Securing O-RAN: ORAN-DEFEND Takes on Backdoor Threats
Open Radio Access Networks face a novel risk from backdoor policies within third-party deep reinforcement learning applications. ORAN-DEFEND emerges as a strong defense mechanism, promising high…
Read the full articleYou might also wanna read
Unrestricted open-weight AI models raise safety concerns as they become more accessible
Open-weight AI models with advanced capabilities and no safeguards are becoming much more accessible. While they can be useful, AI safety ex

Security Risks of Malicious Backdoors in Large Language Models
LLM security is a critical risk for open-weight models. Learn how malicious backdoors are easily fine-tuned into AI agents to execute harmfu
pub.aimind.so·11mo agoThe Case for a Strategic U.S. Policy Response to Adversarial AI Distillation
In February 2026, Anthropic disclosed that roughly 24,000 fraudulent accounts had bombarded its Claude model with 16 million interactions, l
Local LLMs Show 95% Vulnerability to Backdoor Injection Attacks in Security Research
Local LLMs prioritize privacy over security. Our research reveals a 95% backdoor injection success rate.
Why VPNs and Shared Passwords Are Crippling OT Security — And How to Fix It
OT’s Dirty Secret: Why Your VPN and Shared Passwords Are a Hacker’s Golden Ticket + Video - "Undercode Testing": Monitor hackers like a pro.
undercodetesting.com·15d agoUnrestricted open-weight AI models raise safety concerns as they become more accessible
Open-weight AI models with advanced capabilities and no safeguards are becoming much more accessible. While they can be useful, AI safety ex

Comments
Sign in to join the conversation.
No comments yet. Be the first.