Evidence used
- No CISA KEV confirmation is currently recorded.
- A structured source references public exploit or proof-of-concept material.
- EPSS is 0.77% for the current model date.
BlackTreeCVE IntelligenceUnknown · Unknown
Official source article: GitHub GHSA-C582-C96P-R5CQ ↗. Check the applicable product and release in the original source.
Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
Debian findings are scoped to the named distribution, release and source package. An absent finding does not mean a package is unaffected.
A published vendor fix does not prove that a matching update is enabled and installable on a particular asset. Confirm the local package candidate before scheduling remediation.
| Distribution release | Source package | Vendor state | Fixed version | Evidence |
|---|---|---|---|---|
| Debian forkyforky · source | tensorflow | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 6 Oct 2026 |
| Debian sidsid · source | tensorflow | Not affectedDebian marks this release not affected (fixed-version marker 0). | Not published in this feed | Debian Security Tracker ↗Source updated 6 Oct 2026 |
These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.
| Ecosystem and package | Affected range | First fixed version | Evidence |
|---|---|---|---|
| piptensorflow | < 2.5.3 | 2.5.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow | >= 2.6.0, < 2.6.3 | 2.6.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow | = 2.7.0 | 2.7.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | < 2.5.3 | 2.5.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | >= 2.6.0, < 2.6.3 | 2.6.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | = 2.7.0 | 2.7.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | < 2.5.3 | 2.5.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | >= 2.6.0, < 2.6.3 | 2.6.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | = 2.7.0 | 2.7.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
Patch availableTensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.
Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may disrupt the affected service.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
A structured CVE source labels at least one public reference as exploit material. BlackTree has not independently validated that it is safe, reliable or weaponised.
CWE-770: Allocation of Resources Without Limits or Throttling. The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:LCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 3 Feb 2022 · Last source change 12 Feb 2025, 15:58 UTC · CWE-770 · Allocation of Resources Without Limits or Throttling
Missing structured fields: affected product. Missing data is not evidence of low risk; review the primary advisory.
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.