An event that highlighted the current inefficiencies of using traditional authentication on AI agent was the CVE-2025–6514, what is this you may ask? This is a vulnerability that was found in mcp-remote affecting 558,846 development environments making them potential attack vectors. The vulnerability was the usage of human authentication protocols to secure autonomous systems that operate at machine speed. This vulnerability revealed the mismatch between traditional identity systems and autonomous agent architectures. The Fundamental Mismatch When Oauth was designed, it has a specific workflow model: a human clicks “Sign in with Google,” reviews permissions on a familiar interface, approves access, and returns to the application. This happens maybe once per session, with clear visual feedback and human judgment at every step. When it came to AI agents, these assumptions were broken. Volume and velocity: A single user query can trigger dozens of authentication flows as agents chain tool calls across multiple services which defeats what OAuth was designed for which is occasional human interaction. Volume and velocity Absence of human validation: Humans can recognize suspicious authorization URLs while agents lack that intuition. We notice when google.com becomes g00gle.com, or when an authorization page looks wrong. They receive a URL string, follow the protocol, and process whatever comes back. If that URL points to malicious code, the agent executes it without hesitation. Absence of human validation Trust propagation: When Agent A calls Agent B which authenticates to Service C, and Service C is compromised, that compromise propagates through the entire chain. Traditional OAuth has no concept of delegation chains or transitive trust relationships. Trust propagation Context collapse: With Oauth, its all or nothing. You’re authenticated or you’re not, you have permission or you don’t, but agents, there needs to be context-aware authorization: “Agent A can approve refunds up to $100, but only when invoked by User B, only once per day, and only for transactions less than 30 days old.” Context collapse Traditional IAM’s Blind Spots Identity is now chained: With traditional IAM, it models identity as a single entity not a chain of delegations where each link might have different trust levels, permissions, and security contexts. Identity is now chained: Authentication is continuous: Agents don’t log in once. They authenticate constantly as they discover new services, chain tool calls, and adapt to changing contexts. This high-velocity, high-volume pattern overwhelms systems designed for occasional human logins. Authentication is continuous Authorization needs context: There’s no contextual factors with traditional systems. When it gives an agent delete access, it doesn’t drill down to context on what file to be deleted and what reason. Authorization needs context The boundary between user and application has dissolved: Is the agent a user? An application? Both? Neither? When an agent makes autonomous decisions on behalf of a user, it creates ambiguity in audit trails, access control, and compliance frameworks. The boundary between user and application has dissolved Real-World Attack Scenarios Scenario 1: The Compromised Middle Agent Scenario 1: The Compromised Middle Agent Consider a production system with three agents: Agent A (trusted): Handles user requests Agent B (trusted): Manages authentication to external services Agent C (malicious): A recently compromised MCP server Agent A (trusted): Handles user requests Agent B (trusted): Manages authentication to external services Agent C (malicious): A recently compromised MCP server Agent A receives a user request that requires external data. It delegates to Agent B, which attempts to authenticate to Agent C. Agent C returns a malicious authorization endpoint. Agent B executes the payload. Now Agent B is compromised. But Agent A continues to trust Agent B as nothing in the system tracks the trust chain or propagates the security breach. Agent A continues routing sensitive operations through compromised Agent B. The user sees no error. The logs show normal OAuth flows. The monitoring systems detect no anomaly because high-volume authentication is normal for agents. The compromise persists undetected. Scenario 2: The Delegation Chain Collapse Scenario 2: The Delegation Chain Collapse A complex agent system is deployed: User authenticates to Agent A Agent A delegates specific capabilities to Agent B Agent B delegates further to Agent C Agent C authenticates to external Service D User authenticates to Agent A Agent A delegates specific capabilities to Agent B Agent B delegates further to Agent C Agent C authenticates to external Service D Agent C gets compromised. With existing systems, there’s no mechanism to: Identify which delegations flowed through Agent C Revoke only the compromised portion of the delegation chain Maintain service for unaffected paths Audit what the compromised agent accessed Identify which delegations flowed through Agent C Revoke only the compromised portion of the delegation chain Maintain service for unaffected paths Audit what the compromised agent accessed The choice becomes binary: shut down the entire system or accept the compromise. There’s no granular revocation, no surgical response, no way to isolate the breach without breaking everything else. Conclusion The real vulnerability isn’t the mcp-remote incident, but the assumption that OAuth which was designed for humans can secure autonomous agents making thousands of authentication decisions per hour without human oversight. The fix is to build systems that understand these agent behaviors, track, enforce, and adapt to risk in real-time as they are actively working. View every OAuth integration in your agent system as a potential attack vector. The question isn’t whether these vulnerabilities will be exploited. It’s when. References References CVE-2025–6514: https://nvd.nist.gov/vuln/detail/CVE-2025-6514JFrog Security Research:https://research.jfrog.com/vulnerabilities/mcp-remote-command-injection-rce-jfsa-2025-001290844/mcp-remote fix commit:https://github.com/geelen/mcp-remote/commit/607b226a356cb61a239ffaba2fb3db1c9dea4bac https://nvd.nist.gov/vuln/detail/CVE-2025-6514 https://research.jfrog.com/vulnerabilities/mcp-remote-command-injection-rce-jfsa-2025-001290844/ https://github.com/geelen/mcp-remote/commit/607b226a356cb61a239ffaba2fb3db1c9dea4bac