CVE-2025-54131: Improper Neutralization of Special Elements used in a Command

Cursor is a code editor built for programming with AI. In versions below 1.3, an attacker can bypass the allow list in auto-run mode with a backtick or $cmd. If a user has swapped Cursor from its default settings requiring approval for every terminal call to an allowlist, an attacker can execute...

CVE-2025-54132: Server-Side Request Forgery (SSRF)

Cursor is a code editor built for programming with AI. In versions below 1.3, Mermaid which is used to render diagrams allows embedding images which then get rendered by Cursor in the chat box. An attacker can use this to exfiltrate sensitive information to a third-party attacker controlled serve...

Browser Extensions Can Exploit ChatGPT, Gemini in ‘Man in the Prompt’ Attack

Man in the Prompt attack shows how browser extensions can exploit ChatGPT, Gemini and other AI tools to steal data or inject hidden prompts...

CVE-2025-43252

This issue was addressed by adding an additional prompt for user consent. This issue is fixed in macOS Sequoia 15.6. A website may be able to access sensitive user data when resolving symlinks...

CVE-2025-43184

This issue was addressed by adding an additional prompt for user consent. This issue is fixed in macOS Sonoma 14.7.7, macOS Ventura 13.7.7, macOS Sequoia 15.4. A shortcut may be able to bypass sensitive Shortcuts app settings...

SAEL: Leveraging Large Language Models with Adaptive Mixture-Of-Experts for Smart Contract Vulnerability Detection

With the increasing security issues in blockchain, smart contract vulnerability detection has become a research focus. Existing vulnerability detection methods have their limitations: 1 Static analysis methods struggle with complex scenarios. 2 Methods based on specialized pre-trained models...

CVE-2025-43252

This issue was addressed by adding an additional prompt for user consent. This issue is fixed in macOS Sequoia 15.6. A website may be able to access sensitive user data when resolving symlinks...

CVE-2025-46059

langchain-ai v0.3.51 was discovered to contain an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the application via a crafted email message. NOTE: this is disputed by the Supplier because the...

CVE-2025-46059

langchain-ai v0.3.51 was discovered to contain an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the application via a crafted email message. NOTE: this is disputed by the Supplier because the...

Why React Didn't Kill XSS: The New JavaScript Injection Playbook

React conquered XSS? Think again. That's the reality facing JavaScript developers in 2025, where attackers have quietly evolved their injection techniques to exploit everything from prototype pollution to AI-generated code, bypassing the very frameworks designed to keep applications secure. Full...

How Microsoft defends against indirect prompt injection attacks

Summary The growing adoption of large language models LLMs in enterprise workflows has introduced a new class of adversarial techniques: indirect prompt injection. Indirect prompt injection can be used against systems that leverage large language models LLMs to process untrusted data...

Invisible Injections: Exploiting Vision-Language Models through Steganographic Prompt Embedding

Vision-language models VLMs have revolutionized multimodal AI applications but introduce novel security vulnerabilities that remain largely unexplored. We present the first comprehensive study of steganographic prompt injection attacks against VLMs, where malicious instructions are invisibly...

Prompt Optimization and Evaluation for LLM Automated Red Teaming

Applications that use Large Language Models LLMs are becoming widespread, making the identification of system vulnerabilities increasingly important. Automated Red Teaming accelerates this effort by using an LLM to generate and execute attacks against target systems. Attack generators are evaluat...

LangChain 安全漏洞

LangChain is a LangChain open source framework for developing applications powered by the Large Language Model LLM. A security vulnerability exists in LangChain version v0.3.51, which stems from an indirect prompt injection in the GmailToolkit component that could lead to the execution of arbitra...

CVE-2025-46059: Improper Control of Generation of Code

langchain-ai v0.3.51 was discovered to contain an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the application via a crafted email message. NOTE: this is disputed by the Supplier because the...

PT-2025-31216 · Unknown · Langchain-Ai +1

Name of the Vulnerable Software and Affected Versions: langchain-ai version 0.3.51 Description: langchain-ai version 0.3.51 contains an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the applicati...

CVE-2025-46059

The langchain-ai library (v0.3.51) contains an indirect prompt injection vulnerability within the GmailToolkit component. Attackers can exploit this by sending a crafted email message , potentially leading to arbitrary code execution and application compromise. While the supplier disputes the cod...

Hacker Added Prompt to Amazon Q to Erase Files and Cloud Data

A hacker injected a malicious prompt into Amazon Q via GitHub, aiming to delete user files and wipe AWS data, exposing a major security flaw...

Running in CIRCLE? A Simple Benchmark for LLM Code Interpreter Security

As large language models LLMs increasingly integrate native code interpreters, they enable powerful real-time execution capabilities, substantially expanding their utility. However, such integrations introduce potential system-level cybersecurity threats, fundamentally different from prompt-based...

When LLMs Copy to Think: Uncovering Copy-Guided Attacks in Reasoning LLMs

Large Language Models LLMs have become integral to automated code analysis, enabling tasks such as vulnerability detection and code comprehension. However, their integration introduces novel attack surfaces. In this paper, we identify and investigate a new class of prompt-based attacks, termed...