CVE-2024-10714: binary-husky/gpt_academic · Unthrottled Resource Allocation
Affects binary-husky/gpt_academicSource CVE Database V5
Not known to be exploited · CVSS 7.5 High.
Data as of 25 Oct 2026, 19:02 UTC
- EPSS
- 0.6% chance of exploitation in 30 days – higher than 50% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HExploitation evidence
Disclosed: evidence found.
CVE published 20 Mar 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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
| Product | Affected | Fixed in |
|---|---|---|
GitHubbinary-husky/gpt_academicpkg:github/binary-husky/gpt_academicOther threats | Affected
| Fixed in– |
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AI-suggested
To mitigate CVE-2024-10714, organizations should prioritize applying vendor patches once available. In the absence of patches, implement strict input validation on multipart file uploads to reject requests with abnormally long or malformed multipart boundaries. Deploy rate limiting and throttling mechanisms on upload endpoints to prevent resource exhaustion from excessive data processing. Monitoring and alerting on unusual multipart upload activity can help detect exploitation attempts early. Network-level controls such as Web Application Firewalls (WAFs) can be configured to block suspicious multipart requests or limit the size and frequency of uploads. Additionally, consider isolating the vulnerable service behind reverse proxies that can enforce stricter request validation. Regularly update and audit multipart parsing libraries and dependencies to ensure known vulnerabilities are addressed. Finally, conduct penetration testing and resilience assessments to verify the effectiveness of implemented mitigations.
Description
A vulnerability in binary-husky/gpt_academic version 3.83 allows an attacker to cause a Denial of Service (DoS) by adding excessive characters to the end of a multipart boundary during file upload. This results in the server continuously processing each character and displaying warnings, rendering the application inaccessible. The issue occurs when the terminal shows a warning: 'multipart.multipart Consuming a byte '0x2d' in end state'.