GHSA-53gh-p8jc-7rg8 CVE-2024-6825 PYSEC-2026-1541
LiteLLM Vulnerable to Remote Code Execution (RCE)
High
PyPI
- Severity
- 8.8 / 10
- High · CVSS 3.0
- Exploit chance (EPSS)
- 1.65%
- Chance of exploitation in the next 30 days. Higher than 76.51% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-77 Improper Neutralization of Special Elements used in a Command ('Command Injection')
- CWE-94 Improper Control of Generation of Code ('Code Injection')
- Fix
- None yet
- No fixed version published
Description
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.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| litellm | >= 1.40.3.dev2, <= 1.40.12 |
No fix yet |
| litellm | >= 1.40.3.dev2, <= 1.40.12 |
No fix yet |
How to fix
No fixed version has been published yet. Until one is, remove or replace the package, or turn off or isolate the affected feature. This page updates when a fix ships.
Severity breakdown
CVSS 3.0 8.8
CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- Low
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Weakness
CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection')
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.
How to prevent it
- Architecture and Design: If at all possible, use library calls rather than external processes to recreate the desired functionality.
- Implementation: If possible, ensure that all external commands called from the program are statically created.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- Operation: Run time: Run time policy enforcement may be used in an allowlist fashion to prevent use of any non-sanctioned commands.
- System Configuration: Assign permissions that prevent the user from accessing/opening privileged files.
CWE-94: Improper Control of Generation of Code ('Code Injection')
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
How to prevent it
- Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
- Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
- Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-7488-6r32-c95q LiteLLM: MCP Authentication Bypass via OAuth2 Passthrough Fallback | High Known exploited | Also affects litellm |
| GHSA-v4p8-mg3p-g94g LiteLLM: Authenticated command execution via MCP stdio test endpoints | High Known exploited | Also affects litellm |
| GHSA-r75f-5x8p-qvmc LiteLLM has SQL Injection in Proxy API key verification | Critical Known exploited | Also affects litellm |
| GHSA-g5ff-637f-6q2m LiteLLM: internal_user_viewer arbitrary local file read via `vertex_ai_credentials` | High | Also affects litellm |
| GHSA-hhww-mrg2-969h LiteLLM vulnerable to reflected XSS in /sso/debug/callback | Medium | Also affects litellm |
| GHSA-7hp6-4w63-5g45 LiteLLM: Privilege Escalation to Proxy Admin via Cross-Domain Reuse of the Salt Key | Critical | Also affects litellm |
| GHSA-hx8v-g79f-8w5f LiteLLM Proxy has server-side request forgery via the `user_config` request parameter | Medium | Also affects litellm |
| GHSA-3cv6-jpf6-8222 LiteLLM: Authenticated SSRF and provider-credential exfiltration via unvalidated request-body routing parameters | Medium | Also affects litellm |
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