Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:LSummary
CVE-2023-33176 is a medium-severity SSRF (CWE-918) vulnerability in Bigbluebutton Bigbluebutton. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 39th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-37359
Vulnerability Data
BigBlueButton is an open source virtual classroom designed to help teachers teach and learners learn. In affected versions are affected by a Server-Side Request Forgery (SSRF) vulnerability. In an `insertDocument` API request the user is able to supply a URL…
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from which the presentation should be downloaded. This URL was being used without having been successfully validated first. An update to the `followRedirect` method in the `PresentationUrlDownloadService` has been made to validate all URLs to be used for presentation download. Two new properties `presentationDownloadSupportedProtocols` and `presentationDownloadBlockedHosts` have also been added to `bigbluebutton.properties` to allow administrators to define what protocols a URL must use and to explicitly define hosts that a presentation cannot be downloaded from. All URLs passed to `insertDocument` must conform to the requirements of the two previously mentioned properties. Additionally, these URLs must resolve to valid addresses, and these addresses must not be local or loopback addresses. There are no workarounds. Users are advised to upgrade to a patched version of BigBlueButton.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.
Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.
Validates server-side URLs and resource references to block SSRF attempts.
Detects server-side request forgery through monitoring of unexpected outbound connections.
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.