Why Attack Path Analysis Could Stop Rogue AI Agent Swarms

Rogue AI agent swarms have been top of mind for the security industry after over 700 AI agents escaped OpenAI’s environment and hacked Hugging Face in July. Most notably, Anthropic CEO Dario Amodei released a blog post in September warning that a swarm with greater capabilities could have caused “catastrophic damage."

As the industry grapples with how to address agent swarms, cybersecurity company Cogent Security, launched in 2025, today announced Cogent Attack Path analysis, which uses the company’s VR-1 AI model to map the routes an attacker can take to an organization’s most valuable data.

The startup, which has raised $53 million to date from investors including Greylock Partners and Bain Capital Ventures, has developed a context engine that takes data from vulnerability scanners, EDR, firewalls, load balancers, cloud platforms, identity providers, code repositories, deploy pipelines and CMDBs. This data is then placed into a single graph of assets, identities, data and controls that refreshes automatically.

Then an exploitability agent uses the VR-1 model to form competing hypotheses, combining vulnerabilities, misconfigurations, credentials, permissions and trust gaps, to create an attack path that a human engineer wouldn’t be able to. The approach illustrates how defenders can use agents to defend organizations against agent swarms.

Stopping Rogue AI Agent Swarms

OpenAI’s breach of Hugging Face revealed the speed at which agents can chain together exploits to gain access to third party systems. Agents that move at machine speed can identify and exploit vulnerabilities faster than defenders can patch them.

This increase in speed is also opening up new attack paths. Research released today by Cogent analyzed 43 million assets across 50 plus Fortune 1000 companies and found enterprises are gaining three new attack paths viable to AI agents for every one viable for human attackers.