Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI agents create data exfiltration risk by combining three capabilities that are dangerous together: access to private data, exposure to untrusted content, and the ability to communicate externally. When all three exist in one agent, an attacker can hide instructions inside an email, document, or webpage the agent processes and trick it into sending sensitive data out. No software vulnerability is required. The attacker doesn't need to break in. They just need to talk to your agent.

We're excited to announce our new partnership with Friends Against Scams, a National Trading Standards initiative working to protect people from scams across the UK. Together, we've created a cybercrime factsheet to help individuals understand the threats they face online, who is most at risk, and where to turn for support.

Alert fatigue is quietly draining security teams, slowing response times, and increasing business risk. As cyber threats rise and alerts multiply, organisations need smarter prioritisation and actionable intelligence, not more noise.

Last week, OpenAI released Privacy Filter, an open-weight model for detecting and redacting PII in text. It is a thoughtful release: Apache 2.0 licensed, able to run locally, designed for high-throughput workflows, and built to go beyond regex-based detection. This is good news for everyone building enterprise AI. Privacy at the model layer is getting real attention. What we liked most was how clearly OpenAI described the role of the model.

Arctic Wolf has identified a targeted intrusion against a North American Web3/cryptocurrency company, which we attribute with a high confidence level to BlueNoroff, a financially motivated subgroup of DPRK’s Lazarus Group.