Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Ever wonder why security programs in most organizations fall short despite purchasing defensive cybersecurity tools, conducting offensive security scans, and meeting compliance? Simply put, their attack surface changes faster than validation does, i.e., teams add new assets, deploy code constantly, expand access, and let configurations drift. Say you installed fire alarms and ran a safety drill. Months later, you remodel, but you’re still using the old safety checklist. How safe does that sound now?

Security teams are spending more money than ever on offensive security, and getting less clarity than ever on what it buys using them. For a long time, the central debate was pentesting vs red teaming. That argument settled itself once buyers understood that the two serve different objectives. Now it’s slipping again due to autonomous pentesting vs red teaming.

There was a time when “AI red teaming” sounded like a novelty. Now, it’s fast becoming table stakes. If your organization is shipping machine learning or LLM-powered systems into the real world (especially in sensitive domains), you need to know how those systems behave under pressure. That’s where AI red teaming tools come in. These tools help teams stress-test AI the way it will actually be used (and misused).

There’s a persistent myth about red team operators: that the job is all zero-days, glowing terminals, and cinematic “I’m in” moments. The reality is more interesting and far more human. A day in the life of a red teamer is less about chasing flashy exploits and more about understanding how real people, real systems, and real environments fail under pressure.

Red Team Penetration Testing is a simulated cyberattack that mimics real-world threat behavior to identify vulnerabilities, test defenses, and evaluate how effectively an organization can detect and respond to an attack. It goes beyond traditional testing by focusing on how an attacker would actually move through an environment.

This week, we announced the general availability of Evo AI-SPM, the first operational layer of Snyk’s AI Security Fabric. AI-SPM gives security teams something they’ve never had before: a system of record for AI risk, with the ability to discover models, frameworks, datasets, and agent infrastructure embedded directly in code. For many organizations, that discovery step is a breakthrough.

Author: Sadi Zane.