CVE-2022-41899 — HIGH (CVSS 7.5) AI Security Vulnerability

CISO Take

A remotely exploitable, no-auth-required crash in TensorFlow's SDCA optimizer can take down any ML inference service that accepts external feature inputs. Any production deployment exposing a TensorFlow serving endpoint backed by linear/logistic models trained with SdcaOptimizer is at risk of a full availability loss. Patch immediately to TF 2.11, 2.10.1, 2.9.3, or 2.8.4, and add input rank validation at API boundaries.

Risk Assessment

CVSS 7.5 High with AV:N/AC:L/PR:N/UI:N — worst-case exploitability profile for a DoS. No credentials, no user interaction, no complexity barrier: any unauthenticated caller who can reach the inference endpoint can trigger the crash. Impact is pure availability (C:N/I:N/A:H), so no data exposure, but repeated crashes can constitute sustained service disruption. Not in CISA KEV and no confirmed wild exploitation as of enrichment date, which moderates urgency slightly for air-gapped or internal-only deployments.

Affected Systems

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

Do you use tensorflow? You're affected.

Severity & Risk

CVSS 3.1

7.5 / 10

EPSS

0.2%

chance of exploitation in 30 days

Higher than 39% 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 Network

AC Low

PR None

UI None

S Unchanged

C None

I None

A High

Recommended Action

5 steps

Patch: upgrade to TF 2.11, 2.10.1, 2.9.3, or 2.8.4 (commit 80ff197d).
Validate input tensor rank at API boundary before forwarding to model: reject any request where dense_features or example_state_data rank ≠ 2 with a 400 error.
Run TF Serving behind an API gateway that enforces schema validation on input shape/rank.
Deploy process supervisors (systemd, Kubernetes liveness probes) to auto-restart crashed serving processes — reduces blast radius while patching.
Detection: monitor for abrupt serving process exits and sudden spike in 5xx errors from the inference endpoint as indicators of 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.T0006 - Active Scanning AML.T0029 - Denial of AI Service AML.T0049 - Exploit Public-Facing Application

Compliance Impact

This CVE is relevant to:

EU AI Act

Article 15 - Accuracy, Robustness and Cybersecurity (High-Risk AI)

ISO 42001

A.6.2.5 - AI System Availability and Resilience

NIST AI RMF

MANAGE-2.4 - Risk Monitoring and Incident Response for AI Systems MAP-5.1 - Likelihood and Impact of AI Risks

Frequently Asked Questions

What is CVE-2022-41899?

A remotely exploitable, no-auth-required crash in TensorFlow's SDCA optimizer can take down any ML inference service that accepts external feature inputs. Any production deployment exposing a TensorFlow serving endpoint backed by linear/logistic models trained with SdcaOptimizer is at risk of a full availability loss. Patch immediately to TF 2.11, 2.10.1, 2.9.3, or 2.8.4, and add input rank validation at API boundaries.

Is CVE-2022-41899 actively exploited?

Proof-of-concept exploit code is publicly available for CVE-2022-41899, increasing the risk of exploitation.

How to fix CVE-2022-41899?

1. Patch: upgrade to TF 2.11, 2.10.1, 2.9.3, or 2.8.4 (commit 80ff197d). 2. Validate input tensor rank at API boundary before forwarding to model: reject any request where dense_features or example_state_data rank ≠ 2 with a 400 error. 3. Run TF Serving behind an API gateway that enforces schema validation on input shape/rank. 4. Deploy process supervisors (systemd, Kubernetes liveness probes) to auto-restart crashed serving processes — reduces blast radius while patching. 5. Detection: monitor for abrupt serving process exits and sudden spike in 5xx errors from the inference endpoint as indicators of active exploitation attempts.

What systems are affected by CVE-2022-41899?

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

What is the CVSS score for CVE-2022-41899?

CVE-2022-41899 has a CVSS v3.1 base score of 7.5 (HIGH). The EPSS exploitation probability is 0.18%.

Technical Details

NVD Description

TensorFlow is an open source platform for machine learning. Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in `SdcaOptimizer`. We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

Exploitation Scenario

Adversary identifies a public or semi-public TensorFlow Serving endpoint via active scanning or documentation disclosure. They determine the model uses SdcaOptimizer (inferrable from model metadata, API schema, or error messages leaking TF op names). They craft a predict request where dense_features has rank 1 (a 1-D tensor instead of 2-D matrix). TensorFlow's CHECK macro fires inside sdca_internal.cc, raising a fatal signal that kills the serving process. With no restart automation, the endpoint goes dark. With restart automation, adversary loops the request to maintain denial of service with trivial request volume — no flood required, one malformed request per restart cycle suffices.