CVE-2024-10819
CSRF in Binary-Husky Gpt Academic 3.83
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2024-10819 is a high-severity CSRF (CWE-352) vulnerability in Binary-Husky Gpt Academic. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 13th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and SC-23 (Session Authenticity) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-10819 is a Cross-Site Request Forgery (CSRF) vulnerability, classified under CWE-352, affecting version 3.83 of binary-husky/gpt_academic. The flaw allows an attacker to trick an authenticated user into uploading files without their consent by exploiting the user's active session. This enables unauthorized file uploads that can contain malicious scripts, leading to stored Cross-Site Scripting (XSS) attacks and potential system compromise.
The vulnerability can be exploited by any network-based attacker (AV:N) with no required privileges (PR:N), though it requires user interaction (UI:R) such as clicking a malicious link. Successful attacks result in unauthorized file uploads, stored XSS payloads that steal victim information, and the ability to perform arbitrary actions on the victim's behalf within the application context. The CVSS v3.1 base score is 8.8 (AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H), indicating high confidentiality, integrity, and availability impacts.
Mitigation details are available in the advisory published on Huntr at https://huntr.com/bounties/45270c4b-a500-4374-a90b-37b604a3ace0. The CVE was published on 2025-03-20T10:15:20.010.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7095
Vulnerability Data
A Cross-Site Request Forgery (CSRF) vulnerability in version 3.83 of binary-husky/gpt_academic allows an attacker to trick a user into uploading files without their consent, exploiting their session. This can lead to unauthorized file uploads and potential system compromise. The uploaded…
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file can contain malicious scripts, leading to stored Cross-Site Scripting (XSS) attacks. Through stored XSS, an attacker can steal information about the victim and perform any action on their behalf.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.3.2V3.5.1V10.2.1
Mitigating Controls (NIST 800-53 r5) AI
Access enforcement requires verifying that state-changing requests originate from the authenticated user rather than a forged cross-site source.
Protecting session authenticity prevents attackers from replaying or forging authenticated requests via the victim's browser.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly require anti-CSRF controls such as tokens or SameSite attributes.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
By denying access to phishing or malicious sites, the control lowers the likelihood that a user will be tricked into submitting a forged request that performs an unintended action on another site.
Contextual intelligence about emerging CSRF toolkits can be translated into updated anti-CSRF token or same-site policy configurations across applications.