CVE Vulnerabilities

CVE-2025-48868

Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')

Published: Sep 24, 2025 | Modified: Sep 29, 2025
CVSS 3.x
N/A
Source:
NVD
CVSS 2.x
RedHat/V2
RedHat/V3
Ubuntu

Horilla is a free and open source Human Resource Management System (HRMS). An authenticated Remote Code Execution (RCE) vulnerability exists in Horilla 1.3.0 due to the unsafe use of Python’s eval() function on a user-controlled query parameter in the project_bulk_archive view. This allows privileged users (e.g., administrators) to execute arbitrary system commands on the server. While having Django’s DEBUG=True makes exploitation visibly easier by returning command output in the HTTP response, this is not required. The vulnerability can still be exploited in DEBUG=False mode by using blind payloads such as a reverse shell, leading to full remote code execution. This issue has been patched in version 1.3.1.

Weakness

The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes code syntax before using the input in a dynamic evaluation call (e.g. “eval”).

Affected Software

Name Vendor Start Version End Version
Horilla Horilla 1.3 (including) 1.3 (including)

Potential Mitigations

  • 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.
  • Inputs should be decoded and canonicalized to the application’s current internal representation before being validated (CWE-180, CWE-181). Make sure that your application does not inadvertently decode the same input twice (CWE-174). Such errors could be used to bypass allowlist schemes by introducing dangerous inputs after they have been checked. Use libraries such as the OWASP ESAPI Canonicalization control.
  • Consider performing repeated canonicalization until your input does not change any more. This will avoid double-decoding and similar scenarios, but it might inadvertently modify inputs that are allowed to contain properly-encoded dangerous content.
  • 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