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CVE-2025-54952VulnerabilityPublished

CVE-2025-54952: Meta Platforms ExecuTorch · Integer Overflow to Buffer Overflow

Affects Meta Platforms ExecuTorchSource CVE Database V5

0

Not known to be exploited · CVSS 9.8 Critical.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
9.8Critical
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.6% chance of exploitation in 30 days – higher than 49% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 7 Aug 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

What to do

Affected software

ProductAffectedFixed in
Meta Platforms, Inc ExecuTorchAffected
  • =0
Fixed in–

AI-suggested

1. Immediate assessment of ExecuTorch usage: Identify all instances and versions of ExecuTorch deployed within the organization. 2. Apply updates: Although no patches are currently listed, monitor Meta Platforms' official channels for security updates or commits addressing this vulnerability and apply them promptly. 3. Input validation and model source control: Restrict loading of ExecuTorch models to trusted, verified sources only. Implement strict validation and integrity checks on model files before loading to detect malformed or malicious inputs. 4. Network segmentation: Isolate ExecuTorch environments from untrusted networks to reduce exposure to remote attacks. 5. Runtime protections: Employ memory protection mechanisms such as Address Space Layout Randomization (ASLR), Data Execution Prevention (DEP), and control flow integrity to mitigate exploitation impact. 6. Monitoring and detection: Deploy anomaly detection and logging around ExecuTorch model loading activities to identify suspicious behavior indicative of exploitation attempts. 7. Incident response readiness: Prepare playbooks for rapid containment and remediation if exploitation is suspected. 8. Engage with Meta Platforms' security advisories and community forums for updates and shared mitigation strategies.

Description

An integer overflow vulnerability in the loading of ExecuTorch models can cause smaller-than-expected memory regions to be allocated, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit 8f062d3f661e20bb19b24b767b9a9a46e8359f2b.

References

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