LLM Security Under Threat: CVE Exploits, REC Attacks & Why Your AI Stack Isn’t Safe

Описание: https://penligent.ai/
Large language models are transforming modern applications — but they are not inherently safe. Real-world incidents have already proven that LLMs can be exploited through prompt injection, data leakage, policy bypass, and unauthorized tool execution.

The danger is bigger than the model itself. Once connected to plugins, agents, and automation workflows, a single vulnerability can trigger real actions — calling APIs, exposing internal data, or executing unintended operations. This isn’t a traditional bug. It’s a new operational attack surface, and existing security tooling wasn’t built for it.

Penligent solves this problem.

Penligent acts like a red team for your AI stack — purpose-built for LLM infrastructures. It automatically probes for jailbreaks, prompt injection paths, privilege escalation, and unintended tool calls. It validates risks end-to-end, simulates realistic exploit chains, and reveals how an attacker could move through your model, your integrations, and your runtime environment.

Instead of vague warnings, Penligent delivers evidence-based results: reproducible test cases, clear impact analysis, and prioritized fixes you can act on immediately.

The goal is simple: make AI safe to run in production. With continuous testing and verifiable protections, you stay ahead of attackers — before real damage occurs.

Penligent — secure your LLM infrastructure, and let your AI work, safely.