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CVE-2026-31253: flash-attention contains an insecure deserialization vulnerability in its checkpoint loading mechanism

May 11, 2026 (updated May 18, 2026)

The flash-attention training framework thru commit e724e2588cbe754beb97cf7c011b5e7e34119e62 (2025-13-04) contains an insecure deserialization vulnerability (CWE-502) in its checkpoint loading mechanism. The load_checkpoint() function in checkpoint.py and the checkpoint loading code in eval.py use torch.load() without enabling the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted checkpoint file. When a victim loads this checkpoint during model warmstarting or evaluation, arbitrary code is executed on the victim’s system.

References

  • github.com/Dao-AILab/flash-attention
  • github.com/advisories/GHSA-7g5w-pq96-8c5w
  • nvd.nist.gov/vuln/detail/CVE-2026-31253
  • www.notion.so/CVE-2026-31253-35d1e1393188813f9e77e2038104bc49

Code Behaviors & Features

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Affected versions

All versions up to 2.8.3

Solution

Unfortunately, there is no solution available yet.

Impact 7.3 HIGH

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L

Learn more about CVSS

Weakness

  • CWE-94: Improper Control of Generation of Code ('Code Injection')

Source file

pypi/flash_attn/CVE-2026-31253.yml

Spotted a mistake? Edit the file on GitLab.

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