Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI Detection and Response (AI-DR), also called AI runtime security, is quickly becoming a must-have. Prompt injection, jailbreaks, and data leakage are real, and the prompt is often where attacks begin. But the prompt is only the first hop. In an agentic enterprise, a single instruction can trigger activity well beyond the LLM, all the way to your business systems and data.

Ask an AWS security team how many accounts they run, and the honest answer is usually a range. Enterprises on AWS operate anywhere from 100 to 5,000 accounts. Most security teams can see only a fraction of them. That gap is why we built Wallarm Infrastructure Discovery. This week, it was named Enterprise Cloud Security Solution of the Year in the 10th annual CyberSecurity Breakthrough Awards. Here's what it does, and why the judges picked it.

Salt Labs found that the agentic AI platform Manus could be hijacked with a single email. By hiding malicious instructions inside an ordinary message, researchers got Manus to execute malicious code and, from there, reach the email, cloud storage, and code repository accounts a user had connected to it. The full attack required nothing from the victim beyond asking Manus to check their inbox. No stolen password, no clicked link.

Salt Labs recently showed that a single email could hijack the AI agent platform Manus and reach a victim’s connected accounts. The full technical breakdown, with complete evidence, payloads, and screenshots, is in our research team’s write-up, and Dark Reading first reported the finding in an exclusive. This post is the shorter version: what the finding means and what it tells every organization now deploying AI agents. For the full technical detail, read the Salt Labs research blog.

Every automated red-teaming vendor finds the planted flaw in its own demo app. That tells you very little about how the tool will behave on your APIs, with your login flows, your token lifetimes and your developers. The programs we see struggle usually stall on the work around detection: writing auth scripts, keeping tokens alive, arguing over whether a finding is real, and re-testing fixes by hand. That work lands on a small number of senior security engineers.

Answer this without checking: how many AI agents are running in your environment right now? Most security leaders give an estimate and a shrug. That is a fair response, because agents get spun up by an engineer solving a problem on a Tuesday afternoon, through a path that puts them on nobody's radar. In August 2026, researchers found AI agents connected to Hugging Face running loose inside enterprise networks with no owner and no audit trail.