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<\/a><\/p>\nTaken together, this is the nightmare scenario that is widely recognized as the account takeover (ATO). The workspace attack chain begins with an identity compromise via email and expands from there.<\/p>\n
The evolving attack chain: OAuth is the entry point<\/p>\n
The elements of the workspace attack chain attack haven\u2019t changed, but the order in which the attacks unfold has evolved. The sequence I\u2019ve now watched play out across Vercel, Composio, and a growing number of incidents we\u2019re tracking doesn\u2019t start with email at all. Instead, the script gets flipped and an OAuth token becomes the entryway into email, not the other way around.<\/p>\n
Here\u2019s what these attacks looked like:<\/p>\n
OAuth is the entry point: These attacks started by establishing persistence through a stolen OAuth token. These tokens survive password resets, don\u2019t expire, and are hard to observe. They are invisible to users and largely invisible to security teams who aren\u2019t monitoring app behavior. Even scarier, the stolen token is a supply chain attack. A supplier is compromised and the result is access into your environment.
\nSensitive data is accessed: Using the stolen token, the attacker was able to get into data stored in Gmail and Drive.
\nEmail accounts are taken over: The ATO is initially executed using OAuth, not email. The access to email converts a compromised inbox into a much broader incident.
\nLateral pivots: Using a combination of credentials stored in Drive and password resets or magic links via email,the attacker can then move laterally across connected systems.<\/p>\n
We can anticipate that the building blocks of the workspace attack chain will remain consistent, but that attackers \u2013 equipped with AI tools to sniff out vulnerabilities and scale their efforts \u2013 will continue to find ways to recombine them. These OAuth-centric attacks are only one example of this evolution.<\/p>\n The same chains, a different actor<\/p>\n Now let\u2019s shift our thinking, while keeping those four-step sequences I just described in our minds.<\/p>\n Your employees are connecting AI agents to Google Workspace right now. Those agents are authorized. They\u2019re using legitimate OAuth grants. They\u2019re reading email, searching Drive, operating on behalf of real users to do real work. In most organizations, this is happening faster than security teams can track it. <\/p>\n When an AI agent behaves unexpectedly \u2014 because its instructions were ambiguous, because it followed a chain of reasoning its developers didn\u2019t anticipate, because it was fed a prompt through content it encountered in the environment \u2014 it can walk the same path as an attacker:<\/p>\n It accesses an inbox or Drive folder it wasn\u2019t explicitly intended to reach, because its scope was broader than its task required. No malicious actor. No compromised credential. Just an agent doing something its operator didn\u2019t intend, in an environment that didn\u2019t have the controls to stop it.<\/p>\n Why this matters for how you think about defense<\/p>\n Most conversations about AI agent security are framed around preventing prompt injection, red-teaming agent behavior, or reviewing what apps your employees are connecting. Those are real problems and worth solving.<\/p>\n But the threat I\u2019m describing isn\u2019t about an agent being weaponized. It\u2019s about an agent operating exactly as it was built to operate, in an environment where the guardrails weren\u2019t designed with that kind of actor in mind. A human operator acting in an environment where they\u2019ve been overpermissioned will generally know how to navigate this situation using a combination of common sense and understanding of company norms and policies. OAuth tokens granted to an AI agent carry the same access as tokens granted to a person, but the agent won\u2019t understand that it\u2019s been overpermissioned before it acts. It will simply do what it needs to do in order to execute the task.<\/p>\n The controls that matter here aren\u2019t controls on the agent. They\u2019re controls on the environment the agent operates in.<\/p>\n If you know where sensitive data lives across email and Drive, you can enforce policies that restrict access to it before an agent (or an attacker) gets there. If you\u2019re investigating OAuth grants, you can understand and limit exposure to the prying eyes of an attacker or an errant agent. If you can redact password reset links and require step-up verification before sensitive inbox content is readable, it doesn\u2019t matter whether the entity trying to access that content is an attacker or an agent acting outside its intended scope.<\/p>\n The same coverage that defends against the modern attack chain also defends against the modern agent risk. They\u2019re the same problem, wearing different hats.<\/p>\n What defense looks like across the full chain<\/p>\n I don\u2019t think the answer is to add more point solutions to each stage of this chain. I think the answer is coverage that understands the chain as a chain, that can see what\u2019s happening across email, OAuth, Drive, and account behavior, and connect the dots before things go wrong at step three or four.<\/p>\n That\u2019s what we\u2019ve built at Material. Here\u2019s how our coverage maps to each step:<\/p>\n Blocking the initial email payload. Our email security<\/a> is designed to catch what native controls miss: sophisticated phishing, payloads that bypass reputation-based filters, attacker-in-the-middle techniques. Stopping the most common attack method before it starts remains the highest-leverage intervention for the malicious threat.<\/p>\n<\/a><\/p>\n
\nIt reads sensitive content like credentials in email threads or confidential documents in shared drives and makes use of that information.
\nIt takes an action downstream from that access: sending a message, following a link, making a request to another service.
\nIt moves laterally across applications and sensitive information winds up getting exfiltrated to a third party.<\/p>\n