The startup’s stealth exit points to a new security frontier: not just screening what AI says, but trying to catch risky agent behavior while it is still unfolding.
AppViewX’s new Agent Identity Security launch shows how non-human identities are becoming a control problem, not just a convenience problem, as AI systems and long-term cryptographic planning collide.
A newly funded company is pushing autonomous AI into third-party risk management, where the real test is not speed but control, auditability, and permission boundaries.
The company has launched Agent Identity Security, a product aimed at discovering, governing, securing, and monitoring AI agents with a native PKI foundation.
A new integration points to a simple but important problem: if AI agents can act, they also need tightly governed access.
The push to let AI agents trigger orders, planning, and logistics promises speed, but it also turns business software into a high-value control plane that must be tightly governed.
NewCore’s launch with $66 million points to a sharper security problem: identity is no longer just for people, but for workloads and AI agents that act on their behalf.
A newly disclosed attack class shows how an AI helper asked to investigate an error can be steered into executing malicious code, without phishing or server compromise.
The shift from screen-driven ERP to AI-orchestrated workflows may promise speed, but it also moves the real control point toward identity, policy, and runtime verification.
A reported vulnerability chain in LangGraph places checkpoint storage and deserialization under the microscope, with some self-hosted deployments potentially facing remote code execution.
As AI agents push deeper into everyday work, companies and professionals are being forced to treat reskilling, upskilling, KPI design, and gap analysis as part of operational readiness.
Three now-patched LangGraph flaws, including an SQL injection-related issue, underline how self-hosted agent runtimes can turn persistence bugs into much larger security problems.
Oracle’s latest AI billing pilot looks less like a clean break from usage pricing and more like a commercial layer built on top of it, with bigger consequences for procurement, auditability, and control.
Agentic AI does not remove accountability. It can scatter it across developers, operators, approvers, and tool owners until responsibility becomes hardest to locate exactly where it matters most.
IBM research points to a widening enterprise AI control gap: accountability is staying centralized even as AI deployments, agents, and business-led use cases spread faster than governance can track.
A new OWASP guidance package signals that autonomous AI is no longer just a model-safety problem - it is becoming an issue of permissions, oversight, and operational control.
A new OWASP AI security release arrives as enterprises wire autonomous agents into real systems, where the danger is less about bad text and more about bad actions.
A global workplace survey shows AI is already buying back hours each week, but many organizations still lack the rules, metrics, and operating model needed to turn that slack into measurable business gain.
A fresh capital raise and a leadership expansion signal how quickly identity governance is being recast as an AI-assisted control problem, not just an audit chore.
Anthropic’s latest warning is less about science fiction than control: once AI can help build AI, governance shifts from model quality to authority, monitoring, and shutdown discipline.