Best A2A Agents for Security and Authentication

Security is the A2A use case where getting it wrong costs you the most. An agent that hallucinates a vulnerability wastes your time. An agent that misses one costs you a breach. The agents in this space range from genuinely useful reference implementations to thin wrappers around pip audit. Here is an honest assessment of each.

Quick Comparison

Agent	Focus Area	Framework	Language	Auth Support	Quality Score
Headless Agent Auth	Agent authentication patterns	A2A Python SDK	Python	OAuth2, mTLS	9/10
Signing & Verifying	Message integrity	A2A Python SDK	Python	Cryptographic signing	8/10
Magic 8 Ball Security	Auth reference (Java)	Spring Boot	Java	JWT, RBAC	7/10
Code Review Agent	Vulnerability scanning	Custom	Python	Bearer token	7/10
Dependency Audit Agent	Supply chain security	Custom	Python	API key	6/10

Headless Agent Auth

Repo: a2aproject/a2a-samples/headless_agent_auth

This is the reference implementation for A2A authentication. Not a vulnerability scanner, not a compliance checker -- this is the pattern for how agents authenticate with each other without a human in the loop. If you are deploying A2A agents in production, you study this before writing auth code.

It demonstrates OAuth2 client credentials flow, token validation, and secure Agent Card configuration. The code is from the official A2A samples repository and tracks spec changes closely.

# Discover the agent and read its security requirements
import httpx

async def discover_secure_agent(base_url: str):
    async with httpx.AsyncClient() as client:
        response = await client.get(
            f"{base_url}/.well-known/agent-card.json"
        )
        card = response.json()

        # Read the security requirements before connecting
        security_schemes = card.get("securitySchemes", {})
        if "oauth2" in security_schemes:
            token_url = security_schemes["oauth2"]["flows"]["clientCredentials"]["tokenUrl"]
            scopes = security_schemes["oauth2"]["flows"]["clientCredentials"]["scopes"]
            return {"auth_type": "oauth2", "token_url": token_url, "scopes": scopes}

        return {"auth_type": "none"}

What works: Clean, production-quality auth patterns. Official sample. Covers the hard parts: token refresh, scope validation, error handling for expired credentials. This is what you fork when building authenticated agent-to-agent communication.

What doesn't: It is a pattern, not a product. You are not deploying this as-is. You are reading the code and implementing the same patterns in your agents.

Quality: 9/10. The best reference for A2A auth. Essential reading before deploying any agent.

See also: How to Secure A2A Agents with OAuth2 for the full walkthrough.

Signing & Verifying

Repo: a2aproject/a2a-samples/signing_and_verifying

Goes beyond OAuth2 to ensure message integrity. Cryptographic signing means you can verify that a message was not tampered with between sender and receiver, even if it passes through intermediaries.

This matters in multi-agent chains. Agent A sends a task to Agent B through an orchestrator. Without signing, the orchestrator could modify the task content. With signing, Agent B can verify the message came from Agent A unmodified.

# Signing a message before sending
import json
import hashlib
import hmac

def sign_a2a_message(message: dict, secret_key: bytes) -> dict:
    """Add a cryptographic signature to an A2A message."""
    payload = json.dumps(message, sort_keys=True).encode()
    signature = hmac.new(secret_key, payload, hashlib.sha256).hexdigest()

    return {
        **message,
        "metadata": {
            **(message.get("metadata", {})),
            "signature": signature,
            "signatureAlgorithm": "hmac-sha256",
        },
    }


def verify_a2a_message(message: dict, secret_key: bytes) -> bool:
    """Verify the cryptographic signature on an A2A message."""
    metadata = message.get("metadata", {})
    received_signature = metadata.pop("signature", None)
    metadata.pop("signatureAlgorithm", None)

    if not received_signature:
        return False

    # Reconstruct the message without signature fields
    clean_message = {**message, "metadata": metadata}
    payload = json.dumps(clean_message, sort_keys=True).encode()
    expected = hmac.new(secret_key, payload, hashlib.sha256).hexdigest()

    return hmac.compare_digest(received_signature, expected)

What works: Addresses a real gap in the A2A spec. OAuth2 tells you who is calling. Signing tells you the message was not altered in transit. For regulated industries (healthcare, finance), this is not optional.

What doesn't: HMAC requires shared secrets, which creates key distribution challenges at scale. The sample does not cover key rotation or public-key signing (RSA/ECDSA). For large deployments, you would want asymmetric signing with a PKI.

Quality: 8/10. Important pattern for high-trust environments. Needs extension for production key management.

Magic 8 Ball Security (Java)

Repo: a2aproject/a2a-samples/magic_8_ball_security

The name is whimsical but the security implementation is real. This is a Spring Boot A2A agent with JWT validation, role-based access control, and proper security configuration. It is the only Java reference for A2A security in the official samples.

// Security configuration for an A2A agent (Spring Boot)
@Configuration
@EnableWebSecurity
public class SecurityConfig {

    @Bean
    public SecurityFilterChain filterChain(HttpSecurity http) throws Exception {
        http
            .authorizeHttpRequests(auth -> auth
                // Agent Card is public
                .requestMatchers("/.well-known/agent-card.json").permitAll()
                // Everything else requires authentication
                .anyRequest().authenticated()
            )
            .oauth2ResourceServer(oauth2 -> oauth2
                .jwt(jwt -> jwt
                    .jwtAuthenticationConverter(jwtAuthConverter())
                )
            );
        return http.build();
    }

    @Bean
    public JwtAuthenticationConverter jwtAuthConverter() {
        JwtGrantedAuthoritiesConverter converter = new JwtGrantedAuthoritiesConverter();
        converter.setAuthoritiesClaimName("scope");
        converter.setAuthorityPrefix("SCOPE_");

        JwtAuthenticationConverter authConverter = new JwtAuthenticationConverter();
        authConverter.setJwtGrantedAuthoritiesConverter(converter);
        return authConverter;
    }
}

What works: If your organization is Java/Spring Boot, this is your starting point. The Spring Security integration is idiomatic. JWT validation, scope-based authorization, and the public Agent Card endpoint are handled correctly.

What doesn't: It is a demo (Magic 8 Ball) with real security. The business logic is trivial. You are extracting the security layer and grafting it onto your actual agent. Also, Java A2A agent support lags behind Python in terms of ecosystem tooling.

Quality: 7/10. Best available Java reference. Security implementation is solid. Limited by the Java A2A ecosystem being smaller.

Code Review Agent (Security Focus)

Framework: Custom Python with A2A SDK

A code review agent focused on security vulnerabilities: SQL injection, XSS, hardcoded credentials, insecure deserialization. It accepts code snippets or file contents and returns findings with severity ratings.

# Connecting to a security-focused code review agent
import httpx

async def scan_code_for_vulnerabilities(code: str, language: str = "python"):
    payload = {
        "jsonrpc": "2.0",
        "id": "security-scan-1",
        "method": "message/send",
        "params": {
            "message": {
                "role": "user",
                "parts": [
                    {
                        "type": "text",
                        "text": f"Scan this {language} code for security vulnerabilities. "
                                f"Report severity (critical/high/medium/low), "
                                f"the specific vulnerability type (CWE if applicable), "
                                f"and a fix recommendation.\n\n```{language}\n{code}\n```"
                    }
                ],
            }
        },
    }

    async with httpx.AsyncClient() as client:
        response = await client.post(
            "http://code-review-agent:9000",
            json=payload,
            headers={
                "Authorization": "Bearer your-token-here",
                "Content-Type": "application/json",
            },
            timeout=60,
        )
        return response.json()

What works: LLM-based code review catches pattern-level vulnerabilities that regex-based scanners miss. It can reason about data flow, identify taint propagation, and explain why a particular pattern is dangerous. The CWE classification adds rigor.

What doesn't: It hallucinates vulnerabilities. Every LLM-based scanner does. You will get false positives -- sometimes confidently stated false positives. This is a supplementary tool, not a replacement for SAST/DAST. It should never be the only thing between your code and production.

Quality: 7/10. Useful as an additional review layer. Do not use as your only security scanner.

Dependency Audit Agent

Framework: Custom Python

Scans requirements.txt, package.json, go.mod, and similar dependency manifests for known vulnerabilities. Cross-references against the OSV database and NVD.

# Sending a dependency manifest for audit
async def audit_dependencies(manifest_content: str, manifest_type: str):
    payload = {
        "jsonrpc": "2.0",
        "id": "dep-audit-1",
        "method": "message/send",
        "params": {
            "message": {
                "role": "user",
                "parts": [
                    {
                        "type": "text",
                        "text": f"Audit these {manifest_type} dependencies for known vulnerabilities:\n\n{manifest_content}"
                    }
                ],
            },
            "metadata": {
                "skillId": "dependency-audit",
            },
        },
    }

    async with httpx.AsyncClient() as client:
        response = await client.post(
            "http://audit-agent:9000",
            json=payload,
            headers={"X-API-Key": "your-api-key"},
            timeout=120,
        )
        return response.json()

What works: Wraps existing vulnerability databases in an A2A interface, making dependency auditing composable with other agents. A CI/CD pipeline agent can call this before deploying. A code review agent can call it after analyzing imports.

What doesn't: This is essentially pip audit or npm audit behind an HTTP endpoint. The LLM adds some interpretation, but the core data comes from the same databases those tools use. If you are already running Snyk, Dependabot, or Grype, this adds marginal value.

Quality: 6/10. Useful for A2A composability. Redundant if you have existing dependency scanning.

Building a Security Pipeline

The agents above compose into a security review pipeline:

Code Review Agent (static analysis for vulnerabilities)
    |
    v
Dependency Audit Agent (supply chain check)
    |
    v
Signing & Verifying (ensure report integrity)
    |
    v
Compliance Report Agent (aggregate findings, map to frameworks)

Orchestrate it with a coordinator:

async def security_review_pipeline(codebase_path: str):
    """Run a full security review across multiple A2A agents."""

    # Step 1: Code review
    code_findings = await scan_code_for_vulnerabilities(
        code=read_file(codebase_path),
        language="python"
    )

    # Step 2: Dependency audit
    manifest = read_file(f"{codebase_path}/requirements.txt")
    dep_findings = await audit_dependencies(manifest, "pip")

    # Step 3: Sign the combined report
    report = {
        "code_review": code_findings,
        "dependency_audit": dep_findings,
        "timestamp": datetime.utcnow().isoformat(),
    }
    signed_report = sign_a2a_message(report, secret_key)

    return signed_report

Honest Assessment

The A2A security agent ecosystem is early. The authentication patterns (Headless Agent Auth, Signing & Verifying) are production-quality because they come from the official samples and address the protocol's own security needs. The vulnerability scanning and dependency auditing agents are useful as composable building blocks but do not replace dedicated security tools like Snyk, SonarQube, or Semgrep.

Where A2A security agents add genuine value: automating the glue between tools. A pipeline that runs Semgrep, feeds results to an LLM-based agent for triage and explanation, and then routes critical findings to the right team -- that is where the protocol's composability matters.

What they do not replace: your security team's judgment.

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See the full Security & Auth stack on StackA2A for all available agents, or read A2A Agent Discovery: Security Best Practices for securing the agents themselves.