Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Do you regularly back up Office 365 emails? If not, there’s bad news. Even cloud giants like Microsoft can experience outages and disruptions. And contrary to popular belief, Microsoft holds your organization responsible for any data loss due to these events. Moreover, according to Microsoft’s Shared Responsibility Model, protecting all your data within Microsoft 365 infrastructure is solely your responsibility.

Certbot is good software in the classic Linux tradition: it does one thing simply and expects you to chain it together with everything else. One server, one certificate, done. The trouble is that most environments are not simple. And the moment yours isn’t, you discover that renewing a certificate and getting it deployed are two different problems, and deployment is your problem.