Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:NSummary
CVE-2023-42450 is a medium-severity HTTP Request/Response Splitting (CWE-113) vulnerability in Joinmastodon Mastodon. Its CVSS base score is 5.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Content Injection (T1659); ranked at the 32th 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-2023-46896
Vulnerability Data
Mastodon is a free, open-source social network server based on ActivityPub. Starting in version 4.2.0-beta1 and prior to version 4.2.0-rc2, by crafting specific input, attackers can inject arbitrary data into HTTP requests issued by Mastodon. This can be used to…
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perform confused deputy attacks if the server configuration includes `ALLOWED_PRIVATE_ADDRESSES` to allow access to local exploitable services. Version 4.2.0-rc2 has a patch for the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.4.2V4.1.3V1.3.6V4.2.3
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 SDLC practices directly require input sanitization and header handling that prevent CRLF injection.
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.
Security testing in development and acceptance can detect CRLF injection flaws before deployment.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.
Secure development lifecycle mandates input validation and output encoding that directly prevents CRLF injection into HTTP headers.
Application security requirements explicitly call for controls against injection flaws including HTTP header manipulation.
Secure architecture principles reduce the likelihood of header-splitting vulnerabilities through proper component isolation.
Secure coding standards require neutralization of CRLF sequences before inclusion in HTTP headers.