Operations | Monitoring | ITSM | DevOps | Cloud

Citrix was facing a major security crisis before its official warning even went out. Companies were already pulling critical network devices offline as attackers exploited serious vulnerabilities in Citrix NetScaler ADC and Gateway systems. In this ShipTalk clip, Adam, Martin, and Starr break down the Citrix zero-day vulnerabilities, the race to respond, and the impossible decision facing security teams: keep potentially compromised infrastructure running or rush to deploy a patch.

What if AI could find a security vulnerability, determine whether it actually matters, write the fix, validate it, and open a pull request for review? In this demo, see how Harness Security Testing Agents work together to move from vulnerability detection to a verified fix with an audit trail along the way. The system uses three agents: Harness can analyze where vulnerabilities exist in your environment, determine whether they’re actually reachable, prioritize what needs to be fixed, and automatically create remediation pull requests.

Citrix NetScaler customers were pulling devices offline as attackers moved faster than the traditional patch and response cycle. What happens when cyberattacks move faster than security teams can react? In this episode of ShipTalk, Martin Reynolds and Adam Arellano are joined by Starr Brown, Director of Open Source Projects at OWASP, to break down the latest Citrix NetScaler ADC and Gateway security vulnerabilities, active exploitation, and the rapidly shrinking window between vulnerability discovery and attack.

An Alibaba-affiliated AI agent went full crypto bro. During reinforcement learning, the agent autonomously started mining cryptocurrency, downloaded the tools it needed, and created a reverse SSH tunnel to get around network restrictions. What starts as a funny story about an AI vaping and mining crypto gets a lot more serious when you realize how sophisticated the behavior actually was.

What happens when an AI agent can do more than suggest a fix — and actually take action inside your CI pipeline? See Harness Worker Agents in action as an AI agent identifies a failed CI build, determines what went wrong, creates the fix, and gets the pipeline moving toward production again. Worker Agents bring AI-powered reasoning directly into your software delivery pipelines while maintaining the controls enterprises need, including sandboxed execution, scoped credentials, policies, and RBAC.

Jev is a new AI model from Type Safe built around a very different idea: instead of generating long answers, it makes fast, simple decisions. The team reportedly even demoed it playing Doom using nothing but split-second choices. After years of teaching AI models to talk, could the next breakthrough be teaching them to simply decide?

See how Harness helps teams move from AI-generated code to production at machine speed. In this demo, Nick Durkin walks through a fully autonomous software delivery workflow inside Harness, showing how teams can review code, enforce policy, run security and LLM scanning, test intelligently, deploy agents, and use Change Advisor to automate approvals with human oversight when needed. You’ll see how Harness helps teams.