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Open_Ultra_SAST/src/openultrasast/model/specs.py
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Marius CiepluchandClaude Opus 5 f59e0f5b5a fix(model-grounded-detection): two modelling bugs the first live Joern run exposed
Both were found by running the real engine, and neither was visible offline.

1. A sink was its own sanitizer. The shipped facts mark some sanitizers with a
   *shape* qualifier -- parameterized ("execute(sql, params) binds rather than
   interpolates") and literal_format_arg ("printf with a constant format string
   is safe"). These describe a safe FORM OF THE SINK CALL, not a call that
   cleans a value on the path. Flattening them into the sanitizer list made
   `execute` both the injection sink and its own sanitizer, so every SQL flow
   would have reported as already-clean and nothing could ever be entailed.
   Fixed as a class, not an instance: any fact carrying a shape qualifier is
   excluded from `sanitizers` and kept in `safe_shape_sinks` for the shape test
   task 4.2 will model properly. Fixing only the Python `parameterized` case
   would have left C's entire printf family -- which the generalised test then
   caught immediately.

2. labeled_family lost its deterministic derivation in group 1. The deleted
   classifier resolved a pair's family by declared label, else obligation, else
   mechanism, else CWE, and only asked an LLM when every link failed -- which
   for a labeled corpus was never. Group 1 reduced this to the declared label
   alone, which silently emptied every family whose pairs are labeled by CWE:
   the injection slice went to zero pairs. The chain is restored, still with no
   model call, and the family census again matches the committed entailment
   ceiling exactly (injection 50, memory 176, access_control 8, ...).

Also: the Joern seam now runs in the CPG's own scratch directory, because
`joern --script` writes a `workspace/` beside the working directory and would
otherwise leave one inside the repository being analysed.

The taint query itself was corrected against the live engine: the sink is the
call's ARGUMENTS (data flows into arguments, not into the call node) and
reachableByFlows is called on the sink with the source. With that, the
three-hop chain our flat IR could not resolve is found:
  request.args["cmd"] -> cmd -> "echo " + cmd -> full -> os.system(full)

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
2026-09-08 12:45:42 +02:00

184 lines
7.9 KiB
Python

"""The security vocabularies the model layer arbitrates with (model-grounded-detection, Req 7.2-7.4).
Two kinds of knowledge live here, and they are held differently on purpose.
The **guard vocabulary** is ported verbatim from ``semantic/variants.py``, whose optimisation loop this
feature deleted. Nothing else holds it: it is the closed set of ways a fix discharges a flow, and it tells
the model what a *fixed* twin looks like. Order matters — first match wins.
The **taint and dominance specs** are *derived* from data that survives: the source/sink/sanitizer facts in
``ruleset/semantic`` and the obligated operations and dischargers in ``ruleset/obligations``. Copying them
here would create a second place to update, so this module reads them through the retained loaders and
groups them by family via the taxonomy's CWE map.
Read-only by construction (Req 7.4, the verifier boundary): this module exposes no writer, opens no file for
writing, and holds no mutable module state. An LLM or a future optimiser has nothing here to rewrite.
"""
from __future__ import annotations
import re
from collections.abc import Mapping
from dataclasses import dataclass
from ..semantic.facts import SemanticFacts, load_facts
from ..semantic.obligations.facts import ObligationFacts, load_obligation_facts
from .taxonomy import FamilyTaxonomy, load_families
# --- The guard vocabulary (ported verbatim; nothing else holds it) ----------------------------------------
GUARD_KINDS = ("null_test", "bounds_test", "allowlist_test", "auth_check", "parameterized_call", "type_change", "none")
# Closed guard classification over the statements a fix added inside the labeled function.
# Order matters: the first matching kind wins. These classify the *fix*, they never detect.
GUARD_PATTERNS: tuple[tuple[str, re.Pattern[str]], ...] = (
("parameterized_call", re.compile(r"execute\w*\([^,]+,\s*[\(\[]|prepareStatement\(|\?\s*['\"]?\s*[,)]|\$\d\b|%s['\"]\s*,\s*[\(\[]")),
(
"auth_check",
re.compile(
r"\b(request\.user|req\.user|current_user|request\.state|session\[|is_authenticated|authoriz|require_auth"
r"|login_required|verify_token|check_permission|owner_id\s*[!=]=)"
),
),
(
"allowlist_test",
re.compile(
r"\bnot in\b|\bin\s*[\(\{\[]|\.includes\(|\.has\(|\bstartswith\(|\bstartsWith\(|\bendswith\(|\bendsWith\("
r"|re\.(?:match|fullmatch)\(|\.test\(|allow_?list|whitelist|\bALLOWED\b|\bsafe_join\(|secure_filename\("
r"|\brealpath\(|\bnormpath\(|\bresolve\("
),
),
("bounds_test", re.compile(r"\blen\(|\.length\b|\bsizeof\(|\bstrn?len\(|\bsnprintf\(|\bstrlcpy\(|\bmin\(|\bmax\(|\s(?:<|>|<=|>=)\s")),
(
"null_test",
re.compile(
r"\bis None\b|\bis not None\b|[!=]= *NULL\b|[!=]==? *null\b|\bnullptr\b|\bif\s*\(\s*!\s*\w|\bif not \w+\s*:"
r"|\bif\s+\w+\s+is\s+None|\?\?|\?\."
),
),
(
"type_change",
re.compile(r"\bint\(|\bparseInt\(|\bNumber\(|\(int\)|\(size_t\)|\(unsigned\b|\bstr\(|\.toString\(|\bstatic_cast<|\bBigInt\("),
),
)
def classify_guard_text(text: str) -> str:
"""The guard kind the given statements express, or ``none`` when no known guard is recognised."""
for kind, pattern in GUARD_PATTERNS:
if pattern.search(text):
return kind
return "none"
# --- The specs the CPG queries are parameterised by ------------------------------------------------------
@dataclass(frozen=True)
class TaintSpec:
"""What a flow family's source-to-sink-minus-sanitizer query matches on, for one language.
``sanitizers`` holds only *cleansing calls* -- a node on the flow path that makes the value safe, such as
``ast.literal_eval``. It deliberately excludes every fact that carries a **shape qualifier**, because
those describe a safe *form of the sink call*, not a call that cleans a value:
parameterized ``execute(sql, params)`` binds rather than interpolates
literal_format_arg ``printf("literal", x)`` has a constant format string
Flattening either kind into the sanitizer list is actively wrong: the sink becomes its own sanitizer, so
every flow through it reports as already-clean and nothing is ever entailed. Both were present in the
shipped facts (`execute` for Python, the whole printf family for C) and both surfaced on the first live
Joern run. The names are kept in ``safe_shape_sinks`` so the shape test can be modelled properly in task
4.2 rather than silently mis-modelled here.
"""
family: str
language: str
sources: tuple[str, ...]
sinks: tuple[str, ...]
sanitizers: tuple[str, ...]
safe_shape_sinks: tuple[str, ...] = ()
@dataclass(frozen=True)
class DominanceSpec:
"""What an absence family's guard-dominates-operation query matches on, for one language.
``dischargers`` are the guards that discharge an obligation; the query asks whether one of them dominates
the operation on every path, which is the arbiter for the classes that never crash.
"""
family: str
language: str
operations: tuple[str, ...]
dischargers: tuple[str, ...]
def taint_specs(
*,
language: str,
facts: SemanticFacts | None = None,
taxonomy: FamilyTaxonomy | None = None,
) -> Mapping[str, TaintSpec]:
"""One ``TaintSpec`` per flow family that has a sink in this language, grouped through the taxonomy's CWE map.
Sources and sanitizers are language-wide: a family does not get its own notion of what untrusted input is,
and a sanitizer that breaks one flow breaks it whatever the sink's family.
"""
scoped = (facts if facts is not None else load_facts()).for_language(language)
families = taxonomy if taxonomy is not None else load_families()
sources = tuple(sorted({pattern for fact in scoped.sources for pattern in fact.patterns}))
# A shape qualifier means "this sink is safe in this form", never "this call cleans the value".
def _is_shape(fact: object) -> bool:
return bool(getattr(fact, "parameterized", False)) or getattr(fact, "literal_format_arg", None) is not None
sanitizers = tuple(sorted({call for fact in scoped.sanitizers if not _is_shape(fact) for call in fact.calls}))
safe_shapes = tuple(sorted({call for fact in scoped.sanitizers if _is_shape(fact) for call in fact.calls}))
by_family: dict[str, set[str]] = {}
for sink in scoped.sinks:
family = families.family_of_cwe(sink.cwe)
if family is None:
continue
by_family.setdefault(family.id, set()).update(sink.calls)
return {
family_id: TaintSpec(
family=family_id,
language=language,
sources=sources,
sinks=tuple(sorted(calls)),
sanitizers=sanitizers,
safe_shape_sinks=safe_shapes,
)
for family_id, calls in sorted(by_family.items())
}
def dominance_specs(*, language: str, facts: ObligationFacts | None = None) -> Mapping[str, DominanceSpec]:
"""One ``DominanceSpec`` per absence family for this language.
The obligation facts are authored for authorization, so every obligated operation routes to
``access_control``; the shape generalises when a second absence family is added to the taxonomy.
"""
scoped = (facts if facts is not None else load_obligation_facts()).for_language(language)
if not scoped.operations:
return {}
operations = tuple(sorted({call for fact in scoped.operations for call in fact.calls}))
dischargers = tuple(
sorted(
{call for fact in scoped.dischargers for call in fact.calls}
| {decorator for fact in scoped.dischargers for decorator in fact.decorators}
)
)
return {"access_control": DominanceSpec(family="access_control", language=language, operations=operations, dischargers=dischargers)}
__all__ = [
"GUARD_KINDS",
"GUARD_PATTERNS",
"DominanceSpec",
"TaintSpec",
"classify_guard_text",
"dominance_specs",
"taint_specs",
]