TensorRT-LLM: Deserialization of Untrusted Data
CVE-2025-33255 is a critical-severity deserialization of untrusted data vulnerability in TensorRT-LLM from NVIDIA, with a CVSS 3.1 base score of 9.8 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. The record lists version v1.2 as the first without the flaw, so updating TensorRT-LLM to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.57% chance of exploitation within 30 days, which is low compared with other CVEs.
Critical severity: a successful attack would have severe impact.
What to do
- Update TensorRT-LLM to v1.2 or a later version.
- Read the advisory on nvidia.custhelp.com for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| NVIDIA | TensorRT-LLM | before v1.2 | v1.2 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H. Scored by NVD.
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 3.1 | 7.5 | High | CNA (nvidia.com) |
| CVSS 3.1 | 9.8 | Critical | NVD |
Official description
NVIDIA TRT-LLM for any platform contains a vulnerability in MPI server, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How developers prevent this class of flaw
- If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Explicitly define a final object() to prevent deserialization.
More Deserialization of Untrusted Data vulnerabilities (CWE-502)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Third-party and government advisories
- nvd.nist.gov/vuln/detail/CVE-2025-33255Third Party Advisory, US Government Resource
- cve.org/CVERecord?id=CVE-2025-33255Third Party Advisory, VDB Entry
Other vulnerabilities in TensorRT-LLM
- 7.1 High severity
- 8.4 High severity
- 7.1 High severity
- 7.4 High severity
- 7.8 High severity
- 7.5 High severity
Recent Deserialization of Untrusted Data vulnerabilities
- 7.8 High severity
- 9.8 Critical severity
- 9.8 Critical severity
- 9.8 Critical severity
- 8.7 High severity
- 8.8 High severity
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