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.
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.
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.
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.”
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.
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.
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.
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.
Real-World Attack Scenarios
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 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
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
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
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
CVE-2025–6514: https://nvd.nist.gov/vuln/detail/CVE-2025-6514
JFrog 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