fast-xml-parser allows users to process XML from JS object without C/C++ based libraries or callbacks. From version 4.0.0-beta.3 to before version 5.5.7, the DocTypeReader in fast-xml-parser uses JavaScript truthy checks to evaluate maxEntityCount and maxEntitySize configuration limits. When a developer explicitly sets either limit to 0 — intending to disallow all entities or restrict entity size to zero bytes — the falsy nature of 0 in JavaScript causes the guard conditions to short-circuit, completely bypassing the limits. An attacker who can supply XML input to such an application can trigger unbounded entity expansion, leading to memory exhaustion and denial of service. This issue has been patched in version 5.5.7.
Weakness
The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.
Affected Software
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Fast-xml-parser | Naturalintelligence | 4.0.1 (including) | 4.5.5 (excluding) |
| Fast-xml-parser | Naturalintelligence | 5.0.0 (including) | 5.5.7 (excluding) |
| Fast-xml-parser | Naturalintelligence | 4.0.0 (including) | 4.0.0 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta3 (including) | 4.0.0-beta3 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta4 (including) | 4.0.0-beta4 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta5 (including) | 4.0.0-beta5 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta6 (including) | 4.0.0-beta6 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta7 (including) | 4.0.0-beta7 (including) |
| Fast-xml-parser | Naturalintelligence | 4.0.0-beta8 (including) | 4.0.0-beta8 (including) |
| Red Hat Developer Hub 1.10 | RedHat | rhdh/rhdh-hub-rhel9:1780930740 | * |
Extended Description
Specified quantities include size, length, frequency, price, rate, number of operations, time, and others. Code may rely on specified quantities to allocate resources, perform calculations, control iteration, etc.
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.