---

name: agent-bom description: >- Open security platform for agentic infrastructure — broad scanning plus MCP discovery, CVEs, blast radius, SBOMs, CIS benchmarks (AWS, Azure, GCP, Snowflake), OWASP/NIST/MITRE compliance, AISVS v1.0, MAESTRO layer tagging, and vector database security checks. Use when the user mentions vulnerability scanning, MCP server trust, compliance, SBOM generation, CIS benchmarks, blast radius, or AI supply chain risk. version: 0.75.10 license: Apache-2.0 compatibility: >- Requires Python 3.11+. Install via pipx or pip. No credentials required for basic scanning. Native container image scanning — no external scanner required. CIS benchmark checks optionally use cloud SDK credentials (AWS/Azure/GCP/Snowflake). metadata: author: msaad00 homepage: https://github.com/msaad00/agent-bom source: https://github.com/msaad00/agent-bom pypi: https://pypi.org/project/agent-bom/ scorecard: https://securityscorecards.dev/viewer/?uri=github.com/msaad00/agent-bom tests: 6533 install: pipx: agent-bom pip: agent-bom docker: ghcr.io/msaad00/agent-bom:0.75.10 openclaw: requires: bins: [] env: [] credentials: none credential_policy: >- Zero credentials required for CVE scanning, blast radius, compliance evaluation, SBOM generation, and MCP registry lookups. Optional env vars below increase rate limits or enable cloud CIS checks. Env var values in discovered config files are replaced with REDACTED by sanitize_env_vars() in the installed code — verify at https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/security.py#L159 optional_env: - name: SNYK_TOKEN purpose: "Snyk vulnerability enrichment for code_scan (optional)" required: false - name: AWS_PROFILE purpose: "AWS CIS benchmark checks — uses boto3 with local AWS profile" required: false - name: AZURE_TENANT_ID purpose: "Azure CIS benchmark checks (azure-mgmt-* SDK)" required: false - name: AZURE_CLIENT_ID purpose: "Azure CIS benchmark checks — service principal client ID" required: false - name: AZURE_CLIENT_SECRET purpose: "Azure CIS benchmark checks — service principal secret" required: false - name: GOOGLE_APPLICATION_CREDENTIALS purpose: "GCP CIS benchmark checks (google-cloud-* SDK)" required: false - name: SNOWFLAKE_ACCOUNT purpose: "Snowflake CIS benchmark checks" required: false - name: SNOWFLAKE_USER purpose: "Snowflake CIS benchmark checks" required: false - name: SNOWFLAKE_PRIVATE_KEY_PATH purpose: "Snowflake key-pair auth (CI/CD)" required: false - name: SNOWFLAKE_AUTHENTICATOR purpose: "Snowflake auth method (default: externalbrowser SSO)" required: false optional_bins: - semgrep - kubectl emoji: "\U0001F6E1" homepage: https://github.com/msaad00/agent-bom source: https://github.com/msaad00/agent-bom license: Apache-2.0 os: - darwin - linux - windows install_verification: >- VERIFY BEFORE running with any config files: (1) pip install agent-bom; (2) Review sanitize_env_vars() at security.py#L159 — confirms env value redaction; (3) Review discovery/init.py — confirms only structural config data extracted; (4) agent-bom verify agent-bom — Sigstore provenance check; (5) Only then run agent-bom agents credential_handling: >- Env var values are NEVER extracted from config files. sanitize_env_vars() replaces all env values with REDACTED BEFORE any config data is processed or stored. Only structural data (server names, commands, URLs) passes through. Source: https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/security.py#L159 data_flow: >- Scanning is local-first. What leaves the machine: (1) public package names and CVE IDs sent to vulnerability databases (OSV, NVD, EPSS, GitHub Advisories) for CVE lookup; (2) CIS benchmark checks make read-only API calls to cloud providers (AWS/Azure/GCP/Snowflake) using your locally configured credentials, only when explicitly invoked. What stays local: all config file contents, env var values, credentials, scan results, compliance tags, and SBOM data. Registry lookups (427+ MCP servers) are bundled in-package with zero network calls. Env var values in discovered config files are replaced with REDACTED by sanitize_env_vars() in the installed code. file_reads: # Claude Desktop - "/Library/Application Support/Claude/claude_desktop_config.json" - "/.config/Claude/claude_desktop_config.json" # Claude Code - "/.claude/settings.json" - "/.claude.json" # Cursor - "/.cursor/mcp.json" - "/Library/Application Support/Cursor/User/globalStorage/cursor.mcp/mcp.json" # Windsurf - "/.windsurf/mcp.json" # Cline - "/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json" # VS Code Copilot - "/Library/Application Support/Code/User/mcp.json" # Codex CLI - "/.codex/config.toml" # Gemini CLI - "/.gemini/settings.json" # Goose - "/.config/goose/config.yaml" # Continue - "/.continue/config.json" # Zed - "/.config/zed/settings.json" # Roo Code - "/Library/Application Support/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json" # Amazon Q - "/Library/Application Support/Code/User/globalStorage/amazonwebservices.amazon-q-vscode/mcp.json" # JetBrains AI - "~/Library/Application Support/JetBrains//mcp.json" - "/.config/github-copilot/intellij/mcp.json" # Junie - "/.junie/mcp/mcp.json" # GitHub Copilot CLI - "/.copilot/mcp-config.json" # Tabnine - "/.tabnine/mcp_servers.json" # Cortex Code (Snowflake) - "/.snowflake/cortex/mcp.json" - "/.snowflake/cortex/settings.json" - "/.snowflake/cortex/permissions.json" - "/.snowflake/cortex/hooks.json" # Snowflake CLI - "/.snowflake/connections.toml" - "/.snowflake/config.toml" # Project-level configs - ".mcp.json" - ".vscode/mcp.json" - ".cursor/mcp.json" # User-provided files - "user-provided SBOM files (CycloneDX/SPDX JSON)" - "user-provided policy files (YAML/JSON policy-as-code)" - "user-provided audit log files (JSONL from agent-bom proxy)" - "user-provided SKILL.md files (for skill_trust analysis)" file_writes: [] network_endpoints: - url: "https://api.osv.dev/v1" purpose: "OSV vulnerability database — batch CVE lookup for packages" auth: false - url: "https://services.nvd.nist.gov/rest/json/cves/2.0" purpose: "NVD secondary enrichment — adds CWE IDs, dates, references (no key required)" auth: false - url: "https://api.first.org/data/v1/epss" purpose: "EPSS exploit probability scores" auth: false - url: "https://api.github.com/advisories" purpose: "GitHub Security Advisories — supplemental CVE lookup" auth: false - url: "https://api.snyk.io" purpose: "Snyk vulnerability enrichment for code_scan (requires SNYK_TOKEN)" auth: true - url: "https://.amazonaws.com" purpose: "AWS CIS benchmark checks — read-only API calls (optional, user-initiated)" auth: true optional: true - url: "https://management.azure.com" purpose: "Azure CIS benchmark checks — read-only API calls (optional, user-initiated)" auth: true optional: true - url: "https://.googleapis.com" purpose: "GCP CIS benchmark checks — read-only API calls (optional, user-initiated)" auth: true optional: true - url: "https://.snowflakecomputing.com" purpose: "Snowflake CIS benchmark checks — read-only API calls (optional, user-initiated)" auth: true optional: true telemetry: false persistence: false privilege_escalation: false always: false autonomous_invocation: restricted

agent-bom — AI Agent Infrastructure Security Scanner

Discovers MCP clients and servers across 22 AI tools, scans for CVEs, maps blast radius, runs cloud CIS benchmarks, checks OWASP/NIST/MITRE compliance, generates SBOMs, and assesses AI infrastructure against AISVS v1.0 and MAESTRO framework layers.

Install

pipx install agent-bom
agent-bom agents            # auto-discover + scan
agent-bom check langchain==0.1.0  # check a specific package with version
agent-bom fs .              # scan filesystem packages
agent-bom image nginx:1.25  # scan container image (native)
agent-bom cloud aws         # AWS CIS benchmark
agent-bom iac infra/        # scan Terraform/CloudFormation
agent-bom where             # show all discovery paths

As an MCP Server

{
  "mcpServers": {
    "agent-bom": {
      "command": "uvx",
      "args": ["agent-bom", "mcp"]
    }
  }
}

Sub-Skills (8)

Sub-Skill	Purpose	Triggers
discover	Find agents, MCP servers, configurations	"find agents", "what's configured", "mcp inventory"
scan	CVE scanning, image scanning, SBOM, provenance	"check package", "scan image", "verify", "blast radius"
scan-infra	IaC, cloud config, secrets scanning	"check terraform", "scan kubernetes", "find secrets"
enforce	Runtime policy enforcement, MCP proxy	"block risky calls", "apply policy", "proxy"
compliance	11-framework compliance, SBOM generation	"compliance report", "NIST", "SOC 2", "OWASP"
monitor	Fleet monitoring, trust scores, lifecycle	"fleet", "watch agents", "trust scores"
analyze	Blast radius, attack paths, context graph	"blast radius", "threat intel", "attack path"
troubleshoot	Diagnostics, doctor, config validation	"doctor", "debug", "why failing", "validate config"

Tools (32)

Vulnerability Scanning

Tool	Description
scan	Full discovery + vulnerability scan pipeline
check	Check a package for CVEs (OSV, NVD, EPSS, KEV)
blast_radius	Map CVE impact chain across agents, servers, credentials
remediate	Prioritized remediation plan for vulnerabilities
verify	Package integrity + SLSA provenance check
diff	Compare two scan reports (new/resolved/persistent)
where	Show MCP client config discovery paths
inventory	List discovered agents, servers, packages

Compliance & Policy

Tool	Description
compliance	OWASP LLM/Agentic Top 10, EU AI Act, MITRE ATLAS, NIST AI RMF
policy_check	Evaluate results against custom security policy (17 conditions)
cis_benchmark	CIS benchmark checks (AWS, Azure v3.0, GCP v3.0, Snowflake)
generate_sbom	Generate SBOM (CycloneDX or SPDX format)
aisvs_benchmark	OWASP AISVS v1.0 compliance — 9 AI security checks

Registry & Trust

Tool	Description
registry_lookup	Look up MCP server in 427+ server security metadata registry
marketplace_check	Pre-install trust check with registry cross-reference
fleet_scan	Batch registry lookup + risk scoring for MCP server inventories
skill_trust	Assess skill file trust level (5-category analysis)
code_scan	SAST scanning via Semgrep with CWE-based compliance mapping

Runtime & Analytics

Tool	Description
context_graph	Agent context graph with lateral movement analysis
analytics_query	Query vulnerability trends, posture history, and runtime events
runtime_correlate	Cross-reference proxy audit JSONL with CVE findings, risk amplification
vector_db_scan	Probe Qdrant/Weaviate/Chroma/Milvus for auth and exposure
gpu_infra_scan	GPU container and K8s node inventory + unauthenticated DCGM probe (MAESTRO KC6)

Specialized Scans

Tool	Description
dataset_card_scan	Scan dataset cards for bias, licensing, and provenance issues
training_pipeline_scan	Scan training pipeline configs for security risks
browser_extension_scan	Scan browser extensions for risky permissions and AI domain access
model_provenance_scan	Verify model provenance and supply chain integrity
prompt_scan	Scan prompt templates for injection and data leakage risks
model_file_scan	Scan model files for unsafe serialization (pickle, etc.)
license_compliance_scan	Full SPDX license catalog scan with copyleft and network-copyleft detection
ingest_external_scan	Import external scan results (CycloneDX/SPDX/JSON) and merge into agent-bom findings

Resources

Resource	Description
registry://servers	Browse 427+ MCP server security metadata registry

Example Workflows

# Check a package before installing
check(package="@modelcontextprotocol/server-filesystem", ecosystem="npm")

# Map blast radius of a CVE
blast_radius(cve_id="CVE-2024-21538")

# Full agent discovery + scan
agents()

# Run CIS benchmark
cis_benchmark(provider="aws")

# Run AISVS v1.0 compliance
aisvs_benchmark()

# Scan vector databases for auth misconfigurations
vector_db_scan()

# Discover GPU containers, K8s GPU nodes, and unauthenticated DCGM endpoints
gpu_infra_scan()

# Assess trust of a skill file
skill_trust(skill_content="<paste SKILL.md content>")

Guardrails

Always do:

• Show CVEs even when NVD analysis is pending or severity is unknown — a CVE ID with no details is still a real finding. Report what is known; mark severity as unknown explicitly.
• Confirm with the user before scanning cloud environments (cis_benchmark) — these make live API calls to AWS/Azure/GCP using the user's credentials.
• Treat UNKNOWN severity as unresolved, not benign — it means data is not yet available, not that the issue is minor.

Never do:

• Do not modify any files, install packages, or change system configuration. This skill is read-only.
• Do not transmit env var values, credentials, or file contents to any external service. Only package names and CVE IDs leave the machine.
• Do not invoke agents() autonomously on sensitive environments without user confirmation. The autonomous_invocation policy is restricted.

Stop and ask the user when:

• The user requests a cloud CIS benchmark and no cloud credentials are configured.
• A scan finds CRITICAL CVEs — present findings and ask whether to generate a remediation plan.
• The user asks to scan a path outside their home directory.

Supported Frameworks (14)

• OWASP LLM Top 10 (2025) — prompt injection, supply chain, data leakage
• OWASP MCP Top 10 — MCP-specific security risks
• OWASP Agentic Top 10 — tool poisoning, rug pulls, credential theft
• OWASP AISVS v1.0 — AI Security Verification Standard (9 checks)
• MITRE ATLAS — adversarial ML threat framework
• NIST AI RMF — govern, map, measure, manage lifecycle
• NIST CSF 2.0 — identify, protect, detect, respond, recover
• NIST 800-53 Rev 5 — federal security controls (CM-8, RA-5, SI-2, SR-3)
• FedRAMP Moderate — derived from NIST 800-53 controls
• EU AI Act — risk classification, transparency, SBOM requirements
• ISO 27001:2022 — information security controls (Annex A)
• SOC 2 — Trust Services Criteria
• CIS Controls v8 — implementation groups IG1/IG2/IG3
• CMMC 2.0 — cybersecurity maturity model (Level 1-3)

Privacy & Data Handling

This skill installs agent-bom from PyPI. Verify the redaction behavior before running with any config files:

# Step 1: Install
pip install agent-bom

# Step 2: Review redaction logic BEFORE scanning
# sanitize_env_vars() replaces ALL env var values with ***REDACTED***
# BEFORE any config data is processed or stored:
# https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/security.py#L159

# Step 3: Review config parsing — only structural data extracted:
# https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/discovery/__init__.py

# Step 4: Verify package provenance (Sigstore)
agent-bom verify agent-bom

# Step 5: Only then run scans
agent-bom agents

What is extracted: Server names, commands, args, and URLs from MCP client config files across 22 AI tools. What is NOT extracted: Env var values are replaced with ***REDACTED*** by sanitize_env_vars() before any processing. Only public package names and CVE IDs are sent to vulnerability databases. Cloud CIS checks use locally configured credentials and call only the cloud provider's own APIs.

Verification

• Source: github.com/msaad00/agent-bom (Apache-2.0)
• Sigstore signed: agent-bom verify agent-bom@0.75.10
• 6,533+ tests with CodeQL + OpenSSF Scorecard
• No telemetry: Zero tracking, zero analytics