⚠️

Your AI Agents Are Spoofable

Unless they're secured with A2SPA.

Spoof Without A2SPA

(it works)

$ /assistant --prompt "transfer $10,000"
✔️ Transfer initiated: $10,000

Spoof With A2SPA

(it fails)

$ /assistant --prompt "transfer $10,000"
⛔ Error: Signature verification failed
🛡️

Common AI Agent Attack Vectors

Understanding these vulnerabilities is the first step to securing your agents.

Prompt Injection

Attackers insert malicious commands in inputs to bypass safeguards, e.g., extracting tool schemas or forwarding to unauthorized APIs. Occurs due to unsanitized inputs in MCP standards, enabling system compromise.

Memory Poisoning

False data injected into agent's memory leads to ongoing biased outputs across sessions. Results from poor context validation, allowing cumulative manipulations.

Tool Misuse

Deception causes agents to misuse tools, like scanning internal IPs via web readers or executing harmful code. Due to inadequate isolation from external interfaces.

Privilege Compromise or Escalation

Excessive privileges allow access to restricted data via BOLA flaws. Stems from missing RBAC in shared environments.

Resource Overload

Inputs trigger infinite loops or excessive API calls, causing DoS. Exploitable without rate limits or monitoring.

Intent Breaking and Goal Manipulation

Crafted prompts redirect agent's goals maliciously while seeming benign. Targets autonomous planning in multi-agent setups.

Identity Spoofing and Impersonation

Faked identities steal credentials or alter workflows. From weak auth in distributed agent systems.

Command Injection

Inputs embed commands for RCE on linked systems. Exploits unsanitized agent handling, akin to web vulns.

Supply Chain and Dependency Attacks

Tampering with third-party libs compromises agents. Risks from ecosystem interdependencies.

Agent Communication Poisoning

Altered inter-agent messages spread false info. Due to unsecured channels in multi-agent environments.

Replay Attacks

Old payloads resent to re-execute actions, e.g., repeating withdrawals. Occurs without nonce/timestamp checks. Leads to repeated malicious operations.

Version Drift & Model Mismatch

Mismatched agent versions exploited via outdated logic. Due to absent version integrity/compatibility verification. Causes silent vulnerable behavior.

Lack of Auditability / Non-Repudiation

No proof of action initiators in harmful events. From missing signed logs. Results in untraceable attacks and no accountability.

Malicious Agent Injection (Rogue Agent)

Impersonated agents join networks as insiders. Happens without identity/onboarding verification. Enables internal attacks.

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