Evidence used
- No CISA KEV confirmation is currently recorded.
- Exploitation requires an existing local or physical foothold with privileges.
- EPSS is 0.16% for the current model date.
BlackTreeCVE IntelligenceFull vulnerability report · 2021
CVE-2021-37690High confidence
Use after free and segfault in shape inference functions in TensorFlow
tensorflow · tensorflow
Official source article: GitHub GHSA-3HXH-8CP2-G4HG ↗. Check the applicable product and release in the original source.
6.6MediumCVSS 3.1
Scheduled
Patch availableMedium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.
R
Open reassessment dashboard →Operational reassessment
Published severity in operational context
Published severityMedium→Operational priority:Low, lowered one band.downgradedsince 4 Aug 2024
Compensating controls
- Validate the affected product branch and deploy the verified fixed release.
- Restrict local access and enforce least privilege on affected hosts.
- Monitor vendor guidance and exploitation sources for a material change.
Verification
- Confirm that the asset runs tensorflow tensorflow and falls inside the recorded affected range.
- Verify the installed build against the product-specific fixed version after deployment.
- Validate exposure, authentication requirements and compensating controls in the actual environment.
- Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Distribution package intelligence
2 package statesRelease-specific package status
Debian findings are scoped to the named distribution, release and source package. An absent finding does not mean a package is unaffected.
Repository candidate not checked
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 7 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 7 Oct 2026 |
Open-source package ranges9 source-attributed ranges
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 | < 2.3.4 | 2.3.4 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow | >= 2.4.0, < 2.4.3 | 2.4.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow | = 2.5.0 | 2.5.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | < 2.3.4 | 2.3.4 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | >= 2.4.0, < 2.4.3 | 2.4.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-cpu | = 2.5.0 | 2.5.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | < 2.3.4 | 2.3.4 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | >= 2.4.0, < 2.4.3 | 2.4.3 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
| piptensorflow-gpu | = 2.5.0 | 2.5.1 | GitHub advisory ↗upstream repository advisory · 13 Nov 2024 |
Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.
Patch available01
What, why and how
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
What
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Why
The program can continue using memory after it has been released, producing unsafe and attacker-influenceable behaviour.
How
An attacker operating through local access may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
What
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Why
The program can continue using memory after it has been released, producing unsafe and attacker-influenceable behaviour.
How
An attacker operating through local access may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
02
Exploit reality and attack path
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
Observed exploitation No confirmed evidence
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
Public PoC / exploit material None recorded
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
- Likely attack path
- local access → Use After Free → cause the confidentiality, integrity or availability impact described by the vendor
- Attack surface
- Local
- Privileges required
- Low: a basic authenticated account is required
- User interaction
- None
- Attack complexity
- Low: no specialised conditions are recorded
- Security boundary
- Unchanged: impact remains within the vulnerable component's security authority
- Weakness
?
CWE means Common Weakness Enumeration: a standard category for the underlying weakness. - CWE-416 ↗
CWE-416: Use After Free. The product reuses or references memory after it has been freed. At some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. Any operations using the original pointer are no longer valid because the memory belongs to the code that operates on the new pointer.
- CVSS vector
?
CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity. CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:HCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
AVLocalAttack vector: The attacker needs local access to the vulnerable system.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRLowPrivileges required: The attacker needs basic user-level privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CLowConfidentiality impact: A successful attack can cause a limited loss.ILowIntegrity impact: A successful attack can cause a limited loss.AHighAvailability impact: A successful attack can cause a major loss.- Post-exploitation / living off the land
- The issue can support a local privilege or sandbox boundary transition; normal system utilities may then be available in the gained context.
03
Patch and workaround
Operational remediation based on structured source evidence.
- Status
?
Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change. - Patch available
- Action
- Review the linked authoritative reference and apply the recorded fixed release appropriate to the affected product branch.
- Workaround
- No verified workaround is recorded. Limit untrusted access and use least privilege until authoritative guidance is available.
04
Evidence and provenance
Published 12 Aug 2021 · Last source change 4 Aug 2024, 01:23 UTC · CWE-416 · Use After Free
CVE recordCVE.org · 5.1
CVSS sourceCNA
EPSS source FIRST · tracked since 2026-08-14
?
The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.European sourceENISA EUVD · EUVD-2021-0416
Product sourceCNA
Remediation sourceCVE/CNA references
CWE sourceCNA
NVD statusNVD modified after enrichment
Core structured fields are present and their contributing authorities are shown above.
Material change intelligence
View recent updates ↗What changed after publication
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.
CVE published
Fixed release or patch reference recorded
Technical terms and abbreviations used in this report
- CVE
- Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
- CVSS
- Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
- EPSS
- Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
- CWE
- Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
- CNA
- CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
- CISA ADP
- Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
- NVD
- National Vulnerability Database: NIST's enrichment service for CVE records.
- CERT / CSIRT
- A computer security incident response team that publishes warnings or coordinates incident response.
- PoC
- Proof of concept: public material that demonstrates or helps reproduce exploitation.
- CSAF
- Common Security Advisory Framework: a machine-readable format for security advisories.
- LoTL
- Living off the land: abuse of legitimate tools or system functions during an attack.