CVE-2026-0762 is a critical deserialization of untrusted data vulnerability in GPT Academic's stream_daas function, affecting binary_husky gpt_academic. This flaw allows remote attackers to achieve arbitrary code execution as root by interacting with a malicious DAAS server. Rated 8.1 HIGH on CVSS, the attack requires high complexity due to the need for a malicious server interaction, but successful exploitation leads to full compromise of confidentiality, integrity, and availability. Currently, there is no public exploit code, Metasploit modules, or significant community discussion, and it is not listed in CISA's KEV catalog, suggesting it is not actively exploited in the wild.
| Vendor | Product | Version(s) | CPE |
|---|---|---|---|
3.91CPE matchmatch criteria | cpe:2.3:a:binary-husky:gpt_academic:3.91:*:*:*:*:*:*:* |
CVSS version used by this source: 3.0
CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
The average CVE in this peer group has 0.0 Twitter, 0.1 Reddit, 0.1 Bluesky, 0.0 Mastodon, and 0.2 GitHub mentions.
No media coverage found for this CVE.
The average CVE in this peer group has 0.1 InfoSec Media, 0.0 Vendor Blog, and 0.0 Security Researcher mentions.
Remediation records are not available for this CVE.