RDS Light is a simplified version of the Reflective Dialogue System (RDS), a self-reflecting AI framework. Versions prior to 1.1.0 contain a vulnerability that involves a lack of input validation within the RDS AI framework, specifically within the user input handling code in the main module (main.py). This leaves the framework open to injection attacks and potential memory tampering. Any user or external actor providing input to the system could exploit this vulnerability to inject malicious commands, corrupt stored data, or affect API calls. This is particularly critical for users employing RDS AI in production environments where it interacts with sensitive systems, performs dynamic memory caching, or retrieves user-specific data for analysis. Impacted areas include developers using the RDS AI system as a backend for AI-driven applications and systems running RDS AI that may be exposed to untrusted environments or receive unverified user inputs. The vulnerability has been patched in version 1.1.0 of the RDS AI framework. All user inputs are now sanitized and validated against a set of rules designed to mitigate malicious content. Users should upgrade to version 1.1.0 or higher and ensure all dependencies are updated to their latest versions. For users unable to upgrade to the patched version, a workaround can be implemented. The user implementing the workaround should implement custom validation checks for user inputs to filter out unsafe characters and patterns (e.g., SQL injection attempts, script injections) and limit or remove features that allow user input until the system can be patched.
Weakness
The product receives input or data, but it does
not validate or incorrectly validates that the input has the
properties that are required to process the data safely and
correctly.
Extended Description
Input validation is a frequently-used technique
for checking potentially dangerous inputs in order to
ensure that the inputs are safe for processing within the
code, or when communicating with other components.
Input can consist of:
Data can be simple or structured. Structured data
can be composed of many nested layers, composed of
combinations of metadata and raw data, with other simple or
structured data.
Many properties of raw data or metadata may need
to be validated upon entry into the code, such
as:
Implied or derived properties of data must often
be calculated or inferred by the code itself. Errors in
deriving properties may be considered a contributing factor
to improper input validation.
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.
- For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
- Even though client-side checks provide minimal benefits with respect to server-side security, they are still useful. First, they can support intrusion detection. If the server receives input that should have been rejected by the client, then it may be an indication of an attack. Second, client-side error-checking can provide helpful feedback to the user about the expectations for valid input. Third, there may be a reduction in server-side processing time for accidental input errors, although this is typically a small savings.
- 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.
References