With every passing day, AI agents are becoming more and more self-sufficient. Gone are the days when there was a need for manual intervention just to allow agents collaborate in real-time. The latest standardized protocols have enabled the AI agents to not only seamlessly collaborate across systems but also across organizations.
However, beyond the widely discussed MCP, multiple other protocols define how agents discover, authenticate, and interact with each other. With such a vast availability, it becomes very important for organizations to address every unique security challenge that these agents may pose.
A2A (Agent-to-Agent Protocol): Decentralized Collaboration Risks
Let’s get started with the Agent-to-Agent protocol that is primarily used to enable direct collaboration between agents via “Cards”. These cards are HTTPS-served metadata documents that promote capabilities, skills, and endpoints. However, this architecture is prone to critical security vulnerabilities scattered across three dimensions.
Here’s a detailed overview of them all:
Agent Cards present a primary attack surface where malicious actors can spoof legitimate agents or embed prompt-injection payloads in metadata fields like descriptions and skills. It leads to LLM downstream manipulation behavior when this data is embedded into system prompts without filtering.
Secondly, compromised agent servers can extract credentials and operational data, while attackers can infiltrate multiple roles such as tool executor, planner, and delegation helper. This can disrupt operations or redirect traffic to malicious endpoints, with man-in-the-middle and session hijacking attacks exploiting insufficiently protected identity verification.
And lastly, traditional authentication methods are not enough for autonomous agents that require rapid trust establishment. It mainly creates impersonation risks when behavioral patterns lack satisfactory verification, and weak identity protocols fail to provide robust yet dynamic trust mechanisms.
ACP (Agent Communication Protocol): Flexibility vs. Security Trade-offs
The Agent Communication Protocol, powered by IBM, utilizes a registry-based model with MIME-typed multipart messages for structured data exchange. It is further backed by JSON Web Signatures (JWS) for integrity. However, this architectural flexibility boasts significant security vulnerabilities.
Often, predictable integrity failures are caused by optional JWS enforcement in and data exfiltration in non-strict configurations. This mainly occurs when the protocol remains exposed to reflective leakage when task generation depends on LLM reasoning.
While tokens are not fully exposed, it is advisable to use short-lived tokens. Enforcement is optional, which increases the chance for replay attacks. Extended sessions without JWS timestamps are also vulnerable to this issue. Further, loose compatibility with the legacy system creates several misconfigurations that allow the token to have a prolonged lifetime.
Also, when manifests are reused, registry-mediated routing can unintentionally collect metadata across tasks, creating secondary exposure channels that indicate internal system structure, API endpoints, and operational patterns to unauthorized agents.
ANP (Agent Network Protocol): Decentralized Identity Challenges
The Agent Network Protocol has a three-layer architecture for agent identity authentication and dynamic negotiation. However, such a design presents serious security flaws.
By utilizing W3C DID standards, this protocol creates difficulties in setting up trust, making revocation and compromise detection more complicated than similar actions in the case of a centralized authority.
Even though the ANP calls for minimum information disclosure and end-to-end encryption, it is challenging to implement these approaches across different operating agent networks. Care will also need to be taken to enforce the separation of human and agent authorization schemes at the right point in order to mitigate privilege escalation issues.
Moreover, enhancements to flexibility through the naturally-language negotiation and AI code generator components of the Meta-Protocol Layer create attack vectors whereby malicious agents can negotiate capabilities that initially appear harmless but contain hidden malicious functions through AI-native exploitations.
Conclusion
The architecture of A2A, ACP, and ANP protocols has flexibility, but the security analysis shows a conflict.
A2A’s Agent Cards do not have a crypto signature that prevents impersonation and prompt injection attacks. Optional components of the ACP create known states of failure. The collection of metadata in the registry leaks the internal structure. The complexity of ANP's decentralized identity creates reversal and negotiation risks.
To mitigate these threats, organizations must require checks at the transport layer and govern centrally while combining hybrid approaches.