AI browsers can be convenient, but they also come with security risks.

A critical prompt injection vulnerability in GitHub Agentic Workflows could allow unauthenticated attackers to leak private repository data, ...

Your LLM-based systems are at risk of being attacked to access business data, gain personal advantage, or exploit tools to the same ends. Everything you put in the system prompt is public data.

Security leaders must adapt large language model controls such as input validation, output filtering and least-privilege access for artificial intelligence systems to prevent prompt injection attacks.

Awareness of all the ways prompt injection can be effected will help security teams spot a new generation of attacks.

Even as OpenAI works to harden its Atlas AI browser against cyberattacks, the company admits that prompt injections, a type of attack that manipulates AI agents to follow malicious instructions often ...

Attackers have begun embedding hidden instructions in websites to target AI agents, according to new research. Zscaler's ...

Agentic AI browsers have opened the door to prompt injection attacks. Prompt injection can steal data or push you to malicious websites. Developers are working on fixes, but you can take steps to stay ...

The authors developed an attack called CoT (Chain of Thought) Forgery that involves using an LLM to spoof the terse style of ...

A prompt injection attack can trick GitHub’s preview Agentic Workflows into retrieving content from private repositories and ...

A now corrected issue allowed researchers to circumvent Apple’s restrictions and force the on-device LLM to execute attacker-controlled actions. Here’s how they did it. Interestingly, they ...