AI Agent Security Breach Exposed Through Predictable Session Identifiers

Critical Security Flaw in AI Protocol Implementation

Security researchers have uncovered a significant vulnerability in the implementation of Anthropic’s Model Context Protocol that enables attackers to hijack AI agent sessions and inject malicious responses, according to technical analysis reports. The security flaw, tracked as CVE-2025-6515, exists in the Oat++ framework’s MCP integration and allows session takeover through predictable session identifier generation.

Critical Security Flaw in AI Protocol Implementation
How the Session Hijacking Vulnerability Works
Practical Exploitation Demonstration
Scope and Prerequisites for Attack
Security Recommendations and Mitigations

How the Session Hijacking Vulnerability Works

The vulnerability centers on inadequate session ID generation in the oatpp-mcp server implementation, sources indicate. Unlike security best practices that require globally unique and cryptographically secure random identifiers, the affected implementation reportedly returns instance pointers as session IDs when using Server-Sent Events transport. This creates predictable patterns that attackers can exploit., according to technology insights

Analysts suggest the attack methodology involves rapidly creating and destroying sessions to log session IDs, then waiting for those same identifiers to be reassigned to legitimate client sessions. “An attacker can exploit this behavior by rapidly creating and destroying sessions, logging the session IDs and then waiting for those same IDs to be reassigned to legitimate client sessions,” JFrog security researchers explained in their technical disclosure.

Practical Exploitation Demonstration

Researchers demonstrated how this vulnerability could be weaponized in real-world scenarios. In their test case, they configured a server programmed to return Python package names and connected a Claude AI client to it. When a legitimate user requested assistance finding image processing packages, the attacker—having identified a reused session ID—could direct the server to supply malicious package recommendations instead of legitimate responses., according to industry reports

The report states that this exploitation method allows attackers to “send POST requests using the hijacked ID, for example – Requesting tools, triggering prompts, or injecting commands, and the server will forward the relevant responses to the victim’s active GET connection.” This creates a scenario where users receive manipulated responses without their knowledge.

Scope and Prerequisites for Attack

Security analysts note that successful exploitation requires specific conditions. The attack reportedly only affects oatpp-mcp implementations using HTTP Server-Sent Events transport and necessitates that attackers have network access to the relevant HTTP server. This limits the attack surface but still represents significant risk for exposed implementations.

According to reports, the vulnerability highlights how security weaknesses in the infrastructure supporting AI systems can compromise entire workflows without directly attacking the AI models themselves. “As AI models become increasingly embedded in workflows via protocols like MCP, they inherit new risks – this session-level exploit shows how the model itself remains untouched while the ecosystem around it is compromised,” the researchers noted.

Security Recommendations and Mitigations

To prevent this type of prompt hijacking attack, security professionals recommend implementing cryptographically secure random number generators for session ID creation. Additionally, analysts suggest clients should avoid simple incrementing identifiers, which remain vulnerable to spraying attacks, and ensure transport channels incorporate robust session separation and expiration mechanisms.

The discovery underscores the importance of security auditing in the rapidly expanding AI ecosystem, particularly as protocols like MCP become more widely adopted for connecting AI agents with data sources and external tools. Security researchers emphasize that proper implementation of established security practices remains crucial even in emerging technological domains.