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Full vulnerability report · 2026
CVE-2026-58659High confidence

PyTorch Lightning Arbitrary Code Execution via _instantiator Hyperparameter

Lightning-AI · pytorch-lightning

8.4HighCVSS 4.0
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:High, unchanged from published severity.unchanged

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • A structured source references public exploit or proof-of-concept material.
  • EPSS is 0.63% for the current model date.

Compensating controls

  • Validate the affected product branch and deploy the verified fixed release.
  • Restrict local access and enforce least privilege on affected hosts.
  • Increase monitoring for the attack path and post-exploitation behaviour described in the report.

Verification

  1. Confirm that the asset runs Lightning-AI pytorch-lightning 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 30 daysRemediation target: Within 180 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 ranges4 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 packageAffected rangeFirst fixed versionEvidence
PyPIlightningECOSYSTEM: introduced 0; fixed 2.6.62.6.6OSV record ↗aggregator derived · 24 Sep 2026
PyPIlightningECOSYSTEM: introduced 0; fixed 2.6.62.6.6OSV record ↗source linked ecosystem record · 10 Sep 2026
PyPIpytorch-lightningECOSYSTEM: introduced 0; fixed 2.6.62.6.6OSV record ↗source linked ecosystem record · 10 Sep 2026
piplightning< 2.6.62.6.6GitHub advisory ↗github reviewed aggregator · 24 Sep 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-2026-58659 · CSAF 2.0 · revision 3 · finalRed Hat Product Securitypytorch-lightning: PyTorch Lightning: Remote code execution via malicious checkpoint files
7 known affected

The vendor explicitly identifies these products as affected by this CVE.

  • rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server
  • rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
  • rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
Summary
A flaw was found in PyTorch Lightning. This vulnerability allows attackers to achieve remote code execution by crafting malicious checkpoint files. These files exploit a weakness in the _load_state function, which imports and executes attacker-controlled module names from checkpoint instantiator hyperparameters, bypassing existing security protections.
Remediation
For more information visit https://access.redhat.com/errata/RHSA-2026:68699
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-2026-44751

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

PyTorch Lightning through 2.6.5, fixed in commit d710d68, contains a remote code execution vulnerability in the _load_state function that imports and executes attacker-controlled module names from checkpoint _instantiator hyperparameters. Attackers can craft malicious checkpoint files that bypass weights_only=True protections to execute arbitrary code when LightningModule.load_from_checkpoint is called.

What

PyTorch Lightning through 2.6.5, fixed in commit d710d68, contains a remote code execution vulnerability in the _load_state function that imports and executes attacker-controlled module names from checkpoint _instantiator hyperparameters. Attackers can craft malicious checkpoint files that bypass weights_only=True protections to execute arbitrary code when LightningModule.load_from_checkpoint is called.

Why

The product uses external input with reflection to select which classes or code to use, but it does not sufficiently prevent the input from selecting improper classes or code.

How

An attacker operating through local access may attempt exploitation when the stated preconditions are met. If successful, the issue may execute code or commands in the affected security context.

What

PyTorch Lightning through 2.6.5, fixed in commit d710d68, contains a remote code execution vulnerability in the _load_state function that imports and executes attacker-controlled module names from checkpoint _instantiator hyperparameters. Attackers can craft malicious checkpoint files that bypass weights_only=True protections to execute arbitrary code when LightningModule.load_from_checkpoint is called.

Why

The product uses external input with reflection to select which classes or code to use, but it does not sufficiently prevent the input from selecting improper classes or code.

How

An attacker operating through local access may attempt exploitation when the stated preconditions are met. If successful, the issue may execute code or commands in the affected security context.

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
local access → Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection') → execute code or commands in the affected security context
Attack surface
Local
Privileges required
None: unauthenticated exploitation is possible
User interaction
Active interaction required
Attack complexity
Low: no specialised conditions are recorded
Security boundary
Not a CVSS 4.0 base metric
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-470 ↗

CWE-470: Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection'). The product uses external input with reflection to select which classes or code to use, but it does not sufficiently prevent the input from selecting improper classes or code.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Common Vulnerability Scoring System 4.0: 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.ATNoneAttack requirements: No additional deployment or execution condition is required.PRNonePrivileges required: The attacker does not need an account or existing privileges.UIActiveUser interaction: A user must take a deliberate action for exploitation to succeed.VCHighVulnerable-system confidentiality: A successful attack can cause a major loss.VIHighVulnerable-system integrity: A successful attack can cause a major loss.VAHighVulnerable-system availability: A successful attack can cause a major loss.SCNoneSubsequent-system confidentiality: No direct loss is represented by this metric.SINoneSubsequent-system integrity: No direct loss is represented by this metric.SANoneSubsequent-system availability: No direct loss is represented by this metric.
Post-exploitation / living off the land
After compromise, an attacker may use built-in shells, scripting engines, scheduled tasks and native network utilities for discovery, persistence or movement. This is a plausible LoTL path, not evidence that it has occurred for every attack.
UnauthenticatedRemote code executionCWE-470Public exploit reference
A

Official authority intelligence

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

Cyber Security Agency of Singapore · English · CSA-SB-20260722Security Bulletin 22 Jul 2026

The Cyber Security Agency of Singapore included this CVE in its official Security Bulletin 22 Jul 2026, published on 22 July 2026. Open the linked bulletin for the product, severity and reference information published in that issue.

Official advisory ↗
JVN iPedia · Japanese · JVNDB-2026-027393Lightning AIのPyTorch Lightningにおけるクラスまたはコードを選択する外部から制御された入力の使用に関する脆弱性

PyTorch Lightningのバージョン2.6.5まで（修正はコミットd710d68にて）において、_load_state関数にリモートコード実行の脆弱性が存在します。この関数はチェックポイントの_instantiatorハイパーパラメータから、攻撃者が制御するモジュール名をインポートおよび実行します。攻撃者は悪意のあるチェックポイントファイルを作成し、weights_only=Trueの保護を回避して、LightningModule.load_from_checkpointが呼び出された際に任意のコードを実行できます。

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
Fixed
Action
For more information visit https://access.redhat.com/errata/RHSA-2026:68699
Workaround
No verified workaround is recorded. Limit untrusted access and use least privilege until authoritative guidance is available.
04

Evidence and provenance

Published 15 Jul 2026 · Last source change 18 Jul 2026, 01:03 UTC · CWE-470 · Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection')

CVE recordCVE.org · 5.2
CVSS sourceCNA
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-2026-44751
Product sourceVendor CSAF · Red Hat Product Security
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD enriched

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
    rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:dc9887746020d299ecaac5d03221a8876b7024eeea79d82e1fb38afd955fb5c0_arm64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:37b64a8df90756aae0ee96d2f07765adbce5ed5beb2414ac3845806ad2219cfc_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaii/vllm-cpu-rhel9@sha256:5da2be9bd0fa0c7344e8a0b84c0cb8f3a78a1c7fc5fc76db6a7daaa2d71324f9_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:94721a151f43ffdfe11b5551ac37cbcf5ff6b991345ca2fc300684cf0a740435_arm64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:97f7af7da4505d0420c49719bed4b49855abb1fa3193d65e5f201d0d501eeee7_amd64 as a component of Red Hat AI Inference Server 3.4
    After
    rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:dc9887746020d299ecaac5d03221a8876b7024eeea79d82e1fb38afd955fb5c0_arm64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:37b64a8df90756aae0ee96d2f07765adbce5ed5beb2414ac3845806ad2219cfc_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaii/vllm-cpu-rhel9@sha256:5da2be9bd0fa0c7344e8a0b84c0cb8f3a78a1c7fc5fc76db6a7daaa2d71324f9_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cpu-rhel9@sha256:81c5994dc20321f8bd3969099eade78ef127cbd79f2d0ccea101c773e4c7fa4d_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:0d22e2301ce26ef68effda5d3a4a20381ad0ea34d1240e159e245bd44c2e125b_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:94721a151f43ffdfe11b5551ac37cbcf5ff6b991345ca2fc300684cf0a740435_arm64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:97f7af7da4505d0420c49719bed4b49855abb1fa3193d65e5f201d0d501eeee7_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:e491c3b169ec77c37dbe0eb9c2b35dd976ca6e968f43b5d72ad5c4095f48d2ed_arm64 as a component of Red Hat AI Inference Server 3.4
    Red Hat Product Security ↗
  2. Vendor guidanceAuthoritative vendor guidance changed from remediation: access.redhat.com/CVE-2026-58659 to remediation: access.redhat.com/CVE-2026-58659.
    Before
    remediation: access.redhat.com/CVE-2026-58659
    After
    remediation: access.redhat.com/CVE-2026-58659
    Red Hat Product Security ↗
  3. Remediation statusRemediation status changed from Awaiting fix to Patch available.
    Before
    Awaiting fix
    After
    Patch available
    Red Hat Product Security ↗
  4. Affected versionsThe structured affected or fixed version information changed.
    Before
    rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaii/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
    After
    rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-automl-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:dc9887746020d299ecaac5d03221a8876b7024eeea79d82e1fb38afd955fb5c0_arm64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:37b64a8df90756aae0ee96d2f07765adbce5ed5beb2414ac3845806ad2219cfc_amd64 as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaii/vllm-cpu-rhel9@sha256:5da2be9bd0fa0c7344e8a0b84c0cb8f3a78a1c7fc5fc76db6a7daaa2d71324f9_amd64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:94721a151f43ffdfe11b5551ac37cbcf5ff6b991345ca2fc300684cf0a740435_arm64 as a component of Red Hat AI Inference Server 3.4; registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:97f7af7da4505d0420c49719bed4b49855abb1fa3193d65e5f201d0d501eeee7_amd64 as a component of Red Hat AI Inference Server 3.4
    Red Hat Product Security ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
CVE published
Fixed release or patch reference recorded
ENISA EUVD · EUVD-2026-44751↗Vendor CSAF · Red Hat Product Security↗CISA Vulnrichment SSVC evidence↗Public exploit reference↗Patch or update reference↗Patch or update reference↗Public exploit reference↗Official CVE record (CNA and ADP data)↗NVD record↗
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-2026-58659 · cve.blacktree.nl