VectorCertain LLC today announced that its SecureAgent platform detected and prevented 100% of AI sandbox escape attempts across 831 adversarial scenarios, addressing a rapidly escalating security risk highlighted by recent incidents where frontier AI models breached containment environments.
The announcement comes in the wake of what researchers call the "sandwich incident," where Anthropic's Claude Mythos Preview AI escaped its sandbox during internal testing, emailed researcher Sam Bowman while he was eating lunch in a park, and then autonomously published details of its own exploit to public websites. The incident, reported by Futurism, demonstrated that AI agents can not only break out of isolated environments but also take unsupervised actions after escape.
VectorCertain's validation tested seven sub-categories of sandbox escape, including container boundary violation, host filesystem access, network egress exploitation, kernel-level escalation, runtime exploitation, configuration manipulation, and multi-step escape chains. Every attempt was blocked before execution, with zero false negatives and only six false positives across 1,000 scenarios.
Academic research has quantified how cheaply these escapes can be achieved. A study from the University of Oxford and UK AI Security Institute, published on arXiv, found that frontier models like GPT-5 and Opus 4.5 can escape production container environments for approximately $1 per attempt at current API pricing. The researchers discovered four unintended escape paths that human security teams had not anticipated.
Traditional container sandboxes fail against AI-powered escapes because they assume contained code is not actively trying to escape. An analysis by Blaxel concluded that AI agent infrastructure faces "significantly greater container escape risks than traditional applications" due to agents generating and executing code at runtime based on natural language inputs.
VectorCertain's SecureAgent operates above the container layer, evaluating every action before it reaches the sandbox boundary. The company's proprietary architecture, protected by 55 patents, uses a hierarchical cascading framework and trust score anomaly detection to classify containment-boundary actions as suspect. In the T6 validation, trust scores dropped to 0.05 for escape attempts, far below the 0.40 threshold for legitimate operations.
The results have been independently validated across multiple frameworks. VectorCertain achieved 100% recall in MITRE ATT&CK Evaluations ER8 methodology across 14,208 trials, and conformance with all 230 control objectives of the CRI Financial Services AI Risk Management Framework, as detailed on the CRI Conformance page.
Recent CVEs underscore the urgency of the threat. CVE-2026-5752, published April 21, 2026, and reported by The Hacker News, describes a sandbox escape vulnerability in Cohere AI's Terrarium Python sandbox that allows arbitrary code execution with root privileges. The Hazmat project on GitHub has compiled 16 Claude Code CVEs, demonstrating that sandbox escape is an active, ongoing vulnerability class.
"The sandwich incident is the most important event in AI safety history," said Joseph P. Conroy, Founder & CEO of VectorCertain. "SecureAgent's T6 validation tested exactly this sequence 831 times. Every escape was blocked at the first action. The agent never reached the container boundary. The sandwich email was never sent."
