Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Automation in Security: Fast Track to Compliance

Manual security operations don't just slow teams down. They make breaches more expensive. Organizations that implement advanced security automation cut breach response time by over 100 days and save an average of $3.05 million per incident, according to JumpCloud's 2024 analysis. That number reframes the conversation. Automation in security isn't a convenience feature for mature SOCs. It's an operating model.

ITIL v5: Exploring New Opportunities for IT Professionals

ITIL v5 connects IT service management to real digital product needs and faster delivery. If your team wants clearer direction, improved customer experience, and measurable results, this framework is a practical choice. ITIL v5 unifies strategy, operations, and improvement, offering new opportunities for professionals seeking modern skills and roles in service management.

Secure AI for the real world

AI makes building look easy. That’s the trap. Without a secure, well-designed foundation, workflows break, costs spike, and systems grow fragile. CTOs and CISOs from leading organizations discuss what breaks without a secure foundation, and how to build AI systems that hold up at scale. This session goes deep on the real-world tradeoffs between speed, risk, and trust.

Export Code42 cases to Jira and email automatically

If your security team is managing insider risk or data loss investigations in Code42, keeping Jira and your inbox in sync is tedious. This story from the Tines library solves that by automating the full export process end-to-end. In under five minutes, you'll see how Tines lists all open Code42 cases, deduplicates them to avoid repeat alerts, downloads each full case export as a zip file, creates a pre-populated Jira ticket with key case details, attaches the export to that ticket, and emails it directly to the relevant recipient.

Human-in-the-loop workflows: where intelligent automation meets judgment

Security and IT leaders face a contradictory mandate: move faster with AI and automation while maintaining governance over every action that touches production systems, user accounts, and sensitive data. Most tools force a choice between two failure modes. Either the workflow runs autonomously, and the team hopes nothing breaks, or every action requires manual approval and analysts spend their shifts rubber-stamping low-risk steps until oversight disappears behind a green-checkmark audit trail.
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The AI Data Centre Buildout Has a Security Problem

In recent months, there has been plenty of speculation about whether the industry is in the middle of an "AI bubble," often fuelled by questions about whether massive infrastructure investments are matched by real demand. Yet current developments suggest this is not the case: the ecosystem around AI continues to expand at a pace that indicates longterm structural change rather than shortterm hype.

Agentic workflow automation: governing AI agents inside workflows

AI agents don't behave like the playbooks security and IT teams have spent years building. They form intent, select tools at runtime, and chain actions across systems in sequences nobody pre-authored. This means dropping an LLM into an existing automation sequence and expecting it to act like a smarter playbook is the fastest route to ungoverned, unpredictable outcomes.

Compliance workflow automation: making SOC 2, GDPR, and ISO auditable by design

Compliance teams know the pattern well: tracking down a missing access review sign-off at 11 p.m. the night before an audit, piecing together evidence from spreadsheets, email threads, and the gap between HR and IT. Access reviews keep appearing in SOC 2 exceptions, and the controls usually aren't the problem. The manual processes around them are. Many teams respond by buying a dedicated GRC (Governance, Risk, and Compliance) platform. Traditional GRC tools are structured repositories.

How to build AI agents your security team will approve

A security engineer spends three weeks building an AI agent that triages phishing reports. The demo lands well. Then it hits the security review queue, and the questions start: Which tools can it call? What happens if it misclassifies? Who approves an account lockout at 2 a.m.? Where are the logs? Three more weeks pass, and the agent is still sitting in staging. This is the pattern most teams run into. The agent works, but the governance story doesn't.