github analyzed 796585e unconfirmed MCP

aws-samples/sample-ai-security-posture-management

github

AWS-native AI Security Posture Management for AI agents (Observe • Govern • Defend). Discovery, OWASP/NIST/MITRE posture rules, runtime detection & Bedrock Guardrails enforcement, and AIDR integrations (Security Hub, GuardDuty) — open source, in-account, extensible.

maintainer
aws-samples
license
Apache-2.0
first seen
2026-06-07
last seen
2026-06-07
releases · 30d
0
short id
risk 35/100 · heuristic grade
C elevated
  • capability exposureinferred+35

inferred

The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.

graded 7m ago · see ecosystem CVEs →

risk trajectory 1 movements
  • B · 22C · 35
capability exposure grade factor +35
Inferred surface — each links to servers holding it:
vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety 1 findings · grade factor +0
  1. lowdangerous code

    env-secret-flows-to-network-js: A process environment value (often a secret/token) flows into a network call — possible credential exfiltration. (/scratch/obs-code-yNXCL8/aws-sampl

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live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:aws-samples/sample-ai-security-posture-management/badge.svg)](https://mcpobservatory.com/servers/github:aws-samples/sample-ai-security-posture-management/security)

Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of aws-samples.