Firewall

As Large Language Models (LLMs) such as ChatGPT, Perplexity, and Gemini become more prevalent, hackers are, of course, finding ingenious ways to hack them. They succeed because LLMs struggle to distinguish between legitimate instructions and adversarial inputs. Sure, they have some defenses, including input sanitization, output filtering, and adversarial training, but thus far, no foolproof solution exists to stop a hacker from tricking an LLM into doing what they want.

The new Jitter-Trap tool from Varonis is designed to help organizations detect stealthy beacon traffic used by attackers to establish and maintain command and control (C2) communication within victim networks. Beacons are commonly employed by threat actors—including state-sponsored groups and cybercriminals—to avoid detection while executing post-exploitation activities such as data exfiltration, lateral movement, and persistent access.

Cybersecurity circles have been focused on a new threat actor claim regarding a zero-day exploit targeting Fortinet FortiGate firewalls. This claim emerged on a prominent dark web forum and has raised significant alarm due to the exploit’s purported capabilities and the critical role FortiGate devices play in enterprise network security.

Jailbreak techniques for large language models (LLMs) have evolved from simple prompt injections to sophisticated multi-turn strategies that exploit contextual vulnerabilities. The newly discovered Echo Chamber jailbreak, pioneered by NeuralTrust researcher Ahmad Alobaid, represents a significant advancement in adversarial tactics. Unlike direct attacks, it employs iterative “steering seeds” to subtly manipulate model responses while evading safety guardrails.