owasp-security
Skill0 starsChanged 27 days agoMITView on GitHub
Reviews code for security vulnerabilities and guides secure implementation using OWASP Top 10:2025, ASVS 5.0, the OWASP Top 10 for LLM Applications (2026), and the OWASP Top 10 for Agentic Applications (2026). Use when reviewing code or a diff for security issues, implementing authentication, authorization, sessions, or cryptography, handling untrusted input, files, or URLs, hardening config, dependencies, or CI, or building LLM and AI agent features.
18 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- bepaldes/heimdall-agentword for word, first seen Nov 8, 2026
- agamm/claude-code-owaspword for word, first seen Nov 3, 2026
- ChristopherAlphonse/calphonse-skillstheir own version, first seen Nov 2, 2026
- Big-LAORE/Biblioth-que-de-skillsword for word, first seen Nov 1, 2026
- Design-of-Man/claude-skillsedited, first seen Oct 30, 2026
- hoodini/ai-agents-skillstheir own version, first seen Oct 25, 2026
Other versions18 projects use a version of this.
Word for word · 3
- agamm/claude-code-owasp★ 432100% same
- bepaldes/heimdall-agent★ 2100% same
- Big-LAORE/Biblioth-que-de-skills★ 1100% same
Edited · 1
- Design-of-Man/claude-skills★ 054% same
Wrote their own version · 14
- hoodini/ai-agents-skills★ 295same name
- georgekhananaev/claude-skills-vault★ 28same name
- KhaledSaeed18/dotclaude★ 5same name
- zebbern/termstack★ 4same name
- Makiya1202/ai-agents-skills★ 2same name
- Makiya1202/awesome-codex-computer-use★ 2same name
- ChristopherAlphonse/calphonse-skills★ 1same name
- drafael/coding-harness★ 1same name
- mmondora/claude-skills★ 1same name
- SecretJuJu/claude-code-setting★ 1same name
4 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository137 other files it gives its agents.
- skills/marketing-e-vendas/humanizer/AGENTS.mdAGENTS.md
- skills/publicar-e-banco/vercel-optimize/AGENTS.mdAGENTS.md
- skills/sites-e-design/vercel-react-best-practices/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- agent-builderSkill
- find-skillsSkill
- kit-syncSkill
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- publicar-skills-githubSkill
- skill-creatorSkill
- skill-hunterSkill
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- writing-skillsSkill
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- matematica-passo-a-passoSkill
- organizador-de-estudosSkill
- projeto-senai-desafioSkill
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- revisao-flashcardsSkill
- sympySkill
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- tutor-inglesSkill
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- minecraft-construcoesSkill
- abordagem-whatsapp-vendasSkill
- adsSkill
- ai-seoSkill
- cardapio-digitalSkill
- copywritingSkill
- croSkill
- humanizar-texto-ptSkill
- humanizerSkill
- legenda-instagram-negocioSkill
- marketing-psychologySkill
- offersSkill
- orcamento-servicosSkill
- prospeccao-local-brSkill
- schemaSkill
- seo-auditSkill
- socialSkill
- brainstormingSkill
- caveman-compressSkill
- cavemanSkill
- diagnosing-superpowersSkill
- dispatching-parallel-agentsSkill
- executing-plansSkill
- finishing-a-development-branchSkill
- investigate-firstSkill
- planning-with-filesSkill
- receiving-code-reviewSkill
- requesting-code-reviewSkill
- subagent-driven-developmentSkill
- surgical-patchSkill
- systematic-debuggingSkill
- test-driven-developmentSkill
- using-git-worktreesSkill
- using-superpowersSkill
- verification-before-completionSkill
- verify-and-stopSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 10 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 58
Is the sink reachable with that input?: Check whether validation, an allowlist, an ORM, or a framework-level control already sits between …
- Distinctive: line 88
Write every LLM and ASI ID with its risk name, e.g.
- Distinctive: line 99
If the review finds nothing exploitable, say so directly.
- Distinctive: line 169
No composition rules — permit any characters, paste, and password managers (6.2.5, 6.2.7)
- Very specific: line 172
No default accounts like root/admin/sa (6.3.2)
- Very specific: line 180
Avoid eval() and dynamic code execution (1.3.2)
- Distinctive: line 184
No sensitive data in URLs or query strings (14.2.1)
- Distinctive: line 189
No forced periodic password rotation — rotate only on compromise (6.2.10)
“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
OWASP Security
Apply these standards when writing or reviewing code. For a review, follow the workflow below.
Reference files (read the one the task needs, and only the section you need):
reference/review-checklist.md: coverage checklist for every Top 10 category, plus LLM and agent checks. Read during step 3 of a review.reference/languages.md: per-language pitfalls with unsafe/safe examples for 20+ languages. Read the section for the language under review.reference/config-and-supply-chain.md: A02 and A03 in Dockerfiles, Kubernetes, Terraform, framework config, security headers, lockfiles, and CI/CD. Read when the change touches config, IaC, dependencies, or pipelines.reference/owasp-report.md: attack vectors, mitigations, and worked examples for every Top 10:2025, ASVS 5.0, LLM Top 10, and Agentic item. About 1100 lines: jump to the section you need.
Security Review Workflow
Copy this checklist into your response and tick it off as you go:
Security Review Progress:
- [ ] Step 1: Map entry points and trust boundaries
- [ ] Step 2: Load the references this code needs
- [ ] Step 3: Sweep for candidate issues
- [ ] Step 4: Triage every candidate
- [ ] Step 5: Report findingsStep 1: Map entry points and trust boundaries. List where attacker-controlled data enters: routes and handlers, headers and cookies, uploads, webhooks, queue consumers, CLI arguments, third-party API responses, and anything an LLM reads or returns. Note where authentication and authorization are enforced; it is often centralized in middleware rather than per route.
Step 2: Load the references this code needs. The language section of languages.md;
config-and-supply-chain.md if config, IaC, dependencies, or CI changed; the LLM and Agentic
sections of owasp-report.md if the code calls a model or runs an agent.
Step 3: Sweep for candidate issues. Walk review-checklist.md for the categories the code
touches. For each candidate, trace the path from an entry point in step 1 to the sink.
Step 4: Triage every candidate with the rubric in "Before Reporting a Finding" below. Drop candidates that fail it, or downgrade them to defense-in-depth. If a candidate's reachability is unclear, go back to step 1 for that input before deciding.
Step 5: Report findings in the format below, highest severity first.
Before Reporting a Finding
A pattern match is not a vulnerability. The most common failure mode in automated security review is reporting unreachable or already-mitigated code, which buries the real findings. Confirm all four before reporting:
- Is the input actually attacker-controlled? Trace it back to a real entry point: a request parameter, header, cookie, uploaded file, webhook, queue message, or third-party API response. A value that only ever comes from a constant, an enum, or trusted internal config is not an injection source.
- Is the sink reachable with that input? Check whether validation, an allowlist, an ORM,
or a framework-level control already sits between them. Look for auth middleware
(
middleware.ts,proxy.ts, Express/Django/Rails middleware, a base controller, decorators) before flagging a route as missing authorization. Enforcement is often centralized rather than per-route. - What is the blast radius? Who can trigger it, what do they get, and does it cross a trust boundary? An SSRF reaching cloud metadata differs from one reaching localhost only.
- Can the attacker perform every step? Each step of the exploit must be possible from the attacker's position. A symlink race needs a way to create symlinks on the server; a header attack needs a client that can set that header. If a step needs a capability the code doesn't show the attacker having, the finding is "Needs verification", not High.
Report severity by exploitability, not by pattern. State the concrete path (this input reaches this sink) and say so explicitly when a finding is theoretical or defense-in-depth rather than directly exploitable. If reachability can't be determined from the code available, say that instead of asserting either way.
Reporting Format
One block per finding, highest severity first:
[SEVERITY] Title (CWE-###, OWASP A##:2025, LLM## Risk Name, ASI## Risk Name)
Location: path/to/file.ext:LINE
Path: <entry point> -> <intermediate hops> -> <sink>
Impact: who can trigger it, what they get, which trust boundary it crosses
Fix: the concrete change, with a code snippet when it isn't obvious
Confidence: Confirmed | Likely | Needs verification (say what you couldn't see)Write every LLM and ASI ID with its risk name, e.g. "LLM03 Excessive Agency". A bare LLM ID is ambiguous: the 2025 and 2026 editions use the same numbers for different risks.
| Severity | Meaning |
| Critical | Unauthenticated remote code execution, auth bypass, or mass data exposure |
| High | Authenticated exploitation crossing a trust boundary (IDOR into other tenants, SQLi behind login) |
| Medium | Needs unusual preconditions, or impact is limited to the attacker's own data |
| Low | Defense-in-depth gap with no demonstrated exploit path |
| Info | Hardening suggestion; say plainly that it is not a vulnerability |
If the review finds nothing exploitable, say so directly. Do not pad the report with Info items to look thorough; a long list is what makes real findings get ignored.
OWASP Top 10:2025
Three categories were renamed from 2021 and two are new (A03, A10). Use these names and numbers; much OWASP material online still cites the 2021 list.
| # | Category | Key Prevention |
| A01 | Broken Access Control (now includes SSRF) | Deny by default, enforce server-side, verify ownership |
| A02 | Security Misconfiguration | Harden configs, disable defaults, minimize features |
| A03 | Software Supply Chain Failures | Lock versions, verify integrity, audit dependencies |
| A04 | Cryptographic Failures | TLS 1.2+, AES-256-GCM, Argon2/bcrypt for passwords |
| A05 | Injection | Parameterized queries, input validation, safe APIs |
| A06 | Insecure Design | Threat model, rate limit, design security controls |
| A07 | Authentication Failures | MFA, check breached passwords, secure sessions |
| A08 | Software or Data Integrity Failures | Sign packages, SRI for CDN, safe serialization |
| A09 | Security Logging and Alerting Failures | Log security events, structured format, alerting |
| A10 | Mishandling of Exceptional Conditions | Fail-closed, hide internals, log with context |
OWASP Top 10 for LLM Applications (2026)
For applications that call LLMs (chatbots, RAG, copilots, agents). The 2026 edition renumbered
the list; translate 2025 IDs with the table in owasp-report.md and cite 2026 IDs only.
| # | Risk | Key Mitigation |
| LLM01 | Prompt Injection | No complete fix exists. Fence untrusted content (including images, audio, tool output), keep privileges out of the model's reach, filter outputs |
| LLM02 | Sensitive Information Disclosure | Sanitize training/RAG data, strip PII from context, restrict what the model can retrieve per user |
| LLM03 | Excessive Agency | Minimize tools and permissions, require human approval for destructive actions, scope credentials per task |
| LLM04 | Supply Chain | Verify model provenance and signatures, vet third-party model hubs, lock model + adapter versions |
| LLM05 | Data and Model Poisoning | Validate training/fine-tuning sources, anomaly-detect on data ingestion, hold-out integrity tests |
| LLM06 | Unbounded Consumption | Rate-limit per user/key, cap tokens and tool calls per request, monitor cost, set hard timeouts |
| LLM07 | Misinformation | Cite sources, surface confidence, require grounding for high-stakes answers, disclose AI provenance |
| LLM08 | Hidden Context Exposure | Assume the system prompt, tool schemas, and other hidden context are extractable: no secrets there, and no authorization or policy that relies on them staying hidden |
| LLM09 | Vector and Embedding Weaknesses | Tenant-isolate vector stores, access-control on retrieval, sign or hash chunks against indirect prompt injection |
| LLM10 | Improper Output Handling | Treat all LLM output, including generated code, as untrusted input: validate, escape, or sandbox before any sink (SQL, shell, HTML, code, tool calls) |
OWASP Top 10 for Agentic Applications (2026)
For AI agent systems that plan, call tools, or keep memory:
| Risk | Description | Mitigation |
| ASI01: Agent Goal Hijack | Prompt injection alters agent objectives | Treat tool and retrieved content as data, goal boundaries, behavioral monitoring |
| ASI02: Tool Misuse & Exploitation | Tools used in unintended ways | Least privilege, fine-grained permissions, validate I/O |
| ASI03: Identity & Privilege Abuse | Delegated trust, inherited credentials, role chain exploits | Short-lived scoped tokens, identity verification |
| ASI04: Agentic Supply Chain Vulnerabilities | Compromised plugins/MCP servers | Verify signatures, sandbox, allowlist plugins |
| ASI05: Unexpected Code Execution | Unsafe code generation/execution | Sandbox execution, static analysis, human approval |
| ASI06: Memory & Context Poisoning | Corrupted RAG/context data | Validate stored content, segment by trust level |
| ASI07: Insecure Inter-Agent Communication | Spoofing/intercepting agent-to-agent messages | Authenticate, encrypt, verify message integrity |
| ASI08: Cascading Failures | Errors propagate across systems | Circuit breakers, graceful degradation, isolation |
| ASI09: Human-Agent Trust Exploitation | Over-trust in agents leveraged to manipulate users | Label AI content, user education, verification steps |
| ASI10: Rogue Agents | Compromised agents acting maliciously | Behavior monitoring, kill switches, anomaly detection |
ASVS 5.0 Key Requirements
ASVS 5.0 (May 2025) renumbered and reorganized every chapter. 4.0 requirement IDs do not
map to 5.0 — V2.1.1 meant "password length" in 4.0 and means something else now. Cite
5.0 IDs only. Levels are defined by share of requirements, not by application category:
| Level | Share | Intent |
| L1 | ~20% | Minimum bar; deliberately small to lower the barrier to entry |
| L2 | ~50% (≈70% cumulative) | What most applications should target |
| L3 | remaining ~30% | Highest assurance |
Level 1 — the minimum bar
- Passwords at least 8 characters; 15+ strongly recommended (6.2.1)
- No composition rules — permit any characters, paste, and password managers (6.2.5, 6.2.7)
- Block at least the top 3000 common passwords (6.2.4)
- Anti-automation against credential stuffing and brute force (6.3.1)
- No default accounts like
root/admin/sa(6.3.2) - Reference session tokens from a CSPRNG with 128+ bits entropy (7.2.3)
- New session token issued on authentication and re-authentication (7.2.4)
- Session fully unusable after logout or expiry (7.4.1)
- Function-level and data-level access restricted to explicit permissions (8.2.1, 8.2.2)
- Authorization enforced at a trusted service layer the client cannot manipulate (8.3.1)
- Parameterized queries / ORM for all data access (1.2.4); parameterized OS calls (1.2.5)
- Context-appropriate output encoding for HTML, URLs, and JavaScript/JSON (1.2.1–1.2.3)
- Avoid
eval()and dynamic code execution (1.3.2) - Input validated at a trusted service layer, positive/allowlist where possible (2.2.1, 2.2.2)
- TLS 1.2+ on all external traffic, publicly trusted certificates (12.1.1, 12.2.1, 12.2.2)
- Approved ciphers and modes only — no ECB, no PKCS#1 v1.5 padding (11.3.1, 11.3.2)
- No sensitive data in URLs or query strings (14.2.1)
Level 2 — what most applications should target
- MFA, or a documented combination of single factors (6.3.3)
- Passwords checked against a breached-password set (6.2.12)
- No forced periodic password rotation — rotate only on compromise (6.2.10)
- All security logging starts here. ASVS 5.0 has no L1 logging requirements; the whole of V16 is L2+. Log authentication attempts, failed authorization, security events, and unexpected errors (16.3.1–16.3.4)
- Log entries carry when/where/who/what metadata on a synchronized clock (16.2.1, 16.2.2)
- Logs encoded against log injection, protected from modification, shipped off-box (16.4.1–16.4.3)
- Generic error message to the user; detail stays in the log (16.5.1)
Level 3 — highest assurance
ASVS 5.0 has 92 L3 requirements; they are not enumerated here. Two worth knowing because they tighten an L2 requirement rather than adding a new one:
- One factor must be hardware-based and phishing-resistant, e.g. a FIDO key (6.3.3, L3 clause)
- Log all authorization decisions, not only failures (16.3.2, L3 clause)
For an actual L3 assessment, work from the standard itself — see
reference/owasp-report.md for the chapter map.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

