Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
-
AccessObtain low-privilege LiteLLM API credentials
-
DeliverySend crafted MCP test request with internal target URL
-
ExploitLiteLLM proxy issues server-side HTTP request to internal destination
-
ExecutionReceive response revealing internal service data or cloud metadata
-
ImpactLeverage metadata to escalate privileges or pivot laterally
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V4 - API and Web Service URL allowlisting, SSRF prevention
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Credential Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | Exploitation requires the attacker to hold a valid authenticated session or API key with at least low-privilege access to the LiteLLM proxy instance (PR:L per CVSS 4.0 vector). The vulnerable endpoint is within an explicitly experimental component ( |
| Impact | Real-world risk is moderate-to-significant despite the reported CVSS 4.0 score of 2.1, which is depressed by the E:P threat metric (proof-of-concept maturity) and low individual CIA impact ratings. The base network vector (AV:N/AC:L/AT:N/PR:L/UI:N) indicates no special attack complexity beyond valid credentials, which is a meaningful threat in environments where LiteLLM is deployed as a shared internal proxy and multiple users or service accounts have API access. SSRF vulnerabilities in AI gateway products are high-value because these servers frequently run with cloud IAM roles, sit inside private network segments, and have connectivity to internal model registries or admin APIs. The EPSS score was not provided - this is a data gap. No CISA KEV listing exists, indicating exploitation has not been confirmed as widespread, but the public PoC lowers the barrier to exploitation. The CVSS 4.0 SC:N rating (no subsequent-system impact) may understate realistic risk: SSRF by definition causes the vulnerable server to interact with other systems, and the N rating likely reflects the conservative NVD/VulDB assessment rather than a definitive architectural constraint. Defenders should treat this as a meaningful lateral-movement enabler in cloud-hosted deployments. |
| Exploit ScenarioDerived | An attacker with a valid low-privilege API key for a shared LiteLLM proxy deployment sends a crafted POST request to the MCP server connection testing endpoint, supplying an internal URL such as |
Get an e-mail when this CVE is exploited, patched or re-scored. Free account.
Alert meAnalysisAIv1 – Jun 22, 2026
Server-side request forgery in BerriAI LiteLLM versions up to 1.82.2 allows authenticated remote attackers to induce the proxy server to make arbitrary outbound HTTP requests by manipulating the MCP (Model Context Protocol) Server Connection Testing endpoint. The vulnerable function _execute_with_mcp_client in the experimental MCP server component fails to validate or restrict user-supplied connection targets, enabling internal network probing, potential access to cloud metadata services, and circumvention of network segmentation controls. A publicly available proof-of-concept exploit exists (GitHub gist by YLChen-007); no CISA KEV listing was present at time of analysis. The CVSS 4.0 reported score of 2.1 reflects threat-metric downgrade from E:P (proof-of-concept) and should not be taken as indicative of low inherent exploitability - the base network vector with low-privilege access represents a meaningful internal network exposure risk.
RemediationAI
No vendor-released patched version was independently confirmed at time of analysis - the affected version range tops out at 1.82.2 with no fix version cited in VulDB, EUVD, or NVD references. Organizations should monitor the BerriAI LiteLLM GitHub repository and official release notes for a patched release above 1.82.2. As an immediate compensating control, operators should disable or restrict access to the experimental MCP server endpoints in litellm/proxy/_experimental/mcp_server/rest_endpoints.py if MCP connection testing is not required; removing or commenting out the route registration for _execute_with_mcp_client eliminates the attack surface entirely at the cost of losing MCP connectivity testing functionality. If disabling is not feasible, restrict API access to the MCP testing endpoint via network ACLs or the LiteLLM proxy's built-in role-based access controls so that only highly trusted accounts can invoke it. Additionally, deploy an egress firewall rule blocking outbound connections from the LiteLLM proxy host to RFC-1918 ranges and cloud metadata IP addresses (e.g., 169.254.169.254, 100.64.0.0/10) to limit SSRF reach; this does not eliminate the vulnerability but meaningfully constrains exploitation impact. References: https://vuldb.com/vuln/372516, https://nvd.nist.gov/vuln/detail/CVE-2026-12774.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
LiteLLM is a Python-based LLM proxy gateway (vendor: BerriAI) used to unify multiple AI provider APIs behind a single endpoint. The affected component is an experimental MCP (Model Context Protocol) server integration within litellm/proxy/_experimental/mcp_server/rest_endpoints.py, specifically the _execute_with_mcp_client function, which is used to test connectivity to MCP-compatible tool servers. CWE-918 (Server-Side Request Forgery) describes the root cause: the application accepts a user-controlled URL or connection parameter and uses it to initiate an outbound network connection from the server without adequately validating the destination. This class of flaw is particularly dangerous in cloud-deployed AI gateway infrastructure where the server typically has access to internal APIs, cloud provider metadata endpoints (e.g., 169.254.169.254), and adjacent microservices not exposed to the public internet. The CPE string cpe:2.3:a:berriai:litellm:*:*:*:*:*:*:*:* confirms the vulnerability applies broadly across the litellm package.
Know when Litellm gets its next vulnerability
- Watch products and get an email when something new is published
- Check this CVE against your own stack and servers
- Exploit and PoC references, threat intelligence from 22 sources
No credit card · 7-day full trial
Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P
Network SSRF requiring low-privilege auth (PR:L); scope changes as server contacts internal systems; limited C/I from internal probing, no meaningful availability impact.
Primary rating from Vendor (VulDB).
CVSS VectorVendor: VulDB
Lifecycle Timeline
2DescriptionCVE.org
A security vulnerability has been detected in BerriAI litellm up to 1.82.2. Affected by this vulnerability is the function _execute_with_mcp_client of the file litellm/proxy/_experimental/mcp_server/rest_endpoints.py of the component MCP Server Connection Testing. The manipulation leads to server-side request forgery. Remote exploitation of the attack is possible. The exploit has been disclosed publicly and may be used. The vendor was contacted early about this disclosure.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Server-Side Request Forgery exploits applications that fetch remote resources based on user-supplied URLs.
Remote command execution in LiteLLM proxy server versions 1.74.2 through 1.83.6 allows any authenticated user to execute
SQL injection in LiteLLM proxy server versions 1.81.16 through 1.83.6 allows unauthenticated remote attackers to read an
Authentication bypass in LiteLLM (BerriAI) proxy/AI Gateway before 1.84.0 lets a remote unauthenticated attacker reach M
BerriAI/litellm is vulnerable to Server-Side Template Injection (SSTI) via the `/completions` endpoint. Rated critical s
Remote code execution in BerriAI LiteLLM (all versions through 2026-04-08) enables authenticated attackers to execute ar
BerriAI's litellm, in its latest version, is vulnerable to arbitrary file deletion due to improper input validation on t
Authentication bypass in the LiteLLM proxy lets any party who already holds a valid JWT issued by the configured externa
In berriai/litellm version v1.52.1, an issue in proxy_server.py causes the leakage of Langfuse API keys when an error oc
In berriai/litellm before version 1.44.12, the `litellm/litellm_core_utils/litellm_logging.py` file contains a vulnerabi
A Server-Side Request Forgery (SSRF) vulnerability exists in berriai/litellm version 1.38.10. Rated high severity (CVSS
An SQL Injection vulnerability exists in the berriai/litellm repository, specifically within the `/global/spend/logs` en
A code injection vulnerability exists in the berriai/litellm application, version 1.34.6, due to the use of unvalidated
EUVD-2026-38140
GHSA-h9c7-cfj6-h8j6
NVD
CVE.org
EPSS
Vulnrichment
VulDB
Exploit-DB