InternLM LMDeploy through 0.17.0 contains a reachable assertion vulnerability in the DistServe decode migration loop that allows unauthenticated attackers to terminate the inference engine. Attackers can submit a migration_request with an empty remote_block_ids list to trigger an AssertionError that crashes the engine loop and causes subsequent inference requests to fail.
Attack Parameters
Attack Vector
Network
Can be exploited remotely
Attack Complexity
Low
Easy to exploit
Attack Requirements
None
No additional conditions
Privileges Required
None
No privileges needed
User Interaction
None
No user interaction needed
Impact Assessment
Confidentiality
None
No data leak
Integrity
None
No data modification
Availability
High
Complete denial of service
CVSS Vector v4.0
Weakness Type (CWE)
Vulnerable Products 1
| Configuration | From (including) | Up to (excluding) |
|---|---|---|
|
Internlm Lmdeploy
cpe:2.3:a:internlm:lmdeploy:*:*:*:*:*:*:*:*
|
— |
<= 0.17.0
|
References 6
https://github.com/InternLM/lmdeploy/issues/4965
GitHub Issue #4965
https://github.com/InternLM/lmdeploy/blob/v0.17.0/lmdeploy/pytorch/engine/engin…
NVD
https://github.com/InternLM/lmdeploy/blob/v0.17.0/lmdeploy/serve/openai/endpoin…
NVD
https://github.com/InternLM/lmdeploy/blob/v0.17.0/lmdeploy/pytorch/utils.py#L18…
NVD
https://github.com/InternLM/lmdeploy
NVD
https://www.vulncheck.com/advisories/internlm-lmdeploy-through-0.17.0-assertion…
VulnCheck Advisory: InternLM LMDeploy through 0.17.0 Assertion Denial of Service