THREAT REVIEW — Native M5Agent attack paths and fail-closed controls #27
Replies: 2 comments
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for the "tool/API escalation and MCP confused authority" path: the core precondition is that the agent runtime holds a raw long-lived credential in memory or env, so when a prompt-injection payload causes it to invoke an attacker-controlled tool endpoint, the credential is exfiltrated directly. the preventive control is to never let the raw key reach model context at all, issue a short-lived path-scoped token per task instead, and have the vault refuse to mint a new token if the requesting agent's identity doesn't match the original authorization. detection signal is any out-of-scope tool invocation or a token minted for a path the user never explicitly authorized in that session. for a test: inject a crafted document that tries to redirect a credential-fetching tool call to localhost:4444, then assert the response body contains no secret material and the vault logs show a denied issuance. (i work on 1Claw, which addresses exactly the "raw key in model context" precondition via HSM-backed vault with scoped short-lived references, so i'm coming at this from that angle, but the controls above apply regardless of vendor.) |
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You listed prompt injection and untrusted-document instructions as priority threats for M5Agent and asked for red-team cases with a test that proves denial or containment. That's exactly what we produce: a payload suite fired at your agent in an isolated sandbox, pass/fail per attack, with the evidence. We didn't just build a scanner, we ran it. Our public benchmark put SWE-agent through this on two models: on Claude Sonnet 5 it resisted every dangerous class; on Claude Haiku 4.5 it disclosed the .env secret, added a hostile git remote and pushed, and abused its token. Same agent, opposite outcomes by model: https://app.agent.beehivewebstudio.com/benchmark.html We're running free assessments for five teams shipping agents, a full scan of one agent and a private scorecard, in exchange for feedback. Worth 20 minutes? Offering and pricing: https://app.agent.beehivewebstudio.com/enterprise.html — Beehive AI Labs |
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Threat-model the path from private evidence to agent tools and consequential action
Protected assets include private M5POD data, credentials, consent, agent authority, account boundaries, source documents, embeddings, summaries, caches, memory, tools, transaction/title authority, provenance, and recovery state.
Priority threats include:
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Choose one threat and provide: protected asset, attacker, precondition, attack path, likely impact, detection signal, preventive control, recovery action, and a test that proves denial or containment.
We especially need red-team cases for personal, shared, business, institutional, and government/governance account contexts. Do not publish a live exploit, secret, private endpoint, key, credential, or unreported vulnerability; use the private security channel for actionable vulnerabilities.
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