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HIGH severity

GHSA-68v3-g9cm-rmm6 tensorflow

HIGHFix: tensorflow/tensorflow@ff45913

GHSA-68v3-g9cm-rmm6 is a high-severity (CVSS 7.5) Out-of-bounds Read vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

TensorFlow vulnerable to Out-of-Bounds Read in GRUBlockCellGrad

Also known asBIT-tensorflow-2023-25658CVE-2023-25658PYSEC-2026-3120PYSEC-2026-3286PYSEC-2026-960
Published
Mar 24, 2023
Updated
Sep 10, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed
Exploitation data as of Sep 21, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-68v3-g9cm-rmm6.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs32th percentile — riskier than 32% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-68v3-g9cm-rmm6 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,333 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

3 pkgs affected
🐍tensorflow🐍tensorflow-cpu🐍tensorflow-gpu

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

Out of bounds read in GRUBlockCellGrad

func = tf.raw_ops.GRUBlockCellGrad

para = {'x': [[21.1, 156.2], [83.3, 115.4]], 'h_prev': array([[136.5],
      [136.6]]), 'w_ru': array([[26.7,  0.8],
      [47.9, 26.1],
      [26.2, 26.3]]), 'w_c': array([[ 0.4],
      [31.5],
      [ 0.6]]), 'b_ru': array([0.1, 0.2 ], dtype=float32), 'b_c': 0x41414141, 'r': array([[0.3],
      [0.4]], dtype=float32), 'u': array([[5.7],
      [5.8]]), 'c': array([[52.9],
      [53.1]]), 'd_h': array([[172.2],
      [188.3 ]])}

Patches

We have patched the issue in GitHub commit ff459137c2716a2a60f7d441b855fcb466d778cb.

The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by r3pwnx.

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.11.1pip install --upgrade 'tensorflow==2.11.1'
🐍PyPItensorflow-cpuall versions2.11.1pip install --upgrade 'tensorflow-cpu==2.11.1'
🐍PyPItensorflow-gpuall versions2.11.1pip install --upgrade 'tensorflow-gpu==2.11.1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.11.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-68v3-g9cm-rmm6 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-68v3-g9cm-rmm6 can be triaged on real exposure rather than presence alone.

Tailored to GHSA-68v3-g9cm-rmm6. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact Out of bounds read in GRUBlockCellGrad ```python func = tf.raw_ops.GRUBlockCellGrad para = {'x': [[21.1, 156.2], [83.3, 115.4]], 'h_prev': array([[136.5], [136.6]]), 'w_ru': array([[26.7, 0.8], [47.9, 26.1], [26.2, 26.3]]), 'w_c': array([[ 0.4], [31.5], [ 0.6]]), 'b_ru': array([0.1, 0.2 ], dtype=float32), 'b_c': 0x41414141, 'r': array([[0.3], [0.4]], dtype=float32), 'u': array([[5.7], [5.8]]), 'c': array([[52.9], [53.1]]), 'd_h': array([[172.2], [188.3 ]])} ``` ### Patches We have patched the issue in GitHub commit [ff459137c2
O3 Security · Impact-Aware SCA

Is GHSA-68v3-g9cm-rmm6 in your dependencies?

O3 Security finds GHSA-68v3-g9cm-rmm6 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-68v3-g9cm-rmm6: High 7.5 severity | O3 Security