security(sampling): reject prompt_logprobs=-1 to prevent OOM DoS

[malaiwah]

Summary

Fixes #264

prompt_logprobs=-1 ("return all vocabulary logprobs for every prompt token") is impractical for any modern vocabulary and causes unbounded memory allocation that kills the engine.

The problem

When prompt_logprobs=-1, num_prompt_logprobs resolves to model_config.get_vocab_size() (154,880 for GLM-5.2). The V1 _get_prompt_logprobs_dict allocates:

logprobs_tensors = LogprobsTensors.empty_cpu(
    num_prompt_tokens - 1, num_prompt_logprobs + 1  # [prompt_len, 154880]
)

For a 100k-token prompt × 154,880 vocab × 8 bytes = ~62 GiB — far exceeding any host's free memory. The engine crashes with torch.OutOfMemoryError / EngineDeadError.

The V2 PromptLogprobsWorker path has the same pattern at prompt_logprob.py:142-143.

Why the existing chunking fix doesn't help

PR #258 (and follow-up cc5a286de) added VLLM_PROMPT_LOGPROBS_CHUNK_SIZE to chunk the GPU compute_logits call. This bounds the GPU logits tensor to [chunk_size, vocab_size]. However, the upfront CPU LogprobsTensors.empty_cpu allocation is unbounded — it allocates the full [num_prompt_tokens, vocab_size] tensor before any chunking happens.

Reproduction

On AIBoss (RTX 5090, r28 image), even prompt_logprobs=1 with a ~3,800-token chunked prompt triggers OOM:

torch.OutOfMemoryError: CUDA out of memory. Tried to allocate ...
  File ".../vllm/v1/sample/sampler.py", line ...
    return logits.log_softmax(dim=-1, dtype=torch.float32)

EngineCore dies. With prompt_logprobs=-1, the allocation is orders of magnitude larger.

The fix

Reject prompt_logprobs=-1 outright in _validate_logprobs (sampling_params.py:807):

if num_prompt_logprobs == -1:
    raise VLLMValidationError(
        "prompt_logprobs=-1 (all logprobs) is not supported because "
        "it can cause unbounded memory allocation. Specify a "
        "concrete value (e.g. prompt_logprobs=20).",
        parameter="prompt_logprobs",
        value=-1,
    )

The existing max_logprobs=20 default already rejects -1 (resolves to vocab_size > 20), but an operator who sets --max-logprobs=-1 bypasses that guard. This fix makes the rejection unconditional.

Files changed

• vllm/sampling_params.py — reject prompt_logprobs=-1 in _validate_logprobs (17 lines added)
• tests/sampling/test_prompt_logprobs_security.py — 5 new tests

Verification

Tested on AIBoss (RTX 5090, r28 image) with the patched file overlaid:

5 passed

• prompt_logprobs=-1 correctly rejected with VLLMValidationError
• prompt_logprobs=20 (positive) still works
• prompt_logprobs=0 (disabled) still works
• prompt_logprobs=None (unset) still works
• prompt_logprobs=100 > max_logprobs=20 still rejected by existing check

Impact

This is a denial-of-service prevention fix. Any API client can send prompt_logprobs=-1 with a large prompt to kill the engine, affecting all other clients. The "all logprobs" feature is never usable without OOM on modern vocabularies — rejecting it outright is the cleanest fix.

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Review details

⚙️ Run configuration

Configuration used: Organization UI

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Run ID: c5d48347-0c44-4e02-ad00-e70525a722a4

📥 Commits

Reviewing files that changed from the base of the PR and between fa033bd and efbc81e.

📒 Files selected for processing (5)

• tests/sampling/test_prompt_logprobs_security.py
• vllm/entrypoints/openai/chat_completion/protocol.py
• vllm/entrypoints/openai/completion/protocol.py
• vllm/envs.py
• vllm/sampling_params.py

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[malaiwah]

Test Results (automated)

Host: macOS M4 Max, CPU-only (no CUDA)
Command: .venv/bin/python -m pytest tests/sampling/test_prompt_logprobs_security.py --noconftest -x -v

Tests require dependencies not available on this host (macOS M4, CPU-only torch, no CUDA). Cannot run.

Error:

ImportError while importing test module tests/sampling/test_prompt_logprobs_security.py.
Traceback:
tests/sampling/test_prompt_logprobs_security.py:9: in <module>
    from vllm.sampling_params import SamplingParams
vllm/sampling_params.py:13: in <module>
    import msgspec
E   ModuleNotFoundError: No module named msgspec

The test imports vllm.sampling_params, which depends on the msgspec package — not installed in this CPU-only venv. The vLLM package was also not found (version could not be inspected).

---

Automated test run by @malaiwah's agent. Results are from a CPU-only environment; GPU-dependent tests may behave differently on CUDA hardware.

[malaiwah]

Test Results (automated — re-run with fixed dependencies)

Host: macOS M4 Max, CPU-only (no CUDA)
Command: .venv/bin/python -m pytest tests/sampling/test_prompt_logprobs_security.py --noconftest -x -v

============================= test session starts ==============================
platform darwin -- Python 3.12.13, pytest-9.1.1, pluggy-1.6.0 -- /Users/mbelleau/Projects/vllm-voipmonitor/.venv/bin/python
cachedir: .pytest_cache
rootdir: /private/tmp/retest-266
configfile: pyproject.toml
plugins: anyio-4.14.2
collecting ... collected 5 items

tests/sampling/test_prompt_logprobs_security.py::test_prompt_logprobs_minus_one_rejected PASSED [ 20%]
tests/sampling/test_prompt_logprobs_security.py::test_prompt_logprobs_positive_still_works PASSED [ 40%]
tests/sampling/test_prompt_logprobs_security.py::test_prompt_logprobs_zero_still_works PASSED [ 60%]
tests/sampling/test_prompt_logprobs_security.py::test_prompt_logprobs_none_still_works PASSED [ 80%]
tests/sampling/test_prompt_logprobs_security.py::test_prompt_logprobs_exceeds_max_still_rejected PASSED [100%]

=============================== warnings summary ===============================
vllm/__init__.py:7
  /private/tmp/retest-266/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash:
    No module named 'vllm._version'
    from .version import __version__, __version_tuple__  # isort:skip

-- Docs: https://docs.pytest.org/en/stable/how-to/rerun-failures.html
======================== 5 passed, 1 warning in 17.60s =========================

✅ All 5 tests passed.

---

Automated test run by @malaiwah's agent. Results are from a CPU-only environment; GPU-dependent tests may behave differently on CUDA hardware.

[malaiwah]

Review Findings Addressed: B9 (BLOCKER), C4, C5, C6

The Bypass (B9)

The original fix rejected only the sentinel spelling prompt_logprobs=-1. When model_config.max_logprobs == -1 (an operator-settable value), the allowed maximum became the vocabulary size, so prompt_logprobs=154880 passed the > check and allocated the identical full-vocabulary tensor that -1 would have. The DoS was completely unmitigated for that configuration; values just below vocab_size (e.g. 154,879) were equally expensive.

Verified: against the old sentinel-only logic, prompt_logprobs=154880, 154879, and even 21 all pass when max_logprobs=-1 — confirming the bypass was real.

The Fix: Resource Bound (replaces sentinel rejection)

Replaced the sentinel-only rejection with an explicit resource bound:

• VLLM_MAX_PROMPT_LOGPROBS (default 20) — caps prompt_logprobs
• VLLM_MAX_LOGPROBS (default 20) — caps sampling logprobs (C5)

Both are registered in vllm/envs.py. The validation now:

1. Resolves -1 to vocab_size (preserving the documented sentinel semantics)
2. Computes effective_max = min(max_logprobs, cap) — the env-var cap is immune to max_logprobs=-1
3. Rejects any value exceeding effective_max with an error naming both the requested value and the cap

This means -1, vocab_size, vocab_size-1, or any large integer are all rejected identically — the spelling no longer matters. An operator who needs more than 20 can raise the env var. This addresses C6: instead of outright rejection (a breaking change), we preserve the documented feature with a bound that removes the DoS.

Four Contract Sites Migrated (C4)

All four sites that defined the -1 contract are now consistent:

1. chat_completion/protocol.py: prompt_logprobs and top_logprobs validators now enforce the cap at the API edge (positive values > cap are rejected before reaching the engine)
2. completion/protocol.py: prompt_logprobs and logprobs validators now enforce the cap at the API edge
3. sampling_params.py _verify_args: error messages updated to reference the cap; -1 remains syntactically valid (resolved and capped in _validate_logprobs)
4. sampling_params.py field docstrings: updated to document the cap

C5: Sampling Logprobs Path

The identical unbounded allocation for logprobs=-1 (sampling, not prompt) at num_logprobs = model_config.get_vocab_size() was also vulnerable to the same bypass. Applied the same VLLM_MAX_LOGPROBS bound to that path.

Tests

14 tests total (5 original preserved + 9 new):

Test	Description
test_prompt_logprobs_minus_one_rejected	-1 resolves to vocab_size, exceeds cap (original, adapted)
test_prompt_logprobs_positive_still_works	20 within cap (original)
test_prompt_logprobs_zero_still_works	0 = disabled (original)
test_prompt_logprobs_none_still_works	None = unset (original)
test_prompt_logprobs_exceeds_max_still_rejected	100 > max_logprobs=20 (original)
test_prompt_logprobs_vocab_size_rejected	NEW: 154880 rejected even with max_logprobs=-1
test_prompt_logprobs_vocab_size_minus_one_rejected	NEW: 154879 rejected
test_prompt_logprobs_at_cap_accepted	NEW: 20 = cap, accepted
test_prompt_logprobs_above_cap_rejected	NEW: 21 = cap+1, rejected
test_prompt_logprobs_bypass_with_max_logprobs_minus_one	NEW: exact B9 scenario, error mentions VLLM_MAX_PROMPT_LOGPROBS
test_sample_logprobs_vocab_size_rejected	NEW (C5): sampling logprobs=154880 rejected
test_sample_logprobs_minus_one_rejected	NEW (C5): sampling logprobs=-1 rejected
test_sample_logprobs_at_cap_accepted	NEW (C5): sampling logprobs=20 accepted
test_prompt_logprobs_custom_cap	NEW: custom VLLM_MAX_PROMPT_LOGPROBS=100 works

All 14 pass. Verified that the new positive-value bypass tests fail against the OLD sentinel-only logic.

14 passed, 1 warning in 2.54s
``

### Files Changed
- `vllm/envs.py` — added `VLLM_MAX_PROMPT_LOGPROBS` and `VLLM_MAX_LOGPROBS` env vars (default 20)
- `vllm/sampling_params.py` — cap-based enforcement in `_validate_logprobs`, updated `_verify_args` messages and field docstrings
- `vllm/entrypoints/openai/chat_completion/protocol.py` — cap enforcement at API edge for `prompt_logprobs` and `top_logprobs`
- `vllm/entrypoints/openai/completion/protocol.py` — cap enforcement at API edge for `prompt_logprobs` and `logprobs`
- `tests/sampling/test_prompt_logprobs_security.py` — 9 new tests

### Nothing deliberately left unfixed
All findings (B9, C4, C5, C6) are addressed.

[malaiwah]

Again, a memory-related one that made me trip on a OOM while doing some work against the GG endpoint. My understanding is this is not GG specific and would apply to upstream as well.

[malaiwah]

Rebased onto current dev/gilded-gnosis

The previous push went DIRTY because dev/gilded-gnosis gained VLLM_PROMPT_LOGPROBS_CHUNK_SIZE in vllm/envs.py while this branch was adding VLLM_MAX_PROMPT_LOGPROBS / VLLM_MAX_LOGPROBS in the same region.

Resolution: purely additive — all three variables retained. Also restored the two TYPE_CHECKING declarations that the rebase dropped (VLLM_MAX_PROMPT_LOGPROBS: int = 20, VLLM_MAX_LOGPROBS: int = 20).

14 passed, 1 warning in 2.28s

Merge state is clean again.