Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Privileged Access Management (PAM) has become a cornerstone of enterprise security, but the environments it protects have changed dramatically. Organizations now manage cloud infrastructure, SaaS applications, remote workforces, third-party vendors, machine identities, and AI-driven workloads that constantly request privileged access. Security teams need to verify every identity, understand the context of each request, and grant only the minimum level of access required.

The Digital Personal Data Protection (DPDP) Act, 2023, has shifted data privacy from a regulatory obligation into a critical business risk. With the DPDP Rules, 2025 providing operational clarity, businesses are expected to implement reasonable security safeguards, manage consent, protect children's data, and respond promptly to personal data breaches.

Artificial intelligence is quickly becoming one of the most transformative technologies in cybersecurity. Unfortunately, it's not transforming the industry exclusively for defenders. Attackers are already experimenting with AI to accelerate reconnaissance, analyze software for vulnerabilities, develop fully-functional exploits, and automate nearly all parts of the attack lifecycle.

On July 14, 2026, attackers compromised release processes connected to the AsyncAPI open- source project and published malicious versions of four widely used npm packages with a combined reach of approximately 2.9 million weekly downloads.

‍ ‍Cyber insurance has become a standard line item in enterprise risk management, and for good reason. The financial consequences of a significant cyber event, whether a ransomware attack that halts operations for weeks or a data breach that triggers regulatory scrutiny and third-party liability, can far exceed what any operational budget was sized to absorb. Insurance exists to handle that tail. Most organizations recognize this benefit and carry a policy.

AI agents introduce a category of security risk that traditional application security, identity management, and even standard AI security programs were not designed to handle. Unlike a generative model that only produces text, an agent takes autonomous action against real systems, chains API calls together to accomplish goals, and often holds permissions broad enough to touch data across multiple business systems.