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Pytorch CVE-2026-24747

HIGH
Code Injection (CWE-94)
2026-01-27 security-advisories@github.com GHSA-63cw-57p8-fm3p
8.8
CVSS 3.1 · Vendor: github
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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain

  1. Access
    Craft malicious PyTorch checkpoint file
  2. Delivery
    Distribute via network or storage
  3. Exploit
    Victim loads with torch.load weights_only=True
  4. Execution
    Memory corruption occurs
  5. Impact
    Arbitrary code execution achieved

Vulnerability Assessment

Weakness
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Code injection prevention, sandbox exec
MITRE ATT&CK

2 techniques across 2 tactics: Execution, Initial Access

The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up.

Exploitation Conditions

PyTorch versions prior to 2.10.0 with weights_only=True parameter enabled during torch.load() call. Attacker-controlled checkpoint file (.pth) must be loaded by victim application.

Impact

CVSS 8.8 (HIGH). Attack vector: Network. Complexity: Low. Privileges required: None. User interaction: Required. Public exploit/POC available.

Exploit ScenarioDerived

An attacker could exploit this vulnerability to craft a malicious checkpoint file (`.

This Week Schedule remediation this week. Why: HIGH severity (CVSS 7.0-8.9).
Patch available 0.0% exploitation probability (EPSS)

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AnalysisAIv1 – Mar 12, 2026

PyTorch is a Python package that provides tensor computation. [CVSS 8.8 HIGH]

RemediationAI

Monitor vendor advisories for a patch. Restrict network access to the affected service where possible.

Affected Packages

pypi pytorch fix: 2.10.0
pypi torch fix: 2.10.0

Source: OSV (Open Source Vulnerabilities)

Affects your stack

Affects 2 packages in pypi

Checking this CVE against your own stacks and servers is part of the Basic plan and up.

Technical ContextAI · show details

Classified as CWE-94 (Code Injection). Affects Pytorch. PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's weights_only unpickler allows an attacker to craft a malicious checkpoint file (.pth) that, when loaded with torch.load(..., weights_only=True), can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.

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  • Exploit and PoC references, threat intelligence from 22 sources

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Severity by source

Vendor (github) PRIMARY 8.8 HIGH
AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Red Hat 8.8 HIGH

Primary rating from Vendor (github).

CVSS VectorVendor: github

Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Lifecycle Timeline

3
Patch released
Mar 31, 2026 - 21:13 nvd
Patch available
PoC Detected
Jan 30, 2026 - 21:51 vuln.today
Public exploit code
CVE Published
Jan 27, 2026 - 22:15 nvd
HIGH 8.8

DescriptionCVE.org

PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's weights_only unpickler allows an attacker to craft a malicious checkpoint file (.pth) that, when loaded with torch.load(..., weights_only=True), can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.

Blast Radius

ecosystem impact
† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth
  • 211 pypi packages depend on torch (165 direct, 47 indirect)

Ecosystem-wide dependent count for version 2.10.0.

Executive ViewAI

Why It Matters

A critical vulnerability in PyTorch (CVE-2026-24747) with a CVSS score of 8.8 affects organizations using this widely-deployed machine learning library for tensor computation. With public exploits available and no patch currently available, any systems running PyTorch are at immediate risk of compromise, potentially enabling attackers to execute arbitrary code or access sensitive data used in ML pipelines.

Business Impact: High
Compensating Controls

Implement network segmentation to isolate PyTorch-dependent applications; disable PyTorch features not required for operations; apply strict input validation and sanitization on all data fed to PyTorch models; deploy WAF rules to detect exploitation patterns; restrict PyTorch application privileges using OS-level access controls; monitor PyTorch processes for suspicious behavior (unusual resource consumption, file access, network connections); run PyTorch in containerized/sandboxed environments; maintain offline backups of critical ML models; restrict API access to PyTorch services to trusted internal networks only.

Threat Intelligence Overview

EPSS Score
0.0%
Top 87% exploitable
Exploit
POC
Public exploit code exists
Data Quality
6 sources
Confidence: High
NVD CVE.org EPSS Vendor GitHub VulDB

How this decision was reached

The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.

SignalValue
Severity HIGH
CISA KEV No
Public POC Yes
EPSS 0.0%
Patch available Yes
Active threat No
Deciding rule
HIGH severity (CVSS 7.0-8.9)
What every action level means
Emergency Immediate action required. Criteria: CRITICAL + in CISA KEV (actively exploited) without patch, OR CRITICAL + EPSS > 30% without patch, OR CRITICAL + active threat signals without patch.
Act Now Prioritize within 24-48h. Criteria: in KEV with patch available, OR CRITICAL + public POC, OR HIGH + EPSS > 10%, OR CRITICAL + active threat, OR any CRITICAL severity.
This Week Schedule remediation this week. Criteria: HIGH severity (CVSS 7.0-8.9). Patch within normal change window.
This Month Plan within 30 days. Criteria: MEDIUM severity (CVSS 4.0-6.9), lower exploitation probability. Include in regular patch cycle.
Monitor Track and reassess. Criteria: LOW severity (CVSS 0.1-3.9), minimal exploitation risk. No immediate action needed.

SSVC AssessmentENISA

SSVC Decision· derived
Scheduled
Exploitation· derived
Poc
System Exposure· derived
Open
Automatable· derived
No
Human Impact
High

Priority Score

64
Low Medium High Critical
KEV: 0
EPSS: 0
CVSS: +44
PoC: +20
Weaponized: 0
Threat intel: 0
Gov advisory: 0

Attack Technique

Code Injection CRITICAL

Code injection occurs when an application accepts user input and passes it directly into a language interpreter or evaluator without proper sanitization.

Remote Code Execution represents the critical moment when an attacker successfully runs arbitrary code on a target system without physical access.

Affected Products (CPE)CVE.org

cpe:2.3:a:linuxfoundation:pytorch:*:*:*:*:*:python:*:*
CVE-2023-43654 CRITICAL POC
9.8 Sep 28

TorchServe is a tool for serving and scaling PyTorch models in production. Rated critical severity (CVSS 9.8), this vuln

CVE-2024-48063 CRITICAL POC
9.8 Oct 29

In PyTorch <=2.4.1, the RemoteModule has Deserialization RCE. Rated critical severity (CVSS 9.8), this vulnerability is

CVE-2025-1945 CRITICAL POC
9.8 Mar 10

PickleScan before 0.0.23 can be bypassed by flipping specific ZIP file header flag bits, allowing malicious pickle files

CVE-2022-45907 CRITICAL POC
9.8 Nov 26

In PyTorch before trunk/89695, torch.jit.annotations.parse_type_line can cause arbitrary code execution because eval is

CVE-2024-8020 HIGH POC
7.5 Mar 20

A vulnerability in lightning-ai/pytorch-lightning version 2.3.2 allows an attacker to cause a denial of service by sendi

CVE-2026-65918 HIGH POC
7.1 Jul 23

Out-of-bounds heap read in PyTorch torchvision's native GIF decoder (versions through 0.28.0) lets attackers who supply

CVE-2025-1944 MEDIUM POC
6.5 Mar 10

picklescan before 0.0.23 is vulnerable to a ZIP archive manipulation attack that causes it to crash when attempting to e

CVE-2024-35198 CRITICAL
9.8 Jul 19

TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. Rated critical sever

CVE-2025-32434 CRITICAL POC
9.3 Apr 18

PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built

CVE-2025-33244 CRITICAL
9.0 Mar 24

NVIDIA APEX for Linux contains a deserialization of untrusted data vulnerability that affects environments using PyTorch

CVE-2025-2953 MEDIUM POC
4.8 Mar 30

A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Rated medium severity (CVSS

CVE-2025-3136 MEDIUM POC
4.8 Apr 03

A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0.cuda.memory.caching_allocator_dele

Vendor StatusVendor

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