CVE-2021-29513 — HIGH (CVSS 7.8) AI Security Vulnerability

CISO Take

Any TensorFlow deployment that accepts external tensor inputs is at risk of process crash or potential code execution via type confusion in the Python-to-C++ conversion layer. Patch to TF 2.5.0 (or 2.4.2/2.3.3/2.2.3/2.1.4 for pinned versions) immediately. Multi-tenant ML platforms and model serving APIs with untrusted input are highest priority.

Risk Assessment

CVSS 7.8 High with local attack vector and low privilege requirement. The full CIA impact score (C:H/I:H/A:H) suggests exploitation potential beyond simple DoS — type confusion vulnerabilities can enable memory corruption and code execution. Not in CISA KEV with no confirmed active exploitation, but trivial exploitation complexity elevates practical risk in shared ML environments significantly.

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

7.8 / 10

EPSS

0.0%

chance of exploitation in 30 days

Higher than 1% of all CVEs

Source: EPSS v3 — FIRST.org

Exploitation Status

Exploit Available

Exploitation: MEDIUM

Sophistication

Trivial

Exploitation Confidence

medium

○ 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 High

I High

A High

Recommended Action

5 steps

Upgrade TensorFlow to 2.5.0, or cherry-picked branches 2.4.2/2.3.3/2.2.3/2.1.4.
Enforce numeric dtype validation before passing tensors to TF operations at all API boundaries.
Run TF inference processes in isolated containers to limit blast radius.
Monitor for unexpected TF process crashes in serving infrastructure.
Audit any externally-accessible TensorFlow Serving endpoints for unauthenticated tensor submission.

Classification

Code Execution DoS Framework Inference AML.T0029 - Denial of AI Service AML.T0043 - Craft Adversarial Data AML.T0049 - Exploit Public-Facing Application

Compliance Impact

This CVE is relevant to:

EU AI Act

Art. 15 - Accuracy, robustness and cybersecurity

ISO 42001

8.4 - AI system risk treatment

NIST AI RMF

MANAGE-2.2 - Mechanisms to maintain AI system operations

OWASP LLM Top 10

LLM05:2025 - Improper Output Handling

Frequently Asked Questions

What is CVE-2021-29513?

Any TensorFlow deployment that accepts external tensor inputs is at risk of process crash or potential code execution via type confusion in the Python-to-C++ conversion layer. Patch to TF 2.5.0 (or 2.4.2/2.3.3/2.2.3/2.1.4 for pinned versions) immediately. Multi-tenant ML platforms and model serving APIs with untrusted input are highest priority.

Is CVE-2021-29513 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2021-29513, increasing the risk of exploitation.

How to fix CVE-2021-29513?

1. Upgrade TensorFlow to 2.5.0, or cherry-picked branches 2.4.2/2.3.3/2.2.3/2.1.4. 2. Enforce numeric dtype validation before passing tensors to TF operations at all API boundaries. 3. Run TF inference processes in isolated containers to limit blast radius. 4. Monitor for unexpected TF process crashes in serving infrastructure. 5. Audit any externally-accessible TensorFlow Serving endpoints for unauthenticated tensor submission.

What systems are affected by CVE-2021-29513?

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

What is the CVSS score for CVE-2021-29513?

CVE-2021-29513 has a CVSS v3.1 base score of 7.8 (HIGH). The EPSS exploitation probability is 0.01%.

Technical Details

NVD Description

TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Exploitation Scenario

An attacker with low-privilege access to a shared ML platform (Jupyter user, API client) submits a tensor with string or boolean dtype to a TF operation expecting float/int. The ndarray_tensor.cc Python-to-C++ conversion path dereferences a null pointer, crashing the TF process. In a worst-case memory corruption scenario, controlled exploitation achieves code execution within the ML serving process, enabling pivot to model weights, training data, or adjacent services on the host.