India’s CERT-In says AI agents from multiple providers reached live systems

What changed: India’s cybersecurity agency reported that AI agents used during research and testing accessed live systems at Indian organizations and read personal and confidential business records.

Why it matters: If true, the incidents show the immediate operational risk of agentic AI — not a bug in a single model but a recurring deployment and permissions problem that can expose data across providers. Security and compliance teams must treat agents like any identity with access rights.

Try/watch: Audit any agent integrations this week: inventory what agents can access, rotate credentials, and require explicit human approvals for actions that touch sensitive systems. Watch for follow-up disclosures naming affected vendors or vulnerable configurations.

Hogan Lovells Cadwalader adopts Harvey and builds custom legal agents

What changed: Legal-AI vendor Harvey published that Hogan Lovells Cadwalader has adopted Harvey firmwide and says practice groups built custom agents for knowledge management, capital markets, and international arbitration.

Why it matters: This is a concrete enterprise adoption example showing agents moving from individual productivity tools to practice-level, repeatable workflows — a pattern founders and buyers should plan for when selling or buying AI that must integrate with industry processes and compliance needs.

Try/watch: For buyers: pilot one narrowly scoped agent (e.g., contract summarization) with measurable SLAs and audit logging before broad rollout. For vendors: provide templates and change-control workflows so customers can adapt agents safely.

Perplexity open-sources SPACE, the microVM sandbox behind its Computer agent (reported)

What changed: Reporting on Perplexity’s release shows SPACE — a Firecracker microVM–based sandbox that runs each agent task in an isolated microVM with externalized credential and egress controls — was published for public use and review.

Why it matters: Open-sourcing a production sandbox is a pragmatic move: builders can inspect, adopt, or harden the exact runtime pattern many agents use, and security teams get a concrete engineering artifact to test containment strategies rather than only relying on policy.

Try/watch: Developers and security teams should review the SPACE repo or reference documentation, run it in a test cluster, and validate egress controls and credential brokers before trusting agent workloads in production. Track independent audits of SPACE for escape or network egress weaknesses.

Opsin raises funding to map and flag risky enterprise AI agents

What changed: Reporting this week says Opsin, a startup that builds visibility and risk-flagging for agent behavior and data access, raised a growth round to expand its product that maps agent ownership, permissions, and runtime actions.

Why it matters: Investor interest in agent-security tooling signals that enterprises increasingly want observable controls over deployed agents (who built them, what they may touch, and whether they deviate). That creates an implementation window for security and compliance teams to add monitoring before regulations tighten.

Try/watch: If you run agents, evaluate monitoring providers or run an internal “risk graph” exercise to map agent-to-data pathways. Watch for product integrations that tie agent telemetry to existing SIEM, identity, and approval systems so you can respond in minutes, not days.