Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Gartner released the Hype Cycle for Secure AI, 2026 on 12 October 2026. I spent some time going through it, and a few things really stood out. The AI security market is exploding with new vendors, categories, and solutions. But the research reinforces something I’ve believed for a long time: Securing AI requires more than protecting the model. You need to understand and protect what AI can actually do.

Every API security evaluation reaches the same objection: “We already run SAST and DAST.” The objection is fair. Static Application Security Testing (SAST) reads source code before release. Dynamic Application Security Testing (DAST) probes a running application from the outside. Both belong in continuous integration and continuous delivery (CI/CD) pipelines. Both also struggle with the two Application Programming Interface (API) flaws that matter most.

AI agents are moving into production fast. They read email, call tools, query databases, and trigger business processes, often chaining those steps in ways no single team designed. Building them has never been easier. Securing what happens after an agent is manipulated is the hard part. That is the gap Salt and AWS will tackle together on Tuesday, November 10, at 9:00 am PT (12:00 pm ET) in a live session: AWS + Salt: Build Fast, Stay Secure with Agentic AI. Save your seat →

Security teams have never been better at finding problems. Discovery is broader, detection is sharper, and the volume of findings keeps climbing. But a finding is not a fix. When teams identify a risky AI agent, an exposed MCP server, or an active attack against an API, what happens next usually looks the same: someone triages it, someone opens a ticket, and someone on another team eventually makes the change. Until then, the risk stays exactly where it was.

India’s largest bank confirmed a data loss incident in a 21 October 2026 filing with the BSE and NSE. The alert came five days earlier, on 16 October, through SBI’s threat intelligence channels, which its filing names alongside the Defence Cyber Agency, and from CERT-In. Both flagged suspected customer data on the dark web.

PCI DSS 4.0.1 is the first major standard to name API business logic as an attack type you must address. Requirement 6.2.4 lists attacks on business logic, including attempts to abuse or bypass application features through the manipulation of APIs, alongside injection and access control flaws. The timing matters. All requirements, including the ones that were future-dated, have been mandatory since 31 March 2025. Your next assessment will test controls that were optional a year ago. The reason is simple.

Brookings and the World Economic Forum say agent governance must be continuous, scoped in advance, evidenced, and monitored at runtime. We think that bar is correct, and that most organizations are nowhere near it. Most of what companies call AI agent governance today is paperwork. A review board approves the use case. A policy document says agents must follow least privilege. A risk assessment gets filed. Then the agent ships, and nobody can say what it actually did on Tuesday. That isn't governance.

On October 21, 2026, two critical vulnerabilities, PHP2Shell (CVE-2026-109618 and CVE-2026-109619), were publicly disclosed. Both are rated 9.2 and both allow remote code execution on vulnerable servers. Government portals, public services, and commercial sites across multiple countries went offline as a precaution while teams rushed to patch. But the flaws were known on October 20, and the patch didn’t ship until the 21st.

Researchers pulled real, leaked API keys out of three LLMs using only API output. Here is how AI agents carry secrets from developer laptops into model context, and how to stop them before the model sees them.