EchelonGraph CVE & Exposure
CVE, KEV, EPSS, SBOM and advisory lookups; per-CVE exposure from Shodan data (© Shodan). Keyless.
제작자가 쓴 설명(영어 원문)
AWS security scanner with attack chain detection, IAM privilege escalation, and fixes
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"cloud-audit": {
"command": "uvx",
"args": [
"cloud-audit"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add cloud-audit -- uvx cloud-audit프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"cloud-audit": {
"command": "uvx",
"args": [
"cloud-audit"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"cloud-audit": {
"type": "stdio",
"command": "uvx",
"args": [
"cloud-audit"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 gebalamariusz 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(2.0.1)은 7개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: EchelonGraph CVE & Exposure, SML Risk Firewall, Nife
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
CVE, KEV, EPSS, SBOM and advisory lookups; per-CVE exposure from Shodan data (© Shodan). Keyless.
Pre-trade risk checks for agent trades: orders vs your limits, signed receipts.
Manage Nife.io cloud apps, sites, secrets and Git integrations from MCP clients.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
cloud-audit
English | 简体中文
What can a hijacked AI agent reach in your AWS account, and can you prove it?
Open-source, read-only AWS security scanner. 110 checks, 64 IAM privilege-escalation methods, 31 attack-chain rules, blast radius for any resource, and agent-blast for Bedrock Agents and AgentCore: what a prompt-injected or credential-stolen agent can reach, with the IAM policy simulator as the witness. Every finding ships an AWS CLI + Terraform fix . Nothing is written to your account.
30-second demo - agent-blast - Full scan - What's inside - Proof Mode - Installation - Documentation
pip install cloud-audit
cloud-audit agent-blast --demo # a hijacked Bedrock Agent, two threat models, one screen cloud-audit demo --save demo.json # a full sample scan, then explore it offline: cloud-audit blast-radius --report demo.json --resource arn:aws:iam::123456789012:role/support-bot-ticket-role cloud-audit simulate --report demo.json --fix aws-iam-018 cloud-audit exposure --report demo.json
The sample account is invented. Everything derived from it (attack chains, root causes, breach cost, security graph, agent reach) is produced by the same engines a real scan uses.
With credentials, the real thing is one command and read-only. The AWS-managed SecurityAudit policy covers every check (permissions):
cloud-audit scan # default profile and region
cloud-audit scan --verify # plus IAM policy-simulator proof for escalation paths cloud-audit agent-blast --verify # then: what your agents can reach, simulator-confirmed
An AI agent in AWS is a bundle of IAM identities: the role the agent runs as, the execution roles of the Lambda functions behind its tools, the roles of its knowledge bases, gateways and sandboxes. When the agent is hijacked, the attacker acts with *those* identities. agent-blast answers what that means, per agent, under two threat models:
| Threat model | What the attacker has | What is in reach |
|---|---|---|
| Identity takeover | the credentials of a role the agent runs as (sandbox escape, metadata-service read, leaked session) | the full role: privilege-escalation methods, AssumeRole hops, data |
| Behaviour takeover | nothing but a prompt (indirect prompt injection through a document, a ticket, a web page) | what the agent's tools can do, bounded by the tools' own execution roles |
Real output for the sample agent (cloud-audit agent-blast --demo -a support-bot):
support-bot (bedrock_agent, eu-central-1)
├── A hijacked tool (tool: create-ticket) can escalate to account admin via PassRole+Lambda ├── status: PREPARED ├── Identity takeover (attacker holds the role's credentials) │ └── support-bot-agent-role arn:aws:iam::123456789012:role/support-bot-agent-role │ └── no escalation path; 3 reach(es) from policy grants, 1 on named resources (see Reach) │ (risk 0/100, 1 nodes) ├── Behaviour takeover (prompt injection: the agent's tools, their roles) │ ├── search-docs action_group_lambda -> support-bot-search-role │ │ ├── 3 OpenAPI path(s) in apiSchema; state ENABLED │ │ └── no escalation path; 4 reach(es) from policy grants, 4 on named resources (see Reach) │ ├── create-ticket action_group_lambda -> support-bot-ticket-role │ │ ├── 2 function(s) in functionSchema; state ENABLED │ │ ├── reaches Account Takeover in 1 hop(s) via PassRole+Lambda (risk 72/100) │ │ └── escalation: PassRole+Lambda │ └── product-docs knowledge_base -> support-bot-kb-role │ ├── 1 S3 data source(s) │ └── no escalation path; 2 reach(es) from policy grants, 2 on named resources (see Reach) ├── Reach (13 action/resource pairs) │ ├── tool: search-docs secretsmanager:GetSecretValue on │ │ arn:aws:secretsmanager:eu-central-1:123456789012:secret:prod/db-credentials-Ab12Cd │ │ unverified read secret values │ ├── tool: create-ticket sts:AssumeRole on arn:aws:iam::123456789012:role/ops-admin unverified │ │ assume IAM roles │ ├── tool: create-ticket lambda:InvokeFunction on * unverified invoke Lambda functions │ ├── tool: search-docs s3:PutObject on arn:aws:s3:::company-backups-2024/* unverified write S3 │ │ objects │ ├── support-bot-agent-role s3:GetObject on arn:aws:s3:::kb-product-docs/* unverified read the │ │ agent's knowledge base │ ├── tool: search-docs s3:GetObject on arn:aws:s3:::company-backups-2024/* unverified read S3 │ │ objects │ ... ├── Tags │ ├── OWASP Agentic: ASI02 Tool Misuse and Exploitation, ASI03 Identity and Privilege Abuse, │ │ ASI05 Unexpected Code Execution │ └── MITRE ATLAS: AML.T0034 Cost Harvesting, AML.T0040 AI Model Inference API Access, AML.T0053 │ AI Agent Tool Invocation, AML.T0086 Exfiltration via AI Agent Tool Invocation └── Simulated, not executed: identity policies, the attached permissions boundary and SCPs are evaluated by the IAM policy simulator; resource-based policies of the targets, RCPs and VPC endpoint policies are not. Tool reach is an upper bound set by the tool's role; what the tool code does with its inputs is narrower.
The story the output tells: the support bot itself is harmless, but a document that tricks it into calling create-ticket runs code under a role that can pass an admin role to a new Lambda. The search-docs tool, meant to read product docs, can also read the production database secret and write into the backups bucket. Every line names the identity, the action and the resource, so the fix is a policy statement, not a debate.
The same engine covers AgentCore. For the sample gateway (--demo -a tools-gw) the headline is a cross-agent one:
tools-gw (agentcore_gateway, eu-central-1)
├── tool: crm-sync can write into agent 'support-bot' knowledge base (RAG poisoning): arn:aws:s3:::kb-product-docs/* ├── inbound authorizer: NONE; policy engine: none ... │ ├── tool: crm-sync s3:PutObject on arn:aws:s3:::kb-product-docs/* unverified write into agent │ │ 'support-bot' knowledge base (RAG poisoning) ... ├── Coverage notes │ └── tool 'erp-mcp' (gateway_target_mcp_server): backend identity unknown, not assessed - remote │ MCP server; credential provider: OAUTH
What agent-blast reads (all list/get, no charge):
DRAFT version resolved to its Lambda and the Lambda's execution role, knowledge bases resolved to their S3 data-source buckets.Condition is present. Conditions are flagged, never guessed. The simulator decides.Then, per identity: the 64 privilege-escalation methods, AssumeRole hops through the trust graph, and every data, secret, lateral, code-execution and model-invocation grant matched against concrete resources. A knowledge-base bucket is always a concrete target, even behind s3:* on *, and write access to it is reported as RAG poisoning. Anything the scanner could not read (a denied region, a tool without an IAM identity) is a coverage note, never a silent pass.
--verify asks iam:SimulatePrincipalPolicy about every concrete pair, with the context an attacker really has (no MFA on the session, TLS transport), and marks each reach PROVEN, DENIED (with the policy layer that denied: SCP, permissions boundary) or not asserted. Output formats: tree, json, markdown. The MCP server exposes the same report as get_agent_blast.
cloud-audit scan runs 110 read-only checks across 25 AWS services, correlates the findings into attack chains, ranks the fixes by how many chains they break and prices the exposure. This is the sample account (cloud-audit demo), rendered by the same code as a real scan and trimmed for length:
┌─────── Health Score ───────┐
│ 15 / 100 │ └────────────────────────────┘ Provider AWS Account 123456789012 Regions eu-central-1 Resources scanned 80 Checks passed 14 Checks failed 6 Attack chains 3 Risk exposure $572K - $12.5M (IBM/Verizon data) ┌───────────────────────── Attack Chains (3 detected) ─────────────────────────┐ │ CRITICAL PassRole Escalation to Admin (support-bot-ticket-role) │ │ Principal 'support-bot-ticket-role' has iam:PassRole and │ │ can create resources with privileged roles via: │ │ PassRole+Lambda. The attacker passes an admin role to a │ │ service, then uses that service to execute code with admin │ │ privileges. │ │ Fix: Scope iam:PassRole for 'support-bot-ticket-role' to │ │ specific role ARNs │ │ Risk: $250K - $5.0M │ │ │ │ CRITICAL Internet-Exposed Admin Instance │ │ i-0abc123def456789, sg-0a1b2c3d4e5f67890 │ │ Instance i-0abc123def456789 is reachable from the internet │ │ via open security group and has admin IAM role │ │ 'prod-admin-role'. An attacker can reach the instance, │ │ access IMDS credentials, and gain full admin access to the │ │ AWS account. │ │ Fix: Restrict security group sg-0a1b2c3d4e5f67890 to │ │ specific IPs (effort: LOW). │ │ Risk: $62K - $625K │ │
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요