Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-33024 is a critical-severity SSRF (CWE-918) vulnerability in Wwbn Avideo-Encoder. Its CVSS base score is 9.3 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 36th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — 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-2026-33024 is a Server-Side Request Forgery (SSRF) vulnerability (CWE-918) affecting AVideo, an open-source video-sharing platform. Versions prior to 8.0 are vulnerable in the public thumbnail endpoints getImage.php and getImageMP4.php. These endpoints accept a base64Url GET parameter, base64-decode it, and pass the resulting URL directly to ffmpeg as an input source without authentication. The existing validation only ensured syntactic validity via FILTER_VALIDATE_URL and a http(s):// prefix, which is insufficient to prevent access to internal resources.
The vulnerability is exploitable by unauthenticated remote attackers (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N, score 9.1). An attacker can supply a base64-encoded URL pointing to internal services, such as http://169.254.169.254/latest/meta-data/ for AWS instance metadata, http://192.168.x.x/, or http://127.0.0.1/, causing the server to fetch these resources via ffmpeg. As a blind SSRF, the response is not directly returned to the attacker, but results can be inferred through timing differences or server error logs, potentially enabling network reconnaissance, metadata exfiltration, or further internal pivoting.
The issue has been fixed in AVideo version 8.0. The GitHub security advisory (GHSA-h9gh-866r-6vgq) and fixing commit (f9df098534a0e05fd431e771ac9d70f0f36f1c06) detail the patch, which security practitioners should review for deployment guidance on affected instances.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-13557
Vulnerability Data
AVideo is a video-sharing Platform. Versions prior to 8.0 contain a Server-Side Request Forgery vulnerability (CWE-918) in the public thumbnail endpoints getImage.php and getImageMP4.php. Both endpoints accept a base64Url GET parameter, base64-decode it, and pass the resulting URL to ffmpeg…
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as an input source without any authentication requirement. The prior validation only checked that the URL was syntactically valid (FILTER_VALIDATE_URL) and started with http(s)://. This is insufficient: an attacker can supply URLs such as http://169.254.169.254/latest/meta-data/ (AWS/cloud instance metadata), http://192.168.x.x/, or http://127.0.0.1/ to make the server reach internal network resources. The response is not directly returned (blind), but timing differences and error logs can be used to infer results. The issue has been fixed in version 8.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
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 development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
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.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.