CVE-2021-29584 — MEDIUM (CVSS 5.5) AI Security Vulnerability

CISO Take

A local attacker with low privileges can crash TensorFlow processes by crafting a SparseSplit operation with oversized tensor dimensions, triggering an integer overflow and CHECK-fail assertion. In shared ML platforms—Jupyter hubs, multi-tenant model servers, or internal AI APIs accepting user-defined ops—this becomes a practical availability threat. Upgrade to TF 2.5.0 or patched backports (2.4.2, 2.3.3, 2.2.3, 2.1.4) immediately; restrict untrusted tensor op submission in shared environments as a compensating control.

Risk Assessment

Medium overall, but context-dependent. The CVSS 5.5 score reflects local access requirement, which limits mass exploitation. However, in shared ML infrastructure (multi-tenant Jupyter, internal model serving endpoints, AutoML platforms), 'local access' is often a low bar—any authenticated user or API consumer qualifies. No in-the-wild exploitation recorded, not in CISA KEV. The trivial exploitation mechanics (craft oversized shape dimensions) elevate practical risk above the base score in shared-compute environments.

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

0.0%

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 None

I None

A High

Recommended Action

5 steps

PATCH

Upgrade TensorFlow to ≥2.5.0 or apply backports: 2.4.2, 2.3.3, 2.2.3, or 2.1.4. Commit fix: 4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60.
VALIDATE INPUT

Add dimension bounds checks before passing user-supplied shapes to SparseSplit; reject requests where shape dimensions exceed safe thresholds.
ISOLATE

Run TF model servers in separate processes per user/tenant to contain blast radius of a crash.
MONITOR

Alert on abnormal TF process terminations (SIGABRT/CHECK-fail logs) as potential exploitation indicators.
DETECT

Search for patterns like extreme tensor dimension values (approaching INT64_MAX) in model serving logs.

Classification

DoS Framework Inference AML.T0010.001 - AI Software AML.T0029 - Denial of AI Service AML.T0049 - Exploit Public-Facing Application

Compliance Impact

This CVE is relevant to:

EU AI Act

Art.15 - Accuracy, robustness and cybersecurity for high-risk AI

ISO 42001

A.9.2 - AI System Availability and Resilience

NIST AI RMF

GOVERN-1.4 - Organizational teams are committed to risk management MANAGE-2.2 - Mechanisms to sustain AI risk management

Frequently Asked Questions

What is CVE-2021-29584?

A local attacker with low privileges can crash TensorFlow processes by crafting a SparseSplit operation with oversized tensor dimensions, triggering an integer overflow and CHECK-fail assertion. In shared ML platforms—Jupyter hubs, multi-tenant model servers, or internal AI APIs accepting user-defined ops—this becomes a practical availability threat. Upgrade to TF 2.5.0 or patched backports (2.4.2, 2.3.3, 2.2.3, 2.1.4) immediately; restrict untrusted tensor op submission in shared environments as a compensating control.

Is CVE-2021-29584 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2021-29584, increasing the risk of exploitation.

How to fix CVE-2021-29584?

1. PATCH: Upgrade TensorFlow to ≥2.5.0 or apply backports: 2.4.2, 2.3.3, 2.2.3, or 2.1.4. Commit fix: 4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60. 2. VALIDATE INPUT: Add dimension bounds checks before passing user-supplied shapes to SparseSplit; reject requests where shape dimensions exceed safe thresholds. 3. ISOLATE: Run TF model servers in separate processes per user/tenant to contain blast radius of a crash. 4. MONITOR: Alert on abnormal TF process terminations (SIGABRT/CHECK-fail logs) as potential exploitation indicators. 5. DETECT: Search for patterns like extreme tensor dimension values (approaching INT64_MAX) in model serving logs.

What systems are affected by CVE-2021-29584?

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

What is the CVSS score for CVE-2021-29584?

CVE-2021-29584 has a CVSS v3.1 base score of 5.5 (MEDIUM). The EPSS exploitation probability is 0.01%.

Technical Details

NVD Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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 internal data scientist on a shared ML platform submits a SparseSplit operation via a Jupyter notebook with a dense_shape tensor constructed so that multiplying its dimensions causes integer overflow (e.g., shape [9223372036854775807, 2]). TensorShape constructor calls InitDims, which returns a non-OK status due to overflow; the CHECK macro triggers, sending SIGABRT to the TF process. In a shared model-serving scenario, a single crafted API request to an endpoint accepting sparse tensor inputs crashes the serving process, causing a denial of service for all concurrent users. Requires no exploit payload, just knowledge of the overflow condition.