CVE-2025-49133

Libtpms is a library that targets the integration of TPM functionality into hypervisors, primarily into Qemu. Libtpms, which is derived from the TPM 2.0 reference implementation code published by the Trusted Computing Group, is prone to a potential out of bounds (OOB) read vulnerability. The vulnerability occurs in the ‘CryptHmacSign’ function with an inconsistent pairing of the signKey and signScheme parameters, where the signKey is ALG_KEYEDHASH key and inScheme is an ECC or RSA scheme. The reported vulnerability is in the ‘CryptHmacSign’ function, which is defined in the Part 4: Supporting Routines – Code document, section 7.151 - /tpm/src/crypt/CryptUtil.c . This vulnerability can be triggered from user-mode applications by sending malicious commands to a TPM 2.0/vTPM (swtpm) whose firmware is based on an affected TCG reference implementation. The effect on libtpms is that it will cause an abort due to the detection of the out-of-bounds access, thus for example making a vTPM (swtpm) unavailable to a VM. This vulnerability is fixed in 0.7.12, 0.8.10, 0.9.7, and 0.10.1.

Weakness

The product reads data past the end, or before the beginning, of the intended buffer.

Affected Software

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.

Related Attack Patterns

• https://cwe.mitre.org/data/definitions/540.html

References

• https://github.com/stefanberger/libtpms/commit/04b2d8e9afc0a9b6bffe562a23e58c0de11532d1
• https://github.com/stefanberger/libtpms/security/advisories/GHSA-25w5-6fjj-hf8g
• https://trustedcomputinggroup.org/resource/tpm-library-specification
• https://trustedcomputinggroup.org/wp-content/uploads/TPM-2.0-1.83-Part-4-Supporting-Routines-Code.pdf