Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI is changing the speed and scale of cyber defense, and the speed and scale of the adversary. As AI becomes embedded across government, critical infrastructure, and enterprise environments, defenders need the ability to inspect, test, adapt, and secure the systems they depend on.

For the past couple of years, most of the industry’s attention has gone toward agents that respond to a single prompt. They ask a question, get an answer, and move on. Enterprises are now deploying long-horizon agents; autonomous systems that execute extended, multi-step tasks across hours or days, without a human checking in on every step. These agents plan, reason, and improvise their way toward a goal, and that changes what security has to protect against.

Debugging privacy-preserving protocols is hard. Oblivious HTTP has several different steps across four different parties, not to mention binary HTTP encoding and details spread across many draft RFCs. We've taken what we've learned operating protocols like Oblivious HTTP at the scale of millions of requests per second, and wrapped it up in a nice, clean CLI tool — that we are open-sourcing today. We call it our privacy-client, or pvcli.

Scenario-based cyber risk quantification (CRQ) calculates the financial impact of specific cyber incidents in real dollars, one modeled scenario at a time, rather than producing a single blended exposure number for the whole organization.

You're staring at a growing pile of endpoint, cloud, firewall, and identity logs, and the question isn't whether the data is useful, it's whether you can turn it into evidence, detections, and a defensible audit trail. In regulated environments, HIPAA, PCI, and CMMC don't care that your team is busy, they care that logs are collected consistently, normalized correctly, retained properly, and searchable when an incident or audit hits.

An agent reads a file, approves its own next action, and the change survives the session. That one design choice, repeated across nearly every AI coding tool built in the last eighteen months, is the reason this keeps happening.

Fifty-three percent of organizations have had an executive or employee impersonated in targeted social engineering attacks over the past year, according to a new report from Outtake. Just over half of this impersonation activity took place on social media platforms using fake profiles, followed by video platforms.