GLiNER Guard: Unified Encoder Family for Production LLM Safety and Privacy

Production LLM systems require both safety moderation and PII detection under strict latency and cost constraints. This creates a trade-off: autoregressive moderators are accurate but expensive, while lightweight encoders are faster but less capable. We present GLiNER Guard GLiGuard, a unified...

SGLang has an Improper Input Validation/Injection Issue

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation results in deserialization. The attack can be executed remotely. A hi...

Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')

Overview sglang is a SGLang is a fast serving framework for large language models and vision language models. Affected versions of this package are vulnerable to Improper Neutralization of Special Elements in Output Used by a Downstream Component 'Injection' via the gettokenizer function in the...

CVE-2026-7669

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trustremotecode with the input False as part of Boole...

EUVD-2026-26802

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation results in deserialization. The attack can be executed remotely. A hi...

CVE-2026-7669 sgl-project SGLang HuggingFace Transformer hf_transformers_utils.py get_tokenizer code injection

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function gettokenizer of the file python/sglang/srt/utils/hftransformersutils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trustremotecode with the input False as part of Boole...

CVE-2026-7669

Affected software: sgl-project SGLang (up to 0.5.9). The vulnerability targets the function get_tokenizer in python/sglang/srt/utils/hf_transformers_utils.py within the HuggingFace Transformer Handler. Root cause is deserialization triggered by input manipulation. Impact is remote execution with ...

PT-2026-36639

Name of the Vulnerable Software and Affected Versions sgl-project SGLang versions prior to 0.6.0 Description A code injection issue exists in the HuggingFace Transformer Handler within the get tokenizer function of the python/sglang/srt/utils/hf transformers utils.py file. When a caller sets the...

fl-manager-components-datasets-torch (=0.1.0), fl-manager-components-formatters-pillow (=0.1.0) +11 more potentially affected by CVE-2026-24178 via nvflare (>=2.2.0 <=2.7.1)

nvflare PYPI version =2.2.0, =0.1.0, =0.2.0, =3.1.27, =3.1.27, =3.1.29, =3.1.31 Source cves: CVE-2026-24178 Source advisory: SNYK:PYTHON-NVFLARE-16318747...

GHSA-RXPQ-XGQX-FR7P InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

Inclusion of Functionality from Untrusted Control Sphere

Overview instructlab is a Core package for interacting with InstructLab Affected versions of this package are vulnerable to Inclusion of Functionality from Untrusted Control Sphere via default trustremotecode=True for loading models from HuggingFacein in linuxtrain.py file. An attacker can execut...

EUVD-2026-24752

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859 Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

CVE-2026-6859 is a Red Hat advisory about a flaw in InstructLab where linux_train.py hardcodes trust_remote_code=True when loading models from HuggingFace. This enables arbitrary Python code execution if a user runs ilab train/download/generate with a malicious HuggingFace model, potentially lead...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859 Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

PT-2026-34336

Name of the Vulnerable Software and Affected Versions InstructLab affected versions not specified Description A flaw exists in the linux train.py script which hardcodes the trust remote code variable as True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary...