LiteLLM < 1.83.10 Privilege Escalation via User Update
LiteLLM prior to 1.83.10 allows a user to modify their own user_role via the /user/update endpoint. While the endpoint correctly restricts users to updating only their own account, it does not restrict which fields may be changed. A user who can reach this endpoint can set their role to proxy_admin, gaining full administrative access to LiteLLM including all users, teams, keys, models, and prompt history. Users with the org_admin role have legitimate access to this endpoint and can exploit this vulnerability without chaining any additional flaw.
LiteLLM < 1.83.14 Privilege Escalation via API Key Generation
LiteLLM prior to 1.83.14 allows an authenticated internal_user to create API keys with access to routes that their role does not permit. When generating a key, the allowed_routes field is stored without verifying that the specified routes fall within the user's own permissions. A key created with access to admin-only routes can then be used to reach those routes successfully, bypassing the role-based access controls that would otherwise block the request, enabling full privilege escalation from internal_user to proxy_admin.
Critical · CVSS 9.3EPSS 89.42%In KEVPublic exploitFix available
LiteLLM: SQL injection in Proxy API key verification
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.81.16 to before version 1.83.7, a database query used during proxy API key checks mixed the caller-supplied key value into the query text instead of passing it as a separate parameter. An unauthenticated attacker could send a specially crafted Authorization header to any LLM API route (for example POST /chat/completions) and reach this query through the proxy's error-handling path. An attacker could read data from the proxy's database and may be able to modify it, leading to unauthorised access to the proxy and the credentials it manages. This
LiteLLM: Server-Side Template Injection in /prompts/test endpoint
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.80.5 to before version 1.83.7, the POST /prompts/test endpoint accepted user-supplied prompt templates and rendered them without sandboxing. A crafted template could run arbitrary code inside the LiteLLM Proxy process. The endpoint only checks that the caller presents a valid proxy API key, so any authenticated user could reach it. Depending on how the proxy is deployed, this could expose secrets in the process environment (such as provider API keys or database credentials) and allow commands to be run on the host. This issue has been patched
High · CVSS 8.7EPSS 91.44%In KEVPublic exploitFix available
LiteLLM: Authenticated command execution via MCP stdio test endpoints
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.74.2 to before version 1.83.7, two endpoints used to preview an MCP server before saving it — POST /mcp-rest/test/connection and POST /mcp-rest/test/tools/list — accepted a full server configuration in the request body, including the command, args, and env fields used by the stdio transport. When called with a stdio configuration, the endpoints attempted to connect, which spawned the supplied command as a subprocess on the proxy host with the privileges of the proxy process. The endpoints were gated only by a valid proxy API key, with no role
LiteLLM: Password hash exposure and pass-the-hash authentication bypass
### Impact
Three issues combine into a full authentication bypass chain:
1. Weak hashing: User passwords are stored as unsalted SHA-256 hashes, making them vulnerable to rainbow table attacks and trivially identifying users with identical passwords.
2. Hash exposure: Multiple API endpoints (/user/info, /user/update, /spend/users) return the password hash field in responses to any authenticated user regardless of role. Plaintext passwords could also potentially be exposed in certain scenarios.
4. Pass-the-hash: The /v2/login endpoint accepts the raw SHA-256 hash as a valid password without re-hashing, allowing direct login with a stolen
An
LiteLLM has an authentication bypass via OIDC userinfo cache key collision
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. Prior to 1.83.0, when JWT authentication is enabled (enable_jwt_auth: true), the OIDC userinfo cache uses token[:20] as the cache key. JWT headers produced by the same signing algorithm generate identical first 20 characters. This configuration option is not enabled by default. Most instances are not affected. An unauthenticated attacker can craft a token whose first 20 characters match a legitimate user's cached token. On cache hit, the attacker inherits the legitimate user's identity and permissions. This affects deployments with JWT/OIDC authentication en
High · CVSS 8.7EPSS 38.61%Public exploitFix available
LiteLLM affected by privilege escalation via unrestricted proxy configuration endpoint
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. Prior to 1.83.0, the /config/update endpoint does not enforce admin role authorization. A user who is already authenticated into the platform can then use this endpoint to modify proxy configuration and environment variables, register custom pass-through endpoint handlers pointing to attacker-controlled Python code, achieving remote code execution, read arbitrary server files by setting UI_LOGO_PATH and fetching via /get_image, and take over other privileged accounts by overwriting UI_USERNAME and UI_PASSWORD environment variables. Fixed in v1.83.0.
Two LiteLLM versions published containing credential harvesting malware
After an API Token exposure from an exploited trivy dependency, two new releases of `litellm` were uploaded to PyPI containing automatically activated malware, harvesting sensitive credentials and files, and exfiltrating to a remote API.
Anyone who has installed and run the project should assume any credentials available to litellm environment may have been exposed, and revoke/rotate thema ccordingly.
Two litellm versions published containing credential harvesting malware
After an API Token exposure from an exploited Trivy dependency,
two new releases of `litellm` were uploaded to PyPI containing automatically activated malware,
harvesting sensitive credentials and files, and exfiltrating to a remote API.
The malicious code runs during importing any module from the package and scans
the file system and environment variables, collecting all kinds of
sensitive data, including but not limited to private SSH keys, credentials to Git and
Docker repositories, dotenv files, tokens to Kubernetes service accounts,
databases and LDAP configuration. Also exfiltrated are multiple shell history
files and cryptowallet keys
BerriAI/litellm version 1.40.12 contains a vulnerability that allows remote code execution. The issue exists in the handling of the 'post_call_rules' configuration, where a callback function can be added. The provided value is split at the final '.' mark, with the last part considered the function name and the remaining part appended with the '.py' extension and imported. This allows an attacker to set a system method, such as 'os.system', as a callback, enabling the execution of arbitrary commands when a chat response is processed.
A vulnerability in BerriAI/litellm, as of commit 26c03c9, allows unauthenticated users to cause a Denial of Service (DoS) by exploiting the use of ast.literal_eval to parse user input. This function is not safe and is prone to DoS attacks, which can crash the litellm Python server.
An improper authorization vulnerability exists in the main-latest version of BerriAI/litellm. When a user with the role 'internal_user_viewer' logs into the application, they are provided with an overly privileged API key. This key can be used to access all the admin functionality of the application, including endpoints such as '/users/list' and '/users/get_users'. This vulnerability allows for privilege escalation within the application, enabling any account to become a PROXY ADMIN.
Exposure of Sensitive Information in berriai/litellm
In berriai/litellm version v1.52.1, an issue in proxy_server.py causes the leakage of Langfuse API keys when an error occurs while parsing team settings. This vulnerability exposes sensitive information, including langfuse_secret and langfuse_public_key, which can provide full access to the Langfuse project storing all requests.
Improper Output Neutralization for Logs in berriai/litellm
In berriai/litellm before version 1.44.12, the `litellm/litellm_core_utils/litellm_logging.py` file contains a vulnerability where the API key masking code only masks the first 5 characters of the key. This results in the leakage of almost the entire API key in the logs, exposing a significant amount of the secret key. The issue affects version v1.44.9.
A Denial of Service (DoS) vulnerability exists in berriai/litellm version v1.44.5. This vulnerability can be exploited by appending characters, such as dashes (-), to the end of a multipart boundary in an HTTP request. The server continuously processes each character, leading to excessive resource consumption and rendering the service unavailable. The issue is unauthenticated and does not require any user interaction, impacting all users of the service.
High · CVSS 7.5EPSS 34.38%Public exploitFix available
SSRF in berriai/litellm
A Server-Side Request Forgery (SSRF) vulnerability exists in berriai/litellm version 1.38.10. This vulnerability allows users to specify the `api_base` parameter when making requests to `POST /chat/completions`, causing the application to send the request to the domain specified by `api_base`. This request includes the OpenAI API key. A malicious user can set the `api_base` to their own domain and intercept the OpenAI API key, leading to unauthorized access and potential misuse of the API key.
Improper Access Control in Team Management in berriai/litellm
berriai/litellm version 1.34.34 is vulnerable to improper access control in its team management functionality. This vulnerability allows attackers to perform unauthorized actions such as creating, updating, viewing, deleting, blocking, and unblocking any teams, as well as adding or deleting any member to or from any teams. The vulnerability stems from insufficient access control checks in various team management endpoints, enabling attackers to exploit these functionalities without proper authorization.
BerriAI/litellm version v1.35.8 contains a vulnerability where an attacker can achieve remote code execution. The vulnerability exists in the `add_deployment` function, which decodes and decrypts environment variables from base64 and assigns them to `os.environ`. An attacker can exploit this by sending a malicious payload to the `/config/update` endpoint, which is then processed and executed by the server when the `get_secret` function is triggered. This requires the server to use Google KMS and a database to store a model.