HDF5 is a high-performance library and a file format specification that implements the HDF5 data model. If a file is corrupted such that an array datatypes size, the number of elements, and the element size are not in agreement it can trigger an out of bounds read. The array datatype stores the full size of the datatype (dt->shared->size) separately from the number of elements (dt->shared->u.array.nelem) and the element size (dt->shared->parent->shared->size). If any one of these are corrupted so that they dont align with the others (element size * nelem = full size), it can lead to an out of bounds read. Depending on what is corrupted, it can alter the type of out of bounds read triggered. The vulnerability is present only in files that have been maliciously altered, as its generally not possible to independently alter the full size of the datatype, the element count and the element size. As such, this is only present if a malicious actor is altering files, and wont appear in regular usage.
Weakness
The product reads data past the end, or before the beginning, of the intended buffer.
Affected Software
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Hdf5 | Hdfgroup | * | 2.1.0 (excluding) |
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.
- To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.