PT-2026-52167

Name of the Vulnerable Software and Affected Versions Drupal AI versions 0.0.0 through 1.2.17 Drupal AI versions 1.3.0 through 1.3.8 Drupal AI versions 1.4.0 through 1.4.3 Description Improper neutralization of input during web page generation allows Cross-Site Scripting XSS. The module and...

GHSA-C969-5X3P-VQ3V PraisonAI: IMAP Command Injection via Unsanitized Email Search Parameters

Summary The email search tool in src/praisonai-agents/praisonaiagents/tools/emailtools.py constructs IMAP SEARCH commands by interpolating LLM-controlled parameters fromaddr, subject, query directly into IMAP protocol strings using f-string formatting with double-quote delimiters. An attacker who...

Malicious code in @catclaw/message-logger-plugin (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector cf070f85ba454a799d80e6998ee717f0fc9084513041893a164752162e0b0864 On plugin registration, the log-collector is enabled by default and uploads session JSONL files from /.openclaw/agents//sessions to...

FunFuzz: An LLM-Powered Evolutionary Fuzzing Framework

Modern fuzzers increasingly use Large Language Models LLMs to generate structured inputs, but LLM-driven fuzzing is sensitive to prompt initialization and sampling variance, which can reduce exploration efficiency and lead to redundant inputs. We present FunFuzz, a multi-island evolutionary fuzzi...

CVE-2026-33654

nanobot is a personal AI assistant. Prior to version 0.1.6, an indirect prompt injection vulnerability exists in the email channel processing module nanobot/channels/email.py, allowing a remote, unauthenticated attacker to execute arbitrary LLM instructions and subsequently, system tools without...

The System Prompt Is the Attack Surface: How LLM Agent Configuration Shapes Security and Creates Exploitable Vulnerabilities

System prompt configuration can make the difference between near-total phishing blindness and near-perfect detection in LLM email agents. We present PhishNChips, a study of 11 models under 10 prompt strategies, showing that prompt-model interaction is a first-order security variable: a single...

Malicious code in chat-prompt-logger (PyPI)

--- -= Per source details. Do not edit below this line.=- Source: kam193 f25a736985f5c0bb50156fdc7de61e976b16416f42c44a2682b5ce718401383b The package provides a logger of LLM prompts that at the same time looks for hidden instructions and executes them. --- Category: MALICIOUS - The campaign has...

CVE-2025-64320

Improper Neutralization of Input Used for LLM Prompting vulnerability in Salesforce Agentforce Vibes Extension allows Code Injection.This issue affects Agentforce Vibes Extension: before 3.2.0...

LLM-Based Dynamic Differential Testing for Database Connectors with Reinforcement Learning-Guided Prompt Selection

Database connectors are critical components enabling applications to interact with underlying database management systems DBMS, yet their security vulnerabilities often remain overlooked. Unlike traditional software defects, connector vulnerabilities exhibit subtle behavioral patterns and are...