DoS
Denial of service is cheap against AI systems because inference is expensive. A single request asking for a very long context, a recursive thinking pattern, or a maximally complex tokenization ("unicode bombs") can consume seconds of GPU time. Agent frameworks add a more dangerous variant: a prompt that tricks the agent into invoking itself or another expensive tool in a loop, fanning out until the budget is exhausted. For paid model APIs, the same attack is also a financial denial of service — the attacker doesn't take the service down, they run up the bill. We have seen production CVEs of all three shapes in inference servers (vLLM, TGI), agent frameworks (LangChain, AutoGen), and applications using third-party LLM APIs without per-tenant budget caps. Defenses: per-request token and time limits, per-tenant compute and budget quotas, depth limits on agent recursion, and circuit breakers on tool invocation.
| Severity | CVE | Headline | Package | CVSS |
|---|---|---|---|---|
| HIGH | CVE-2022-35993 | TensorFlow: DoS via malformed SetSize tensor shape | tensorflow | 7.5 |
| HIGH | CVE-2022-35994 | TensorFlow: CollectiveGather assertion DoS via scalar | tensorflow | 7.5 |
| HIGH | CVE-2022-35995 | TensorFlow: DoS via AudioSummaryV2 CHECK failure | tensorflow | 7.5 |
| HIGH | CVE-2022-35996 | TensorFlow: Conv2D DoS via empty input tensor | tensorflow | 7.5 |
| HIGH | CVE-2022-35997 | TensorFlow: CHECK-fail DoS in tf.sparse.cross op | tensorflow | 7.5 |
| HIGH | CVE-2022-35998 | TensorFlow: DoS via EmptyTensorList CHECK fail | tensorflow | 7.5 |
| HIGH | CVE-2022-35999 | TensorFlow: DoS via empty Conv2DBackpropInput tensors | tensorflow | 7.5 |
| HIGH | CVE-2022-36000 | TensorFlow: null deref crashes MLIR graph conversion | tensorflow | 7.5 |
| HIGH | CVE-2022-36001 | TensorFlow: DoS via type confusion in DrawBoundingBoxes | tensorflow | 7.5 |
| HIGH | CVE-2022-36002 | TensorFlow: DoS via Unbatch assertion failure | tensorflow | 7.5 |
| HIGH | CVE-2022-36003 | TensorFlow: DoS via RandomPoissonV2 large input | tensorflow | 7.5 |
| HIGH | CVE-2022-36004 | TensorFlow: DoS via tf.random.gamma CHECK assertion | tensorflow | 7.5 |
| HIGH | CVE-2022-36005 | TensorFlow: DoS via CHECK fail in fake_quant gradient | tensorflow | 7.5 |
| HIGH | CVE-2022-36011 | TensorFlow: null deref DoS in MLIR function conversion | tensorflow | 7.5 |
| HIGH | CVE-2022-36012 | TensorFlow: DoS via empty MLIR function attributes | tensorflow | 7.5 |
| HIGH | CVE-2022-36013 | TensorFlow MLIR: null ptr deref crashes model serving | tensorflow | 7.5 |
| HIGH | CVE-2022-36014 | TensorFlow: null ptr dereference in MLIR causes remote DoS | tensorflow | 7.5 |
| HIGH | CVE-2022-36015 | TensorFlow: integer overflow in RangeSize causes DoS | tensorflow | 7.5 |
| HIGH | CVE-2022-36016 | TensorFlow: CHECK-fail assertion crashes model serving | tensorflow | 7.5 |
| HIGH | CVE-2022-36017 | TensorFlow: DoS via malformed Requantize tensors | tensorflow | 7.5 |