Server-side Request Forgery (SSRF)

Overview ragas is an Evaluation framework for RAG and LLM applications Affected versions of this package are vulnerable to Server-side Request Forgery SSRF via improper validation of URLs in the retrievedcontexts parameter when processing multimodal inputs. An attacker can access arbitrary files,...

GHSA-V2XR-WVRV-P969 RAGAS has an Arbitrary File Read vulnerability

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

EUVD-2025-208315

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

RAGAS has an Arbitrary File Read vulnerability

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

CVE-2025-45691

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

CVE-2025-45691

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

CVE-2025-45691

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

PT-2026-23468

Name of the Vulnerable Software and Affected Versions Exploding Gradients RAGAS versions 0.2.3 through 0.2.14 Description An arbitrary file read issue exists in the ImageTextPromptValue class. This is due to insufficient validation and sanitization of URLs provided in the retrieved contexts...

CVE-2025-45691

An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrievedcontexts parameter when handling multimodal inputs...

CVE-2025-45691

An Arbitrary File Read vulnerability affects Exploding Gradients RAGAS, versions v0.2.3 through v0.2.14, in the ImageTextPromptValue class. The flaw arises from improper validation/sanitization of URLs supplied in the retrieved_contexts parameter when handling multimodal inputs, enabling potentia...

CVE-2025-62372 vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether...

CVE-2025-62372 vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether...

CVE-2025-62372

CVE-2025-62372 affects vLLM (inference/serving engine). From version 0.5.5 up to before 0.11.1, passing multimodal embedding inputs with correct ndim but incorrect shape (e.g., wrong hidden dimension) can crash the engine when serving multimodal models, regardless of whether those inputs are supp...

vLLM 输入验证错误漏洞

vLLM is a high throughput and memory efficient inference and service engine for LLM from the vLLM open source. An input validation error vulnerability exists in vLLM versions 0.5.5 through prior to 0.11.1, which stems from improper handling of multimodal embedded inputs and could cause the engine...

Improper Validation of Array Index

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Improper Validation of Array Index via the MultiModalDataParser input processor. An attacker can cause the engine to crash by submitting multimodal...

PT-2025-47649

Name of the Vulnerable Software and Affected Versions vLLM versions 0.5.5 through 0.11.0 Description vLLM is an inference and serving engine for large language models LLMs. Users can cause the vLLM engine to crash when serving multimodal models by providing multimodal embedding inputs with a...

A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?

Recently, AI-driven interactions with computing devices have advanced from basic prototype tools to sophisticated, LLM-based systems that emulate human-like operations in graphical user interfaces. We are now witnessing the emergence of \emphComputer-Using Agents CUAs, capable of autonomously...