Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:LSummary
CVE-2026-30832 is a critical-severity SSRF (CWE-918) vulnerability in Charm Soft Serve. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 26th 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-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-2026-30832 is a server-side request forgery (SSRF) vulnerability, classified under CWE-918, affecting Soft Serve, a self-hostable Git server for the command line. The flaw impacts versions from 0.6.0 up to but not including 0.11.4, where an authenticated SSH user can force the server to issue HTTP requests to internal or private IP addresses. This occurs by executing the repo import command with a crafted --lfs-endpoint URL.
Exploitation requires an authenticated SSH user with repository import privileges. The initial request is a blind batch to a metadata endpoint, which fails to parse as valid LFS JSON. An attacker hosting a fake LFS server can chain this by returning download URLs that redirect to internal targets, enabling full read access to internal services. The vulnerability carries a CVSS v3.1 base score of 9.1 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L), reflecting its high severity from network reachability, low complexity, low privileges, scope change, and predominant confidentiality impact.
The vulnerability has been patched in Soft Serve version 0.11.4. Mitigation involves upgrading to this version or later. Official resources include the patching commit at https://github.com/charmbracelet/soft-serve/commit/3ef660098ab37a7950457da8ecc25b516e37ce4e, release notes at https://github.com/charmbracelet/soft-serve/releases/tag/v0.11.4, and the GitHub security advisory at https://github.com/charmbracelet/soft-serve/security/advisories/GHSA-3fvx-xrxq-8jvv.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10166
Vulnerability Data
Soft Serve is a self-hostable Git server for the command line. From version 0.6.0 to before version 0.11.4, an authenticated SSH user can force the server to make HTTP requests to internal/private IP addresses by running repo import with a…
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crafted --lfs-endpoint URL. The initial batch request is blind (the response from a metadata endpoint won't parse as valid LFS JSON), but an attacker hosting a fake LFS server can chain this into full read access to internal services by returning download URLs that point at internal targets. This issue has been patched in version 0.11.4.
- 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
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.