedly, multiplying Joern invocations for no new coverage. Where several
# entries agree on a region, the highest access rank wins, because that is the one worth looking at first.
best: dict[tuple[str, str | None], ScanRegion] = {}
for entry in entries:
path = str(getattr(entry, "path", ""))
language = by_path.get(path)
@@ -74,17 +77,18 @@ def regions_for(entries: Sequence[object], targets: Sequence[object]) -> tuple[S
families = _families(language, has_handler=True)
if not families:
continue
covered.add(path)
regions.append(
ScanRegion(
path=path,
function=(getattr(entry, "function_name", None) or None),
language=language,
families=families,
rank=_ACCESS_RANK.get(str(getattr(entry, "access_level", "")), 0.5),
source="entry_point",
)
)
function = getattr(entry, "function_name", None) or None
rank = _ACCESS_RANK.get(str(getattr(entry, "access_level", "")), 0.5)
key = (path, function)
current = best.get(key)
if current is None or rank > current.rank:
best[key] = ScanRegion(path=path, function=function, language=language, families=families, rank=rank, source="entry_point")
# A nameless entry point IS the file. Where a named region already covers that file it adds nothing but
# a second full-file pass, so it is dropped -- unless the file has no named region at all.
named_paths = {path for path, function in best if function is not None}
regions = [region for (path, function), region in best.items() if function is not None or path not in named_paths]
covered = {region.path for region in regions}
for path, language in by_path.items():
if path in covered:
+88 -27
View File
@@ -24,13 +24,21 @@ from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
from ..cpg.backend import CpgResult
from .candidates import enumerate_candidates
from .config_value import request_params as config_params
from .dominance import request_params as dominance_params
from .ladder import Rung
from .pipeline import ModelFinding, scan_region
from .regions import ScanRegion
from .specs import ConfigSpec, DominanceSpec, TaintSpec, config_specs, dominance_specs, taint_specs
from .taint import request_params as taint_params
from .taxonomy import load_families
# The three arbiters a region can be routed to. Naming the union keeps the batcher honest: `object`
# would let a fourth spec kind reach `_grouped` and silently fall through to the taint branch.
ArbiterSpec = TaintSpec | DominanceSpec | ConfigSpec
logger = logging.getLogger(__name__)
_RUNG_ORDER = {Rung.ENTAILED: 0, Rung.CORROBORATED: 1, Rung.SUSPICION: 2, Rung.EXECUTION_CONFIRMED: -1}
@@ -90,36 +98,60 @@ def scan_repository(
# spent in belongs to whoever holds the budget.
ordered_regions = sorted(regions, key=lambda r: (-r.rank, r.path, r.function or ""))
for region in ordered_regions:
if scanned >= limits.max_regions or (counted is not None and counted.calls >= limits.max_model_calls):
degradations.append({"stage": "model", "reason": "budget_exhausted", "regions_unjudged": len(regions) - scanned})
break
# Phase 1: collect the whole scan's questions, for at most `max_regions` regions. Nothing is asked yet.
work: list[tuple[str, ScanRegion, ArbiterSpec]] = []
for region in ordered_regions[: limits.max_regions]:
for family in region.families:
spec = _spec_for(family, region.language)
if spec is None:
continue
try:
# Enumerate the region's candidate sites so the judge has something to answer about where the
# model resolves nothing. Without this a repository scan reports only what taint, dominance
# and constant abstraction establish unaided -- and the suspicion band, which supplied 15 of
# 26 findings in the pair measurement, would never be populated at all.
enumerated = enumerate_candidates(root, region, family, taxonomy=taxonomy)
candidates = [{"id": c.id, "text": c.text, "line": c.line} for c in enumerated.candidates]
found = scan_region(
cpg,
spec,
function=region.function or "",
client=counted,
model=model,
candidates=candidates,
parameter_sources=False, # a repository's parameters are not all attacker input
)
except Exception as exc: # noqa: BLE001 -- one bad region must not end the scan
logger.warning("model scan failed for %s: %s", region.path, exc)
degradations.append({"stage": "model", "reason": "region_failed", "path": region.path})
continue
collected.extend((finding, region.rank) for finding in found)
scanned += 1
work.append((f"{len(work)}", region, spec))
# Phase 2: ONE invocation per query kind. JVM startup dominates a repository scan -- a call per region
# per family put a ten-line file at four minutes and a thousand regions at roughly fifty hours -- while
# the queries themselves are milliseconds once the CPG is loaded.
rows_by_id: dict[str, list[object]] = {}
for kind, requests in _grouped(work).items():
batch = getattr(cpg, "run_batch", None)
if callable(batch):
rows_by_id.update(batch(kind, requests) or {})
else: # a backend without batching still works, one call at a time
for rid, params in requests.items():
answered = cpg.run(kind, params)
rows_by_id[rid] = list(answered) if isinstance(answered, list) else []
# Phase 3: arbitrate from the rows already in hand. The arbiters are unchanged: each is handed a
# CpgResult that simply returns its own prefetched rows.
#
# `judged` counts regions actually ARBITRATED, not regions collected: a region the budget stopped before
# is unjudged, and reporting it as scanned is the silent truncation this exists to prevent.
judged: set[tuple[str, str | None]] = set()
for rid, region, spec in work:
if counted is not None and counted.calls >= limits.max_model_calls:
degradations.append({"stage": "model", "reason": "budget_exhausted", "regions_unjudged": max(len(regions) - len(judged), 0)})
break
family = getattr(spec, "family", "")
prefetched = CpgResult(cpg_path=cpg.cpg_path, run=_prefetched(rows_by_id.get(rid, [])))
try:
enumerated = enumerate_candidates(root, region, family, taxonomy=taxonomy)
candidates = [{"id": c.id, "text": c.text, "line": c.line} for c in enumerated.candidates]
found = scan_region(
prefetched,
spec,
function=region.function or "",
client=counted,
model=model,
candidates=candidates,
parameter_sources=False, # a repository's parameters are not all attacker input
)
except Exception as exc: # noqa: BLE001 -- one bad region must not end the scan
logger.warning("model scan failed for %s: %s", region.path, exc)
degradations.append({"stage": "model", "reason": "region_failed", "path": region.path})
continue
judged.add((region.path, region.function))
collected.extend((finding, region.rank) for finding in found)
scanned = len(judged)
findings = _ordered(collected)
return ModelScanResult(
@@ -134,7 +166,36 @@ def scan_repository(
)
def _spec_for(family: str, language: str) -> TaintSpec | DominanceSpec | ConfigSpec | None:
def _prefetched(rows: list[object]): # type: ignore[no-untyped-def]
"""A `run` that ignores the question and returns rows already fetched in the batch."""
def run(query: str, params: Mapping[str, object]) -> object:
del query, params
return rows
return run
def _grouped(work: Sequence[tuple[str, ScanRegion, ArbiterSpec]]) -> dict[str, dict[str, Mapping[str, object]]]:
"""The work, keyed by query kind, with each request built by the arbiter's OWN parameter function.
Building the parameters here instead would be a second copy that drifts from the arbiter's -- the exact
shape of the five bugs the predecessor spent a session finding.
"""
grouped: dict[str, dict[str, Mapping[str, object]]] = {}
for rid, region, spec in work:
function = region.function or ""
if isinstance(spec, DominanceSpec):
kind, params = "dominance", dominance_params(spec, function=function)
elif isinstance(spec, ConfigSpec):
kind, params = "config", config_params(spec, function=function)
else:
kind, params = "taint", taint_params(spec, function=function, parameter_sources=False)
grouped.setdefault(kind, {})[rid] = params
return grouped
def _spec_for(family: str, language: str) -> ArbiterSpec | None:
"""The spec whose arbiter can decide this family. Routing stays a lookup; dispatch stays in `_arbitrate`."""
if family == "access_control":
return dominance_specs(language=language).get(family)
+17 -11
View File
@@ -19,6 +19,21 @@ from .ladder import Rung, Verdict
from .specs import TaintSpec
def request_params(spec: TaintSpec, *, function: str = "", parameter_sources: bool = False) -> dict[str, object]:
"""The query parameters this arbiter sends. Shared with the batcher so there is one definition, not two.
Two copies of a parameter dict is precisely the duplication that produced five bugs of one shape in the
predecessor: a change made in one place and not its sibling.
"""
return {
"sources": spec.sources,
"sinks": spec.sinks,
"sanitizers": spec.sanitizers,
"function": function,
"parameterSources": "true" if parameter_sources else "false",
}
def verdict(cpg: CpgResult, spec: TaintSpec, *, function: str = "", parameter_sources: bool = False) -> Verdict | None:
"""The strongest verdict the taint query supports for ``spec`` in ``function``, or ``None`` to stay at suspicion.
@@ -26,16 +41,7 @@ def verdict(cpg: CpgResult, spec: TaintSpec, *, function: str = "", parameter_so
for a function-level pair, where the function boundary *is* the trust boundary, and wrong for a whole
repository, where most parameters carry internal values — so it is off by default and the caller opts in.
"""
rows = cpg.run(
"taint",
{
"sources": spec.sources,
"sinks": spec.sinks,
"sanitizers": spec.sanitizers,
"function": function,
"parameterSources": "true" if parameter_sources else "false",
},
)
rows = cpg.run("taint", request_params(spec, function=function, parameter_sources=parameter_sources))
flows = _flows(rows, function=function)
# A sink whose *shape* is safe is the fix, not the bug. `execute(sql, params)` binds rather than
# interpolates and `printf("literal", x)` has a constant format string, so the flow that reaches them is
@@ -146,4 +152,4 @@ def _witness(flow: Mapping[str, object]) -> str:
return f"{flow['source']} -> {flow['sink']} (line {line}, {flow['length']} steps)"
__all__ = ["verdict"]
__all__ = ["request_params", "verdict"]