CVE-2024-10956
Binary-Husky Gpt Academic 3.83
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-10956 is a high-severity Origin Validation Error (CWE-346) vulnerability in Binary-Husky Gpt Academic. Its CVSS base score is 7.1 (High).
Operationally, ranked at the 27th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and IA-3 (Device Identification and Authentication) — 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-2024-10956 is a Cross-Site WebSocket Hijacking (CSWSH) vulnerability affecting GPT Academy version 3.83 in the binary-husky/gpt_academic GitHub repository. The flaw stems from insufficient WebSocket authentication and lack of origin validation, enabling attackers to hijack existing WebSocket connections between a victim's browser and the server. It carries a CVSS v3.1 base score of 7.1 (AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:H/A:N) and is associated with CWE-346 (Origin Validation Error).
An attacker can exploit this vulnerability without privileges by tricking a victim into visiting a malicious webpage via social engineering or other means requiring user interaction. Once the victim loads the attacker's page, it hijacks the active WebSocket connection to the GPT Academy server, allowing unauthorized actions such as deleting the victim's conversation history without consent. This results in high integrity impact with low confidentiality impact and no availability disruption.
Mitigation details and additional technical analysis are provided in the Huntr advisory at https://huntr.com/bounties/0f8403ad-5f60-4eb9-9f51-8fbd2e41eda4.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7066
Vulnerability Data
GPT Academy version 3.83 in the binary-husky/gpt_academic repository is vulnerable to Cross-Site WebSocket Hijacking (CSWSH). This vulnerability allows an attacker to hijack an existing WebSocket connection between the victim's browser and the server, enabling unauthorized actions such as deleting conversation…
more
history without the victim's consent. The issue arises due to insufficient WebSocket authentication and lack of origin validation.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: gpt
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement directly requires validating the source of data before allowing transmission or receipt.
Device identification and authentication mandates verifying the source before establishing connections.
Session authenticity mechanisms require validation that communications originate from the expected party.
Boundary protection at interfaces enforces checks on the origin of incoming communications.
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.
Network security controls enforce origin validation at network boundaries.
Security of network services includes validating the authenticity of service endpoints.
A.8.26 requires identifying and specifying requirements for resilience against malicious attacks including SQL injections and input validation (items d, j), plus related protections (authentication, segregation, cryptography per 8.24), which can address some but not most origin validation scenarios such as those involving untrusted cross-origin requests or implicit trust in sources.
A.8.27 mandates security-by-design principles (defense-in-depth, least privilege, assume-breach, distrust-external-input, zero-trust verification) plus design reviews that can catch and block origin-validation gaps in many common cases, but leaves a bounded remainder (e.g. protocol-level or third-party component origin errors not surfaced by the organization's review process).
Secure coding practices include implementing proper origin validation to prevent spoofing.
Secure authentication verifies identity but does not address origin validation of arbitrary data flows.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.
- No fine-grained STIG row for CWE-346, a class-level weakness, and none of its children carries one either.