[BUG] - Native Code Execution via CWD-poisoned SQLite cache in CUTLASS `cutlass_cppgen`

Which component has the problem?

CUTLASS C++

Bug Report

1. Summary (TL;DR)

cutlass_cppgen.ArtifactManager persists compiled device (cubin) and host (hostbin) artifacts in a SQLite database whose path is the bare, CWD-relative filename compiled_cache.db (cutlass_cppgen/__init__.py:84). The manager is a module-level singleton instantiated at import (backend/__init__.py:48: compiler = ArtifactManager()), and its constructor does sqlite3.connect("compiled_cache.db") (compiler.py:141) — which auto-creates the file in the process's current working directory.

On the default compile path (bypass_cache=False, compiler.py:358), a cache miss calls load_operation(key, …) (compiler.py:387), which runs SELECT * FROM compiled_operations WHERE op_key = ? (compiler.py:189-190) and — for any matching row — takes the attacker-controlled hostbin BLOB and passes it to CDLLBin(host_binary) (compiler.py:205). CDLLBin writes the blob to a temp .so and calls ctypes.CDLL(...) on it (compiler.py:126-132), so the blob's ELF constructors/init code runs inside the victim's Python process.

An attacker who can plant a compiled_cache.db in the victim's CWD (shared filesystem, extracted archive, cloned/checked-out project, world-writable dir) with a row whose op_key matches an operation the victim will compile achieves native RCE the moment the victim compiles that op.

This is the standard "untrusted-search-path / cache-poisoning → native library load" class. It is rated Medium (not High) because exploitation requires (a) CWD-plant capability and (b) a matching op_key — both stronger preconditions than the sibling pickle.loads advisory, which needs no key match.

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2. Affected component

• Repository: github.com/NVIDIA/cutlass
• Sub-tree: python/cutlass_cppgen/
• Files involved:
  • python/cutlass_cppgen/__init__.py — CACHE_FILE = "compiled_cache.db" (line 84) — bare, CWD-relative
  • python/cutlass_cppgen/backend/__init__.py — compiler = ArtifactManager() (line 48) — singleton instantiated at import
  • python/cutlass_cppgen/backend/compiler.py:
    • ArtifactManager.__init__ (line 135) → sqlite3.connect(CACHE_FILE) (line 141)
    • CDLLBin(host_binary) (lines 126-132) — writes blob to temp .so, ctypes.CDLL-loads it
    • load_operation(op_key, extra_funcs) (lines 186-228) — SELECT ... WHERE op_key = ? (189-190) → CDLLBin(host_binary) (205)
    • add_module(operations, compile_options=None, bypass_cache=False) (line 358) — cache used by default; cache miss → load_operation(key, …) (387)
    • op_key = operation.rt_module.emit() + operation.procedural_name() + self.backend (line 382)
  • Public entry: Gemm.compile() (python/cutlass_cppgen/op/gemm.py:478) → compiler.add_module([self.operation]) (gemm.py:506); Conv.compile() (op/conv.py:637) → compiler.add_module([self.operation]) (conv.py:675). Neither passes bypass_cache=True, so the cache path is the default.
• Distribution: cutlass_cppgen ships in the nvidia-cutlass PyPI wheel and is imported by the public CUTLASS Python API.

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3. Vulnerable code (exact, from HEAD 2802e22)

3.1 The CWD-relative cache path — cutlass_cppgen/__init__.py

CACHE_FILE = "compiled_cache.db"   # line 84 — bare filename; resolved relative to process CWD

3.2 Singleton at import + auto-create in CWD — backend/__init__.py / compiler.py

# backend/__init__.py
compiler = ArtifactManager()        # line 48 — runs at import of cutlass_cppgen.backend

# compiler.py
class ArtifactManager:              # line 135
    def __init__(self) -> None:     # line 140
        connection = sqlite3.connect(CACHE_FILE)          # line 141 — opens/CREATES compiled_cache.db IN CWD
        cursor = connection.cursor()
        sqlite_create_table_query = """                   # line 144
        CREATE TABLE IF NOT EXISTS compiled_operations(op_key TEXT NOT NULL UNIQUE,
                                                        cubin BLOB NOT NULL,
                                                        hostbin BLOB NOT NULL,   # <-- attacker native blob
                                                        op_name TEXT NOT NULL,
                                                        op_attrs TEXT NOT NULL)
        """
        cursor.execute(sqlite_create_table_query)         # line 151
        ...
        self.nvcc()                                       # line 161 — backend defaults to "nvcc"

3.3 The sink — CDLLBin() (compiler.py:126-132)

def CDLLBin(host_binary):
    tempfile.tempdir = "./"                                  # line 127 — temp .so also lands in CWD
    temp_so = tempfile.NamedTemporaryFile(prefix="host_func", suffix=".so", delete=True)  # 128
    with open(temp_so.name, "wb") as file:
        file.write(host_binary)                             # 129-130 — write attacker blob
    host_lib = ctypes.CDLL(temp_so.name)                    # line 131 — *** load + run constructors ***
    return host_lib

3.4 The poisoned-row trigger — load_operation() (compiler.py:186-205)

def load_operation(self, op_key, extra_funcs):
    connection = sqlite3.connect(CACHE_FILE)                # line 187
    cursor = connection.cursor()
    sqlite_fetch_blob_query = """SELECT * from compiled_operations where op_key = ?"""   # line 189
    cursor.execute(sqlite_fetch_blob_query, (op_key,))      # line 190 — exact-key match
    record = cursor.fetchall()                              # line 191
    if len(record) == 0:
        return False                                        # line 193
    for row in record:
        key, cubin_image, host_binary, operation_name, op_attr = row   # line 195 — host_binary = attacker blob
        op_attr = json.loads(op_attr)                       # line 196
        err, module = cuda.cuModuleLoadData(cubin_image)    # line 197 — (attacker supplies a valid cubin so this succeeds on a GPU host)
        if err != cuda.CUresult.CUDA_SUCCESS:
            raise RuntimeError("Cuda Error: {}".format(err))
        err, kernel = cuda.cuModuleGetFunction(module, bytes(str.encode(operation_name)))  # line 201
        self.compiled_cache_device[key] = kernel
        compiled_host_fns = {}
        host_lib = CDLLBin(host_binary)                     # line 205 — *** native RCE ***

3.5 Default cache use on the public path — add_module() (compiler.py:358-400)

def add_module(self, operations, compile_options=None, bypass_cache=False):   # line 358 — default uses cache
    ...
    for operation in operations:
        key = operation.rt_module.emit() + operation.procedural_name() + self.backend   # line 382 — op_key
        compiled_kernel = self.compiled_cache_device.get(key)               # line 384 — in-memory first
        if compiled_kernel is None and not bypass_cache:                    # line 386
            hit = self.load_operation(key, getattr(operation.rt_module, "extra_funcs", {}))  # line 387 — DB query
            if hit:
                ...                                                          # line 388-390

Gemm.compile() (gemm.py:506) and Conv.compile() (conv.py:675) call compiler.add_module([self.operation]) without bypass_cache=True, so a poisoned row is consulted by default.

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4. Root cause

1. CWD-relative cache path. CACHE_FILE = "compiled_cache.db" is a bare filename; SQLite auto-creates/opens it wherever the process's CWD points. There is no per-user, non-CWD resolution (~/.cache/…, XDG_CACHE_HOME) and no integrity binding.
2. ctypes.CDLL on cached blobs with no verification. CDLLBin writes the stored hostbin BLOB to a temp .so and CDLL-loads it. The BLOB is treated as trusted by virtue of being in the cache, but the cache itself is an untrusted CWD file.
3. Singleton-at-import amplifies exposure. Merely importing the backend (e.g. from cutlass_cppgen.backend import compiler) creates/opens the CWD DB, so any directory the victim cds into and runs from becomes the cache location.
4. Default cache use. The cache is consulted on the default (bypass_cache=False) public compile path, so victims get no opt-out signal that loading may execute native code.

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5. Attack chain (end to end)

attacker:
  1. compile a malicious shared object  evil.so  with a constructor/init that does anything the victim can
  2. build  compiled_cache.db  with a row:
       op_key  = rt_module.emit() + procedural_name() + backend   # pre-computable by compiling the SAME op once
       cubin   = <a VALID cubin for any kernel>                    # so cuModuleLoadData succeeds on the GPU host
       hostbin = <bytes of evil.so>                                # <-- native payload
       op_name = <any>, op_attrs = json([1])
  3. place  compiled_cache.db  in a directory the victim will `cd` into and run from
     (shared FS, extracted archive/attachment, cloned/checked-out project, world-writable /tmp)

victim:
  cd <that directory>
  python -c "
    import cutlass
    plan = cutlass.Gemm(...)        # imports cutlass_cppgen.backend -> ArtifactManager() -> opens/creates compiled_cache.db IN CWD
    plan.compile()                  # gemm.py:478 -> compiler.add_module([op]) (gemm.py:506), bypass_cache=False default
      -> key = op.rt_module.emit() + op.procedural_name() + backend          # compiler.py:382
      -> compiled_cache_device.get(key) is None                              # :384
      -> load_operation(key, ...)                                            # :387
           -> SELECT * WHERE op_key = key  -> matches attacker row           # :189-190
           -> cuModuleLoadData(attacker_cubin) succeeds (valid cubin, GPU)    # :197
           -> CDLLBin(host_binary = bytes of evil.so)                        # :205
                -> ctypes.CDLL(temp.so)                                      # :131
                     -> *** constructor executes -> native RCE in victim process ***

No GPU is needed for the native primitive itself — ctypes.CDLL runs the constructor on the host CPU. End-to-end against the real load_operation does require a GPU for the cuModuleLoadData(cubin) line (:197) that precedes CDLLBin; the attacker satisfies it by storing a valid cubin in the poisoned row (the cubin's correctness is irrelevant to the RCE — it only needs to load). The PoC (§7) stubs that GPU line and exercises CDLLBin verbatim on attacker bytes.

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6. Realistic exploitation scenario

• A developer/researcher cds into an attacker-influenced directory and runs any CUTLASS Python compile:
  • a cloned repo / checked-out branch that commits a compiled_cache.db (e.g. a malicious PR, a typo-squatted example repo, an "example kernels" repo),
  • an extracted archive/attachment (a "precompiled kernels bundle" zip/tar that drops the DB),
  • a shared filesystem / NFS / world-writable /tmp where a prior user (or a different compromise) planted the DB,
  • a poisoned CI/devcontainer working dir.
• The victim runs import cutlass; plan = cutlass.Gemm(...).compile(). The singleton ArtifactManager() opens compiled_cache.db in CWD; compile() → add_module → load_operation(key) matches the attacker row → CDLLBin loads the attacker .so → native code runs as the victim.
• The op_key (rt_module.emit() + procedural_name() + backend) is fully deterministic for a given operation configuration. The attacker pre-computes it by compiling the same op once (on any machine with CUTLASS) and reading the key — or by targeting a common, documented example kernel. The default backend is nvcc (__init__ → self.nvcc(), compiler.py:161).

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7. Proof of Concept

A tested, self-contained PoC is at
audit-campaign/.nvidia-audit/poc/cache426/cache426_poc.py (with evil.c → evil.so).

7.1 What it demonstrates

The full load_operation path calls cuda.cuModuleLoadData(cubin) (compiler.py:197) before CDLLBin (:205), which needs a real GPU. The security-relevant sink — CDLLBin(host_binary) → ctypes.CDLL on the attacker BLOB read from the poisoned DB — is pure Python + ctypes + sqlite3. The PoC faithfully reproduces CDLLBin (compiler.py:126-132) and the SELECT→row→CDLLBin slice of load_operation (compiler.py:186-205) with the cubin/GPU lines stubbed (they are a precondition satisfied by a valid cubin on a GPU host, not the vulnerability). It builds a real malicious .so (a gcc -shared -fPIC constructor blob), plants it in a compiled_cache.db, and shows the constructor executes through ctypes.CDLL.

7.2 The malicious library (evil.c)

#include <stdio.h>
#include <unistd.h>
__attribute__((constructor)) static void _on_load(void){
    FILE* f = fopen("/tmp/pwned_by_cache426","w");
    if(f){ fprintf(f, "CACHE426 RCE: uid=%d\n", getuid()); fclose(f); }
}

7.3 Result (run on Python 3.12 + gcc, sandbox, no GPU)

[*] planted compiled_cache.db in CWD with attacker hostbin (15704 bytes) at op_key='VICTIM_GEMM_KEY'
[*] victim compiles an op whose key matches -> load_operation(key) ...
[*] checking for code-execution marker ...
[+] *** NATIVE RCE CONFIRMED *** CDLLBin() ctypes.CDLL'd the attacker blob from poisoned compiled_cache.db. Marker:
    CACHE426 RCE: uid=1003

The constructor ran inside the loader process — proving the attacker hostbin BLOB in the CWD-poisoned cache executes native code via ctypes.CDLL.

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8. Impact

• Confidentiality / Integrity / Availability: High (on trigger). Full native code execution in the victim's Python process — same privilege as the victim (read secrets/keys, exfiltrate data/models, persist, destroy). Native (not Python-interpreter) execution.
• Preconditions (why Medium, not High):
  1. CWD-plant capability — the attacker must place compiled_cache.db in a directory the victim will run from (local/shared-FS write), and
  2. matching op_key — the poisoned row's key must equal the victim's compiled-op key (pre-computable, but requires the attacker to know/target the op).
• Reachability: default public path. Gemm.compile()/Conv.compile() use the cache by default (bypass_cache=False); no opt-in is required.
• Amplifier: the singleton-at-import + tempfile.tempdir = "./" (compiler.py:127) mean the DB and the temp .so both resolve to the victim's CWD, maximizing the chance a planted file is consulted.

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9. Severity (CVSS 3.1)

CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H → 6.7 Medium

• AV:L — local file plant in the victim's CWD.
• AC:H — two specific, partially out-of-attacker-control conditions must hold simultaneously: CWD-plant and op_key match. This non-trivial friction justifies AC over Low.
• PR:L — the attacker needs some local/shared-directory write capability to plant the file (on a fully world-writable/shared dir this approaches PR:N).
• UI:R — the victim must run a compile in the poisoned CWD (the documented workflow).
• C:H/I:H/A:H — full native process compromise.

If the CWD is a fully unauthenticated shared/public location (PR:N), the score rises toward 7.0; if the op_key match is considered low-friction (e.g. a widely-documented example kernel, AC:L), it can reach the 7.8 High of the sibling pickle advisory. The conservative, defensible rating for general deployment is Medium because of the two preconditions; specific deployments (shared CWD + known target op) are effectively High.

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10. Remediation (recommended fix)

10.1 (Primary) Resolve the cache under a per-user, non-CWD location

# cutlass_cppgen/__init__.py
import os, pathlib
def _cache_path() -> str:
    base = os.environ.get("CUTLASS_CPPGEN_CACHE",
                          os.environ.get("XDG_CACHE_HOME",
                                         os.path.join(pathlib.Path.home(), ".cache")))
    d = pathlib.Path(base) / "cutlass_cppgen"
    d.mkdir(parents=True, exist_ok=True)
    return str(d / "compiled_cache.db")
CACHE_FILE = _cache_path()

This removes the CWD-poisoning vector entirely (an attacker can no longer plant the file in an arbitrary working directory).

10.2 (Integrity) Do not CDLL cached blobs without a signature

Compute an HMAC (or NVIDIA signature) over the hostbin/cubin blobs at insert_operation time with a key the consumer trusts, and verify before CDLLBin/cuModuleLoadData. Store the tag in a new column; reject on mismatch.

10.3 (Opt-in / least surprise) Make cache loading explicit

• Require an explicit trust_cache=True (or an env var) before load_operation will CDLL-load blobs, mirroring torch.load(weights_only=…). Default to recompile-from-source (the safe path) when the cache is untrusted.

10.4 (Defense in depth) Sandbox the temp load

CDLLBin currently sets tempfile.tempdir = "./" (writes the temp .so to CWD) — resolve temp files under tempfile.gettempdir() per-user, and avoid mutating the global tempfile.tempdir.

Recommended combination: 10.1 (non-CWD path) closes the reported vector; 10.2 (integrity) defends against any residual untrusted-cache case; 10.3 removes the silent-execute surprise.

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Appendix B — Verified line references (HEAD 2802e22)

Step	File:line	Symbol
CWD-relative cache name	python/cutlass_cppgen/__init__.py:84	CACHE_FILE = "compiled_cache.db"
Singleton at import	python/cutlass_cppgen/backend/__init__.py:48	compiler = ArtifactManager()
Open/create DB in CWD	python/cutlass_cppgen/backend/compiler.py:141	sqlite3.connect(CACHE_FILE)
Cache table (has hostbin BLOB)	python/cutlass_cppgen/backend/compiler.py:144-150	CREATE TABLE … hostbin BLOB …
Default backend = nvcc	python/cutlass_cppgen/backend/compiler.py:161	self.nvcc()
Public compile entry (Gemm)	python/cutlass_cppgen/op/gemm.py:478	Gemm.compile()
→ add_module call	python/cutlass_cppgen/op/gemm.py:506	compiler.add_module([self.operation])
Public compile entry (Conv)	python/cutlass_cppgen/op/conv.py:637 / :675	Conv.compile() → add_module
Default cache use	python/cutlass_cppgen/backend/compiler.py:358	add_module(..., bypass_cache=False)
op_key computation	python/cutlass_cppgen/backend/compiler.py:382	rt_module.emit() + procedural_name() + backend
Cache miss → load_operation	python/cutlass_cppgen/backend/compiler.py:386-387	if … not bypass_cache: load_operation(key,…)
SELECT poisoned row	python/cutlass_cppgen/backend/compiler.py:189-190	SELECT * … WHERE op_key = ?
cubin load (needs GPU)	python/cutlass_cppgen/backend/compiler.py:197	cuda.cuModuleLoadData(cubin_image)
SINK: CDLLBin on host blob	python/cutlass_cppgen/backend/compiler.py:205	host_lib = CDLLBin(host_binary)
ctypes.CDLL (constructors run)	python/cutlass_cppgen/backend/compiler.py:131	host_lib = ctypes.CDLL(temp_so.name)
Temp .so in CWD	python/cutlass_cppgen/backend/compiler.py:127	tempfile.tempdir = "./"

Start by reading python/cutlass_cppgen/init.py, backend/init.py, and backend/compiler.py, following ArtifactManager initialization through add_module(), load_operation(), and CDLLBin(). Reproduce the reported CWD cache and native-library load chain using the referenced entry points, then verify that the completed change prevents untrusted cache data from reaching the load path and includes regression coverage.