CVE-2026-24779 is a high-severity (CVSS 7.1) Server-Side Request Forgery (SSRF) vulnerability in vllm. A fix is available for vllm — see the affected versions and patch details below.
vLLM vulnerable to Server-Side Request Forgery (SSRF) in `MediaConnector`
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
Exploitation and automatability from CISA’s SSVC triage for CVE-2026-24779.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
CVE-2026-24779 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 378,156 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
vllmReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class within the vLLM project's multimodal feature set. The load_from_url and load_from_url_async methods obtain and process media from URLs provided by users, using different Python parsing libraries when restricting the target host. These two parsing libraries have different interpretations of backslashes, which allows the host name restriction to be bypassed. This allows an attacker to coerce the vLLM server into making arbitrary requests to internal network resources.
This vulnerability is particularly critical in containerized environments like llm-d, where a compromised vLLM pod could be used to scan the internal network, interact with other pods, and potentially cause Denial of Service or access sensitive data. For example, an attacker could make the vLLM pod send malicious requests to an internal llm-d management endpoint, leading to system instability by falsely reporting metrics like the KV cache state.
Details
The core of the vulnerability lies in the MediaConnector.load_from_url method and its asynchronous counterpart. These methods accept a URL string to fetch media content (images, audio, video).
def load_from_url( self, url: str, media_io: MediaIO[_M], *, fetch_timeout: int | None = None, ) -> _M: # type: ignore[type-var] url_spec = urlparse(url) if url_spec.scheme.startswith("http"): self._assert_url_in_allowed_media_domains(url_spec) connection = self.connection data = connection.get_bytes( url, timeout=fetch_timeout, allow_redirects=envs.VLLM_MEDIA_URL_ALLOW_REDIRECTS, ) return media_io.load_bytes(data)
The URL validation uses the urlparse function from Python's urllib module, while the request is made using the request function from Python's requests module. The requests module's underlying URL parsing is implemented using the parse_url function from Python's urllib3. These two parsing functions follow different URL specifications; one is implemented according to the RFC 3986 specification, and the other is implemented according to the WHATWG Living Standard. There is a difference in how the two functions handle backslashes (\) in URLs, which allows the hostname restriction to be bypassed.
Fix
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | vllm | all versions | 0.14.1pip install --upgrade 'vllm==0.14.1' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for vllm, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update vllm to 0.14.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-24779 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2026-24779 can be triaged on real exposure rather than presence alone.
Tailored to CVE-2026-24779. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Fixing This On Your OS
If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.
This IMPORTANT Server-Side Request Forgery (SSRF) vulnerability in vLLM's `MediaConnector` allows an attacker to bypass host restrictions when processing user-provided URLs. This enables the vLLM server to be coerced into making arbitrary requests to internal network resources. This is critical in containerized…
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat AI Inference Server 3.2 | rhaiis/vllm-cuda-rhel9:1772160593 | RHSA-2026:3461 |
| Red Hat AI Inference Server 3.2 | rhaiis/vllm-rocm-rhel9:1772160625 | RHSA-2026:3462 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-spyre-rhel9:1782352919 | RHSA-2026:30087 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-rocm-rhel9:1782353093 | RHSA-2026:30088 |
| Red Hat AI Inference Server 3.3 | rhaiis/vllm-cuda-rhel9:1782352847 | RHSA-2026:30089 |
| Red Hat OpenShift AI 2.25 | rhoai/odh-vllm-cpu-rhel9:1776259063 | RHSA-2026:10184 |
| Red Hat OpenShift AI 2.25 | rhoai/odh-vllm-gaudi-rhel9:1772093278 | RHSA-2026:3782 |
| Red Hat OpenShift AI 2.25 | rhoai/odh-vllm-cuda-rhel9:1783998774 | RHSA-2026:42644 |
Frequently Asked Questions
Is CVE-2026-24779 in your dependencies?
O3 Security finds CVE-2026-24779 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.