CVE-2026-7669: sgl-project SGLang · Code Injection
Affects sgl-project SGLangSource CVE Database V5
Not known to be exploited · CVSS 6.3 Medium.
Data as of 30 Oct 2026, 11:52 UTC
- EPSS
- 0.3% chance of exploitation in 30 days – higher than 30% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:XExploitation evidence
Disclosed: evidence found.
CVE published 2 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: evidence found.
Public exploit code: GitHub proofs of concept
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), GitHub proofs of concept, the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| sgl-projectSGLang | Affected
| Fixed in– |
PyPIsgl-project-sglangpkg:pypi/sgl-project-sglangOther threats | Affected
| Fixed in– |
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
Until a patch is released, users should avoid using untrusted or remote tokenizer models with SGLang, especially when relying on the trust_remote_code setting. Monitoring for updates from the vendor or community is recommended to apply any forthcoming fixes.
Description
A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function get_tokenizer of the file python/sglang/srt/utils/hf_transformers_utils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trust_remote_code with the input False as part of Boolean results in code injection. The attack can be executed remotely. A high complexity level is associated with this attack. The exploitability is considered difficult. In get_tokenizer(), when the caller passes trust_remote_code=False and HuggingFace transformers v5 returns a TokenizersBackend instance (the generic fallback for tokenizer classes not in the registry), SGLang silently re-invokes AutoTokenizer.from_pretrained with trust_remote_code=True, overriding the caller's explicit security setting. A model repository containing a malicious tokenizer.py referenced via auto_map in tokenizer_config.json will execute arbitrary Python in the SGLang process during this second call. No log line or warning is emitted. The override affects all current SGLang versions because transformers==5.3.0 is pinned in pyproject.toml. Both tokenizer_mode="auto" and tokenizer_mode="slow" are affected. The exploit is now public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.