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FEAT: A2ATarget for Agent-to-Agent (A2A) protocol endpoints

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#2,824 0 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Active
Tech stack
python
Domain
ai, api, security

Research direction

Start by reviewing the implementation referenced in #2771 and the existing prompt-target patterns in PyRIT. Confirm how the target should handle A2A 0.3 and 0.2 requests, context and task lifecycles, rate-limit retries, and JSON-RPC errors; done means these behaviors are covered by tests against the stated requirements.

Written by the indexing model from the issue text.

Description

Is your feature request related to a problem? Please describe.

More and more agents are deployed behind the Agent-to-Agent (A2A) protocol, for example Microsoft Foundry Agent Service incoming A2A endpoints and Google ADK agents. For a caller, A2A is often the only way in to such an agent, and it sits in front of the agent's server-side instructions, platform guardrails and tools. PyRIT has no target for A2A today, so red-teaming these agents needs a custom HTTPTarget setup that can't follow A2A's task lifecycle or keep an agent's context across turns.

Describe the solution you'd like

An A2ATarget prompt target that:

  • speaks A2A 0.3 (message/send) over JSON-RPC, with a fallback to 0.2 (tasks/send)
  • maps each PyRIT conversation to one A2A context, so multi-turn attacks keep the agent's own server-side state
  • handles the task lifecycle: blocking sends, polling pending tasks, continuing tasks that are waiting for input
  • retries rate limits with pyrit_target_retry, including rate limits the agent relays from its model
  • returns JSON-RPC errors as PyRIT error responses rather than agent text
Describe alternatives you've considered, if relevant

HTTPTarget with a JSON template works for single requests, but it can't manage A2A context IDs, poll pending tasks, or tell a JSON-RPC error apart from an agent reply.

Additional context

I have an implementation in #2771, tested against a Microsoft Foundry prompt agent with incoming A2A enabled.

Dominant language
Python
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Avg merge
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Merged PRs (30d)
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