BlackTreeCVE Intelligence
← Back to the CVE catalogue
Full vulnerability report · 2026
CVE-2026-11816High confidence

Path Traversal in keras-team/keras

keras-team · keras-team/keras

8.1HighCVSS 3.1
Recommended action
Within 7 days

High technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.

Patch available
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityHighOperational priority:Critical, raised one band.upgradedsince 21 Jul 2026

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • A structured source references public exploit or proof-of-concept material.
  • EPSS is 0.56% for the current model date.

Compensating controls

  • Validate the affected product branch and deploy the verified fixed release.
  • Restrict the affected network interface to trusted sources where business-safe.
  • Increase monitoring for the attack path and post-exploitation behaviour described in the report.

Verification

  1. Confirm that the asset runs keras-team keras-team/keras and falls inside the recorded affected range.
  2. Verify the installed build against the product-specific fixed version after deployment.
  3. Validate exposure, authentication requirements and compensating controls in the actual environment.
  4. Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Mitigation target: Within 3 daysRemediation target: Within 90 days

This automated reassessment organises public evidence. It does not know asset exposure, business impact or control effectiveness and does not replace CVSS or a human risk decision.

Open-source package ranges1 source-attributed range

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 packageAffected rangeFirst fixed versionEvidence
pipkeras< 3.14.03.14.0GitHub advisory ↗github reviewed aggregator · 7 Aug 2026
Direct vendor intelligence

Authoritative vendor CSAF and VEX advisories

Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.

1 current
CVE-2026-11816 · CSAF 2.0 · revision 3 · finalRed Hat Product Securitykeras: Keras: Arbitrary file write via path traversal in archive extraction utilities
12 fixed

The vendor explicitly identifies these products or versions as containing the fix.

  • registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:32c445d4b6b2ff8b9a45a518e073ae9f6e2c3b036873e09d04ab7d799a20a470_arm64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:b5a4acc27a64c62f6e4cac24d4b890fb6db2cde3e2b1d69bd98137932d9040a2_amd64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:c4beeb61db437f1caff171a2c55ec7c7b42b527658d81cc8d716bd38dd2ed787_s390x as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:d856ad602b5e1937f0499836feeaf6238658007e97570736d07d070da292becd_ppc64le as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-modelmesh-runtime-adapter-rhel9@sha256:ac13936a0f44d1b1e2357564018f72e5c919240de2570e06f8441e392b0a7a98_amd64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-modelmesh-runtime-adapter-rhel9@sha256:be9972eb91c651f4370752494d49dd12de5ee6e75c6e5834dc1e03af14cedf8f_arm64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9@sha256:85c2edc3a3e3ecf7cc97b39a67a83945065ca3990f8c4d7c31fe222de6aae76c_amd64 as a component of Red Hat OpenShift AI 3.3
  • registry.redhat.io/rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9@sha256:c56271bda7ecb294673084362eda995e669eeb9ab775ecc55ecf7d661efedf83_arm64 as a component of Red Hat OpenShift AI 3.3
  • registry.redhat.io/rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9@sha256:db93aac8c8746b868b0b455b29d0a5b527266e7d94cce51f3be31697dc447ccd_amd64 as a component of Red Hat OpenShift AI 3.3
  • registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:a0268e2bfc2046460c19cd92b4c9d91a946618301cf16917b5b801aaa6f29842_arm64 as a component of Red Hat OpenShift AI 3.3
  • registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:eb29643c173a284186ad3c6d3eb6adad258bfa0c311a1006ddb21d3e54a2988e_amd64 as a component of Red Hat OpenShift AI 3.3
  • registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9@sha256:d695b04c37d2ba40fb4e4fbfdd2f75437797b3478c4a951b6496fb472a0c2ca9_amd64 as a component of Red Hat OpenShift AI 3.3
Summary
A flaw was found in Keras. Attackers can exploit a path traversal vulnerability in the archive extraction utilities, specifically `filter_safe_tarinfos()` and `filter_safe_zipinfos()`. This occurs because the validation of archive member paths is performed against the process's current working directory (CWD) instead of the actual extraction destination. When the CWD is set to the filesystem root, this allows malicious paths to bypass security checks. Successful exploitation can lead to arbitrary file writes outside the intended directory, potentially enabling attackers to overwrite critical configuration files, inject malicious code, or corrupt machine learning data.
Remediation
For Red Hat OpenShift AI 2.25.9 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Choose official national sources for this report. Each advisory shows its original language. Your selection is remembered on this device and included in shared links.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2026-36244

No EUVD known-exploited evidence

ENISA has published the identifier mapping but no EUVD description has been stored yet.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
Not supplied in the stored EUVD record
Advisory evidence
No linked advisory details stored yet
Recommended actionWithin 7 days

High technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.

Patch available
01

What, why and how

Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.

What

Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.

Why

Attacker-controlled path data is not constrained to the intended directory before the application accesses a file.

How

An attacker operating through a network path may attempt exploitation without authentication after a user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

What

Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.

Why

Attacker-controlled path data is not constrained to the intended directory before the application accesses a file.

How

An attacker operating through a network path may attempt exploitation without authentication after a user interaction. 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
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

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
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
Reference recorded

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.

Likely attack path
a network path → Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') → cause the confidentiality, integrity or availability impact described by the vendor
Attack surface
Network
Privileges required
None: unauthenticated exploitation is possible
User interaction
Required interaction required
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-22 ↗

CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'). The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N

Common Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRNonePrivileges required: The attacker does not need an account or existing privileges.UIRequiredUser interaction: Another user must perform an action for exploitation to succeed.SUnchangedScope: The security impact remains within the vulnerable component's authority.CHighConfidentiality impact: A successful attack can cause a major loss.IHighIntegrity impact: A successful attack can cause a major loss.ANoneAvailability impact: No direct loss is represented by this metric.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkUnauthenticatedCWE-22Public exploit reference
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

JVN iPedia · Japanese · JVNDB-2026-021972Kerasにおけるパストラバーサルの脆弱性

Kerasのバージョン3.14.0未満には、keras/src/utils/file_utils.pyにあるアーカイブ展開ユーティリティにパス・トラバーサルの脆弱性があります。filter_safe_tarinfos()およびfilter_safe_zipinfos()関数は、アーカイブ内メンバーのパスを実際の展開先ではなく、プロセスのカレントワーキングディレクトリ(CWD)に対して検証します。プロセスがCWDを/に設定して実行される場合(Dockerコンテナ、CI/CDランナー、Jupyter環境で一般的)、検証の境界がファイルシステムのルートとなり、トラバーサルパスがセキュリティチェックを回避できてしまいます。さらに、zipフィルターにはブロックされたエントリに遭遇した際にAttributeErrorを引き起こすバグが存在し、展開が不完全になる問題も含まれています。加えて、Python 3.11のインストールではfilter="data"の安全網が欠如しており、欠陥のあるCWDベースのフィルターのみに依存しています。この脆弱性が悪用されると、意図した展開ディレクトリの外部に任意のファイル書き込みが可能となり、攻撃者が設定ファイルの上書きや悪意のあるコードの注入、機械学習データセットやパイプラインの破損を引き起こす恐れがあります。

Official advisory ↗
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
Affected
keras-team/keras: unspecified < 3.14.0
Fixed
Action
For Red Hat OpenShift AI 2.25.9 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/
Workaround
No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04

Evidence and provenance

Published 11 Jun 2026 · Last source change 21 Jul 2026, 12:05 UTC · CWE-22 · Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')

CVE recordCVE.org · 5.2
CVSS sourceOther authority
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
FIRST · tracked since 2026-08-14
European sourceENISA EUVD · EUVD-2026-36244
Product sourceCNA
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD modified after enrichment

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates ↗
  1. Affected versionsThe structured affected or fixed version information changed.
    Before
    unspecified < 3.14.0 · Fixed: An authoritative update reference is available, but the fixed version is not recorded in the structured CVE fields. Check the linked vendor advisory for the applicable release.
    After
    unspecified < 3.14.0 · Fixed: For Red Hat OpenShift AI 2.25.9 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/
    Red Hat Product Security ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
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.
Free version - for non-commercial use only.CVE-2026-11816 · cve.blacktree.nl