Security architecture and threat modeling. OWASP Top 10 2025 analysis, OWASP Agentic AI Top 10 (ASI01-ASI10), AI/LLM security patterns, supply chain security, modern API authentication (OAuth 2.1, DPoP, Passkeys/WebAuthn), vulnerability assessment, and security review for code and infrastructure.
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Security architecture and threat modeling. OWASP Top 10 2025 analysis, OWASP Agentic AI Top 10 (ASI01-ASI10), AI/LLM security patterns, supply chain security, modern API authentication (OAuth 2.1, DPoP, Passkeys/WebAuthn), vulnerability assessment, and security review for code and infrastructure.
version
1.1.0
model
sonnet
invoked_by
both
user_invocable
true
tools
["Read","Write","Edit","Bash","Glob","Grep"]
best_practices
["Apply defense in depth","Follow principle of least privilege","Validate all inputs","Encrypt sensitive data at rest and in transit","Apply human-in-the-loop controls for agentic AI actions","Enforce supply chain integrity (lockfiles, SRI, signed artifacts)"]
error_handling
graceful
streaming
supported
verified
true
lastVerifiedAt
"2026-02-22T00:00:00.000Z"
source
builtin
trust_score
100
provenance_sha
5706c64c817623d9
Security Architect Skill
Security Architect Skill - Performs threat modeling, OWASP Top 10 2025 analysis, OWASP Agentic AI Top 10 (ASI01-ASI10) assessment, AI/LLM security review, supply chain hardening, modern API authentication design, and vulnerability assessment for code and infrastructure.
- Threat modeling (STRIDE)
- OWASP Top 10 2025 vulnerability analysis (updated list)
- OWASP Agentic AI Top 10 (ASI01-ASI10) — AI agent-specific risks
- AI/LLM security: prompt injection defense, tool sandboxing, memory poisoning prevention
- Supply chain security: dependency confusion, typosquatting, SBOM, lockfile enforcement
- Modern API authentication: OAuth 2.1, DPoP (RFC 9449), Passkeys/WebAuthn (FIDO2)
- Security code review
- Authentication/Authorization design
- Encryption and secrets management
- Security architecture patterns
Use OAuth 2.1 (mandatory PKCE, remove implicit/ROPC grants)
Enforce secure session management; invalidate sessions on logout
A08: Software or Data Integrity Failures
Verify dependencies with SRI hashes and cryptographic signatures
Protect CI/CD pipelines; require signed commits and artifacts
A09: Security Logging and Alerting Failures
Log all security events (auth failures, access control violations, input validation failures)
Protect log integrity; never log secrets or PII
Alert on anomalous patterns
A10: Mishandling of Exceptional Conditions (NEW)
Ensure errors fail securely — never "fail open" (default to deny on error)
Validate logic for edge cases: timeouts, partial responses, unexpected nulls
Return generic error messages to clients; log detailed context server-side
Test error handling paths explicitly (chaos/fault injection testing)
Step 3: OWASP Agentic AI Top 10 (ASI01-ASI10) — For AI/Agent Systems
When the codebase involves AI agents, LLMs, or autonomous systems, perform this additional assessment. Released December 2025 by OWASP GenAI Security Project.
ASI
Risk
Core Attack Vector
ASI01
Agent Goal Hijack
Prompt injection redirects agent objectives
ASI02
Tool Misuse
Legitimate tools abused beyond intended scope
ASI03
Identity & Privilege Abuse
Credential inheritance/delegation without scoping
ASI04
Supply Chain Vulnerabilities
Malicious tools, MCP servers, agent registries
ASI05
Unexpected Code Execution
Agent-generated code bypasses security controls
ASI06
Memory & Context Poisoning
Persistent corruption of agent memory/embeddings
ASI07
Insecure Inter-Agent Communication
Weak agent-to-agent protocol validation
ASI08
Cascading Failures
Error propagation across chained agents
ASI09
Human-Agent Trust Exploitation
Agents manipulate users into unsafe approvals
ASI10
Rogue Agents
Agents act outside authorized scope
ASI01 — Agent Goal Hijack: Attackers manipulate planning logic via prompt injection in user input, RAG documents, emails, or calendar invites.
Mitigations: Validate all inputs against expected task scope; enforce task boundary checks in routing layer; use system prompts that resist goal redirection; log unexpected task deviations for review.
ASI02 — Tool Misuse: Agents use tools beyond intended scope (e.g., file deletion when only file read was authorized).
Mitigations: Whitelist/blacklist tools per agent role; validate tool parameters before execution; enforce principle of least privilege for tool access; monitor tool usage patterns for anomalies.
ASI03 — Identity & Privilege Abuse: Agents inherit or delegate credentials without proper scoping, creating attribution gaps.
Mitigations: Assign each agent a distinct, scoped identity; never reuse human credentials for agents; audit all credential delegation chains; enforce short-lived tokens for agent actions.
ASI04 — Supply Chain Vulnerabilities (Agentic): Malicious MCP servers, agent cards, plugin registries, or tool packages poison the agent ecosystem.
Mitigations: Verify integrity of all tool/plugin sources; use registry allowlists; audit MCP server provenance; apply same supply chain controls as A03 to agent tooling.
ASI05 — Unexpected Code Execution: Agent-generated or "vibe-coded" code executes without traditional security controls (sandboxing, review).
Mitigations: Sandbox code execution environments; review agent-generated code before execution in production; apply static analysis to generated code; never execute code from memory/context without validation.
ASI06 — Memory & Context Poisoning: Attackers embed malicious instructions in documents, web pages, or RAG corpora that persist in agent memory and influence future actions.
Mitigations: Sanitize all data written to memory (learnings, vector stores, embeddings); validate memory entries before use; never execute commands sourced from memory without explicit approval; implement memory rotation and auditing (see ADR-102).
ASI07 — Insecure Inter-Agent Communication: Agent-to-agent messages lack authentication, integrity checks, or semantic validation, enabling injection attacks between agents.
Mitigations: Authenticate all agent-to-agent messages; validate message schemas; use signed inter-agent payloads; apply semantic validation (not just structural) to delegated instructions.
ASI08 — Cascading Failures: Errors or attacks in one agent propagate uncontrolled through multi-agent pipelines.
Mitigations: Define error boundaries between agents; implement circuit breakers; require human-in-the-loop checkpoints for high-impact actions; never auto-retry destructive operations on failure.
ASI09 — Human-Agent Trust Exploitation: Agents present misleading information to manipulate users into approving unsafe actions.
Mitigations: Display agent reasoning and provenance transparently; require explicit human confirmation for irreversible actions; detect urgency/fear manipulation patterns; maintain audit trails of all user-agent interactions.
ASI10 — Rogue Agents: Agents operate outside authorized scope, take unsanctioned actions, or resist human override.
Mitigations: Enforce hard authorization boundaries at the infrastructure level (not just prompt level); implement kill-switch mechanisms; log all agent actions with human-reviewable audit trail; test override/shutdown paths regularly.
Step 4: Supply Chain Security Review
Perform this check for all projects with external dependencies:
# Check for known vulnerabilities
npm audit --audit-level=high
# or
pnpm audit
# Verify lockfile integrity (ensure lockfile is committed and not bypassed)# Check that package-lock.json / yarn.lock / pnpm-lock.yaml exists and is current# Scan for malicious packages (behavioral analysis)# Tools: Socket.dev, Snyk, Aikido, Safety (Python)
Dependency Confusion Defense:
Scope all internal packages under a private namespace (e.g., @company/package-name)
Configure registry resolution order to prefer private registry
Use publishConfig and registry scoping to prevent public registry fallback for private packages
Block exotic transitive dependencies (git URLs, direct tarball URLs)
Typosquatting Defense:
Audit all npm install / pip install commands for misspellings
Use allowlists for permitted packages in automated environments
Delay new dependency version installs by 24+ hours (minimumReleaseAge) to allow malware detection
CI/CD Pipeline Hardening:
Enforce separation of duty: no single actor writes code AND promotes to production
Sign all build artifacts and verify signatures before deployment
Pin action versions in GitHub Actions (use commit SHA, not floating tags)
Restrict pipeline secrets to minimum required scope
Step 5: Modern API Authentication Review
OAuth 2.1 (current standard — replaces OAuth 2.0 for new implementations):
OAuth 2.1 removes insecure grants:
- Implicit grant (response_type=token) — REMOVED: tokens in URL fragments leak
- Resource Owner Password Credentials (ROPC) — REMOVED: breaks delegated auth model
OAuth 2.1 mandates:
- PKCE (Proof Key for Code Exchange) for ALL authorization code flows
- Exact redirect URI matching (no wildcards)
- Sender-constraining tokens (DPoP recommended)
DPoP — Demonstrating Proof of Possession (RFC 9449):
Binds access/refresh tokens cryptographically to the client's key pair
Prevents token replay attacks even if tokens are intercepted
Implement for all public clients (SPAs, mobile apps) where bearer token theft is a concern
// DPoP proof JWT structure (sent in DPoP header with each request)// Header: { "typ": "dpop+jwt", "alg": "ES256", "jwk": { client_public_key } }// Payload: { "jti": nonce, "htm": "POST", "htu": "https://api.example.com/token", "iat": timestamp }// Signed with client private key — server verifies binding to issued token
Passkeys / WebAuthn (FIDO2) — for user-facing authentication:
Phishing-resistant: credentials are origin-bound and never transmitted
Replaces passwords and SMS OTP for high-security contexts
Major platforms (Windows, macOS, iOS, Android) support cross-device sync as of 2026
Implementation: use navigator.credentials.create() (registration) and navigator.credentials.get() (authentication)
Store only the public key and credential ID server-side (never the private key)
// WebAuthn registration (simplified)const credential = await navigator.credentials.create({
publicKey: {
challenge: serverChallenge, // random bytes from serverrp: { name: 'My App', id: 'myapp.example.com' },
user: { id: userId, name: userEmail, displayName: userName },
pubKeyCredParams: [{ alg: -7, type: 'public-key' }], // ES256authenticatorSelection: { residentKey: 'preferred', userVerification: 'required' },
},
});
// Send credential.id and credential.response to server for verification
Step 6: Security Code Review
Look for common issues:
// BAD: SQL Injectionconst query = `SELECT * FROM users WHERE id = ${userId}`;
// GOOD: Parameterized queryconst query = `SELECT * FROM users WHERE id = $1`;
await db.query(query, [userId]);
Role-based access control (RBAC) enforced server-side
API authentication: OAuth 2.1 + PKCE (not OAuth 2.0 implicit/ROPC)
DPoP sender-constraining for public clients handling sensitive data
Phishing-resistant MFA (WebAuthn preferred over SMS OTP)
Step 8: Generate Security Report
Create findings report:
## Security Assessment Report### Critical Findings1. SQL injection in /api/users endpoint
- Risk: Data breach
- Fix: Use parameterized queries
### High Findings2. Missing rate limiting on login
- Risk: Brute force attacks
- Fix: Implement rate limiting
3. OAuth 2.0 implicit grant in use (deprecated)
- Risk: Access token exposure in URL fragments / browser history
- Fix: Migrate to Authorization Code + PKCE (OAuth 2.1)
### Medium Findings4. No lockfile committed for npm dependencies
- Risk: Supply chain attack via dependency resolution drift
- Fix: Commit package-lock.json; add lockfile verification to CI
### Recommendations- Enable HTTPS everywhere; enforce HSTS
- Implement CSP headers
- Add security logging for auth events
- Migrate to OAuth 2.1 (remove implicit/ROPC grants)
- Implement passkey/WebAuthn for phishing-resistant authentication
- Run `npm audit` / `pnpm audit` in CI with failure on high/critical
</execution_process>
<best_practices>
Defense in Depth: Layer security controls; no single control is sufficient
Least Privilege: Minimal permissions for users, services, and AI agents
Fail Securely: Default to deny — especially on errors (A10:2025)
Validate Everything: Never trust input from any source, including agent memory
Keep Secrets Secret: Use secret managers; rotate regularly; never commit credentials
Supply Chain Hygiene: Lock dependencies, verify integrity, monitor for compromise
Human-in-the-Loop for Agents: Require explicit approval for irreversible agentic actions
Modern Auth Standards: OAuth 2.1 + PKCE, DPoP, and Passkeys/WebAuthn over legacy flows
</best_practices>
Review the authentication flow in src/auth/ for security issues
Example Response:
## Security Review: src/auth/### Findings#### CRITICAL: Weak Password Hashing- File: src/auth/password.js:23
- Issue: Using MD5 for password hashing
- Fix: Use bcrypt with cost factor >= 12
#### HIGH: No Rate Limiting- File: src/auth/login.js
- Issue: Login endpoint has no rate limiting
- Fix: Add rate limiting (5 attempts/minute)
#### HIGH: OAuth 2.0 Implicit Grant in Use- File: src/auth/oauth.js:45
- Issue: Using response_type=token (implicit grant, deprecated in OAuth 2.1)
- Fix: Migrate to Authorization Code flow with PKCE
#### MEDIUM: Session Not Invalidated
- File: src/auth/logout.js
- Issue: Logout doesn't invalidate server-side session
- Fix: Clear session from store on logout
### Recommendations
1. Implement bcrypt for password hashing (cost factor >= 12)
2. Add rate limiting middleware (5 req/min on /login)
3. Migrate OAuth flows to Authorization Code + PKCE (OAuth 2.1)
4. Consider passkeys/WebAuthn for phishing-resistant authentication
5. Use secure session configuration (HTTPOnly, Secure, SameSite=Strict)
</usage_example>
<usage_example>
AI Agent Security Review Request:
Review the LLM agent pipeline in src/agents/ for agentic AI security risks
Example Response:
## Agentic AI Security Review: src/agents/### ASI01 — Agent Goal Hijack (HIGH)- File: src/agents/email-processor.js
- Issue: User email content passed directly to agent system prompt without sanitization
- Fix: Sanitize email content; enforce task boundary validation in routing layer
### ASI06 — Memory & Context Poisoning (HIGH)- File: src/agents/memory-store.js:78
- Issue: Web-fetched content written to persistent memory without validation
- Fix: Validate and sanitize all external content before writing to memory; never
execute commands retrieved from memory without explicit human approval
### ASI02 — Tool Misuse (MEDIUM)- File: src/agents/tools/file-tool.js
- Issue: Agent has both read and delete file permissions; delete scope too broad
- Fix: Split into read-only and write tools; apply least privilege per agent role
### ASI10 — Rogue Agent Risk (MEDIUM)- Issue: No kill-switch or hard resource limits on agent execution
- Fix: Implement max-steps limit, timeout, and human override checkpoint for
operations affecting production data
</usage_example>
Iron Laws
NEVER approve production deployment for code handling auth, PII, or external data without a completed security review
ALWAYS run both OWASP Top 10 2025 AND ASI01-ASI10 assessments for AI/agentic systems
ALWAYS fail securely — design all error paths to deny by default, never allow
NEVER trust any input without validation, including data from internal services
ALWAYS prioritize findings by severity (CRITICAL > HIGH > MEDIUM > LOW) with specific remediation steps and code examples
Anti-Patterns
Anti-Pattern
Why It Fails
Correct Approach
Approving code without full security review
Partial reviews miss exploitable paths in auth/PII/external data flows
Complete all STRIDE + OWASP phases before approving production deployment
Using OWASP 2021 for AI/agentic systems
AI-specific threats (ASI01-ASI10) are not covered by the standard web list
Always run both OWASP Top 10 2025 and ASI01-ASI10 for any agentic component
Failing open on security errors
Error paths become exploitable bypass conditions
Design every failure mode to deny access by default
Providing vague remediation guidance
Developers cannot act without specifics
Provide exact code examples and parameterized fix patterns for every finding
Missing severity prioritization
Critical findings are buried in noise with informational findings
Triage all findings as CRITICAL > HIGH > MEDIUM > LOW before delivery
Related Skills
auth-security-expert - OAuth 2.1, JWT, and authentication-specific security patterns
Related Workflow
For comprehensive security audits requiring multi-phase threat analysis, vulnerability scanning, and remediation planning, see the corresponding workflow:
Coverage: Full OWASP Top 10 2025, OWASP Agentic AI Top 10 (ASI01-ASI10), STRIDE threat modeling, CVE database checks, automated and manual penetration testing
