Skip to main content
VulnerabilityPublished Updated

CVE-2024-12387: binary-husky/gpt_academic · Data Amplification

Affects binary-husky/gpt_academicSource CVE Database V5

0

Not known to be exploited · CVSS 6.5 Medium.

Data as of 26 Oct 2026, 17:16 UTC

CVSS 3.0 base score
6.5Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.7% chance of exploitation in 30 days – higher than 54% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 20 Mar 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 26 Oct 2026.

What to do

AI-suggested

  1. Implement strict validation on uploaded compressed files, including limiting maximum decompressed size and depth to prevent zip bombs.
  2. Use safe decompression libraries or sandbox decompression processes to isolate resource consumption.
  3. Monitor memory and CPU usage during file processing to detect and terminate suspicious decompression tasks early.
  4. Enforce authentication and authorization controls to restrict file upload capabilities to trusted users.
  5. Employ rate limiting and anomaly detection on upload endpoints to identify and block abuse patterns.
  6. Regularly update the binary-husky/gpt_academic software and monitor for official patches addressing this vulnerability.
  7. Consider deploying web application firewalls (WAFs) with rules to detect and block zip bomb patterns.
  8. Educate developers and administrators about the risks of handling compressed data and best practices for secure file processing.

Description

A vulnerability in the binary-husky/gpt_academic repository, as of commit git 3890467, allows an attacker to crash the server by uploading a specially crafted zip bomb. The server decompresses the uploaded file and attempts to load it into memory, which can lead to an out-of-memory crash. This issue arises due to improper input validation when handling compressed file uploads.

References

Community reviews

Loading reviews…