CVE-2022-29198 — MEDIUM (CVSS 5.5) AI Security Vulnerability

CISO Take

This medium-severity DoS in TensorFlow crashes the runtime via malformed sparse tensor inputs—no RCE, no data leakage. Risk is real in shared ML environments (Jupyter clusters, multi-tenant GPU nodes) where low-privileged users can submit crafted inputs. Patch to TF 2.9.0/2.8.1/2.7.2/2.6.4 at next maintenance window; no emergency action required.

Risk Assessment

CVSS 5.5 Medium with local attack vector and low privilege requirement limits blast radius. Exploitation requires access to the TF runtime, which in practice means shared notebooks, Kubeflow pipelines, or on-prem GPU clusters with multi-user access. No evidence of active exploitation and not in CISA KEV. Severity elevates in high-availability inference environments where process crashes affect SLAs, but remains low-priority compared to RCE or data exposure vectors.

Affected Systems

Package	Ecosystem	Vulnerable Range	Patched
tensorflow	pip	—	No patch
195.0K OpenSSF 7.2 3.7K dependents Pushed 6d ago 4% patched ~1372d to patch Full package profile →

Do you use tensorflow? You're affected.

Severity & Risk

CVSS 3.1

5.5 / 10

EPSS

0.1%

chance of exploitation in 30 days

Higher than 17% of all CVEs

Source: EPSS v3 — FIRST.org

Exploitation Status

Exploit Available

Exploitation: MEDIUM

Sophistication

Trivial

Exploitation Confidence

medium

○ CISA SSVC: Public PoC

○ Public PoC indexed (trickest/cve)

Composite signal derived from CISA KEV, CISA SSVC, EPSS, trickest/cve, and Nuclei templates.

Attack Surface

AV Local

AC Low

PR Low

UI None

S Unchanged

C None

I None

A High

Recommended Action

5 steps

Upgrade TensorFlow to 2.9.0, 2.8.1, 2.7.2, or 2.6.4.
If immediate patching is not possible, validate that dense_shape is rank-1 and indices is rank-2 before calling SparseTensorToCSRSparseMatrix at the application layer.
In shared environments, restrict which users can submit raw ops to the TF runtime.
For inference services, add input shape validation at the API gateway before tensors reach TF.
Monitor for unexpected TF process crashes—repeated CHECK-failure crashes with user-controlled inputs indicate active exploitation attempts.

CISA SSVC Assessment

Decision Track*

Exploitation poc

Automatable No

Technical Impact partial

Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.

Classification

DoS Framework Inference AML.T0029 - Denial of AI Service AML.T0034 - Cost Harvesting AML.T0049 - Exploit Public-Facing Application

Compliance Impact

This CVE is relevant to:

EU AI Act

Article 15 - Accuracy, Robustness and Cybersecurity

ISO 42001

A.6.1.4 - AI System Availability and Resilience

NIST AI RMF

MANAGE-2.2 - Risk Response: Availability and Resilience

OWASP LLM Top 10

LLM04 - Model Denial of Service

Frequently Asked Questions

What is CVE-2022-29198?

This medium-severity DoS in TensorFlow crashes the runtime via malformed sparse tensor inputs—no RCE, no data leakage. Risk is real in shared ML environments (Jupyter clusters, multi-tenant GPU nodes) where low-privileged users can submit crafted inputs. Patch to TF 2.9.0/2.8.1/2.7.2/2.6.4 at next maintenance window; no emergency action required.

Is CVE-2022-29198 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2022-29198, increasing the risk of exploitation.

How to fix CVE-2022-29198?

1. Upgrade TensorFlow to 2.9.0, 2.8.1, 2.7.2, or 2.6.4. 2. If immediate patching is not possible, validate that dense_shape is rank-1 and indices is rank-2 before calling SparseTensorToCSRSparseMatrix at the application layer. 3. In shared environments, restrict which users can submit raw ops to the TF runtime. 4. For inference services, add input shape validation at the API gateway before tensors reach TF. 5. Monitor for unexpected TF process crashes—repeated CHECK-failure crashes with user-controlled inputs indicate active exploitation attempts.

What systems are affected by CVE-2022-29198?

This vulnerability affects the following AI/ML architecture patterns: training pipelines, model serving, inference, shared ML platforms.

What is the CVSS score for CVE-2022-29198?

CVE-2022-29198 has a CVSS v3.1 base score of 5.5 (MEDIUM). The EPSS exploitation probability is 0.06%.

Technical Details

NVD Description

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorToCSRSparseMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Exploitation Scenario

An attacker with access to a shared Jupyter Hub instance or Kubeflow pipeline crafts a SparseTensor where dense_shape is a matrix instead of a vector, or indices is a vector instead of a matrix. Passing this to tf.raw_ops.SparseTensorToCSRSparseMatrix triggers an unchecked assertion failure, crashing the TF process. In a multi-tenant ML platform, this disrupts other users' training jobs sharing the same runtime. In an inference API exposing sparse tensor endpoints, repeated calls constitute a targeted availability attack without rate limiting.