Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

CrowdStrike is expanding CrowdStrike Falcon Next-Gen SIEM to support third-party endpoint detection and response (EDR) solutions — beginning with Microsoft Defender — with no Falcon sensor required. This evolution will enable organizations to modernize their SOC without replacing existing endpoint agents. Adversaries are moving faster than ever, exploiting cross-domain gaps across endpoint, identity, network, and cloud.

As organizations race to adopt new AI tools, deploy AI agents, and build AI-powered software, they create new attack surfaces that traditional security controls were never designed to protect. A key example is the prompt and agentic interaction layer, which faces novel threats like indirect prompt injection and agentic tool chain attacks.

Security teams face a threat landscape shaped by AI-driven attacks and identity misuse. Adversaries increasingly rely on compromised identities to blend in as legitimate users, making attacks harder to detect and slower to contain. On average, organizations take 241 days to identify and contain a breach.1 While threats have evolved, legacy SIEMs have not kept pace.

Jira Cloud APIs are widely used for automation and integrations across CI/CD, DevOps, reporting, and internal tools. Atlassian provides native REST API authentication using API tokens and OAuth. This works well for simple scripts and internal automation. However, modern organizations often require stronger controls when APIs are used by multiple services, integrations, and automated systems. As integrations grow, teams often need a more controlled authentication model than user-based tokens alone.

In only a few years, artificial intelligence (AI) has changed almost every aspect of life, and especially so in business. Today, employees are using generative AI tools to draft emails, code software, and analyze data at lightning speed. However, there is a hidden side to this productivity boost: unauthorized AI use. Many employees are bypassing official IT channels and using shadow AI applications to get their work done.

Non-human identities (NHIs) and AI Agents including service accounts, CI/CD credentials and cloud workload identities, now eclipse human identities in enterprise identity systems by 50:1 to 100:1. Modern identity security platforms must assign identities to these assets and furthermore, apply roles, access control policies, visibility and governance in order to secure the modern enterprise.

There’s a claim gaining traction in the market: homomorphic encryption can preserve data privacy in AI workflows. Encrypt your data, run it through a language model, and never expose a single token. Sounds bulletproof. It isn’t. Homomorphic encryption (HE) was built for math, not language. Applying it to LLM pipelines is like encrypting a book and asking someone to summarize it without reading a word. The problem isn’t efficiency.

Endpoint management system breaches stem from compromised privileged access, not unpatched vulnerabilities. Attackers use legitimate credentials to operate undetected within trusted workflows, bypassing traditional controls. Eliminating standing privilege with just-in-time access and enforcing least privilege reduces attack paths, while identity threat detection and response ensures misuse of valid access is identified and contained in real time.

For organisations pursuing SOC 2, demonstrating effective security controls is central to the audit process. While the framework does not prescribe specific technologies or testing frequencies, it does require evidence that risks are identified, assessed, and mitigated through appropriate controls. This is where SOC 2 penetration testing becomes particularly relevant.

Plaintext secrets on developer machines create real supply chain risk. Honeytokens provide early detection while stronger identity-based controls are rolled out.