CVE-2022-36012: TensorFlow: DoS via empty MLIR function attributes
HIGHA network-reachable crash in TensorFlow's MLIR graph compiler requires no authentication and no user interaction to trigger, making any exposed TF serving endpoint a trivial DoS target. Patch to TensorFlow 2.10.0, 2.9.1, 2.8.1, or 2.7.2 immediately — no workaround exists. Prioritize internet-facing inference services first.
Risk Assessment
CVSS 7.5 is accurate for this DoS-only vulnerability. The attack profile (network, low complexity, no privileges, no interaction) makes it trivially exploitable by any attacker who can reach a TF endpoint. Impact is confined to availability — no code execution, no data exfiltration. Risk is highest for organizations running public-facing TensorFlow Serving deployments; internal-only inference pipelines have lower but non-zero exposure. Not in CISA KEV and no evidence of active exploitation, reducing urgency slightly.
Affected Systems
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| tensorflow | pip | — | No patch |
Do you use tensorflow? You're affected.
Severity & Risk
Attack Surface
Recommended Action
5 steps-
Patch: Upgrade to TensorFlow 2.10.0, 2.9.1, 2.8.1, or 2.7.2 immediately.
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If patching is delayed: place TF serving endpoints behind an API gateway with strict input schema validation; reject malformed or empty function attribute payloads at the perimeter.
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Harden: Restrict network access to TF serving ports to trusted clients only — no public exposure without auth proxy.
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Monitor: Alert on TF process crashes or unexpected restarts as a detection signal.
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Inventory: Audit all services running TF 2.7.x–2.9.x to confirm patch coverage.
Classification
Compliance Impact
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2022-36012?
A network-reachable crash in TensorFlow's MLIR graph compiler requires no authentication and no user interaction to trigger, making any exposed TF serving endpoint a trivial DoS target. Patch to TensorFlow 2.10.0, 2.9.1, 2.8.1, or 2.7.2 immediately — no workaround exists. Prioritize internet-facing inference services first.
Is CVE-2022-36012 actively exploited?
No confirmed active exploitation of CVE-2022-36012 has been reported, but organizations should still patch proactively.
How to fix CVE-2022-36012?
1. Patch: Upgrade to TensorFlow 2.10.0, 2.9.1, 2.8.1, or 2.7.2 immediately. 2. If patching is delayed: place TF serving endpoints behind an API gateway with strict input schema validation; reject malformed or empty function attribute payloads at the perimeter. 3. Harden: Restrict network access to TF serving ports to trusted clients only — no public exposure without auth proxy. 4. Monitor: Alert on TF process crashes or unexpected restarts as a detection signal. 5. Inventory: Audit all services running TF 2.7.x–2.9.x to confirm patch coverage.
What systems are affected by CVE-2022-36012?
This vulnerability affects the following AI/ML architecture patterns: model serving, training pipelines, ML inference endpoints.
What is the CVSS score for CVE-2022-36012?
CVE-2022-36012 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 0.19%.
Technical Details
NVD Description
TensorFlow is an open source platform for machine learning. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Exploitation Scenario
An attacker enumerates an organization's AI inference infrastructure — via Shodan, internal network scan, or API documentation leak — and identifies an exposed TensorFlow Serving endpoint. They craft a minimal TFG function definition with empty attributes and submit it to the model import API. The `ConvertGenericFunctionToFunctionDef` call triggers an assertion crash, taking down the TF serving process. Repeating submissions sustains the outage. The attack requires no ML knowledge, no credentials, and no prior access — a script-kiddie-level DoS against production AI inference.
Weaknesses (CWE)
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H References
Timeline
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