Files
Anthropic-Cybersecurity-Skills/skills/continuous-llm-red-teaming-with-promptfoo/references/standards.md
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mukul975 8cae0648ec Add 55 new skills across 3 new domains + 6 undercovered areas (762 -> 817)
Demand-driven expansion targeting the fastest-growing 2025-2026 threat and
skills categories (ISC2/WEF/CrowdStrike/Mandiant signals):

- AI Security (NEW domain, 12 skills): LLM red-teaming with garak/PyRIT,
  prompt injection (direct/indirect/RAG), MCP tool-poisoning, agentic tool
  invocation, guardrails, model/data poisoning, system-prompt leakage,
  embedding/vector weaknesses, model extraction, continuous red-teaming
- Supply Chain Security (NEW domain, 5 skills): SBOMs, dependency confusion,
  malicious-npm triage, typosquatting, SLSA/Sigstore provenance
- Hardware & Firmware Security (NEW domain, 4 skills): CHIPSEC/UEFI audit,
  Secure Boot bypass, TPM measured-boot attestation, ESP bootkit hunting
- Identity (10): Entra ID/ROADtools, GraphRunner, AADInternals, ADCS/Certipy,
  shadow credentials, coercion, BloodHound CE, device-code phishing, SSO abuse
- Cloud-native (8): Stratus, Pacu, CloudFox, container escape, K8s RBAC,
  Falco, Trivy, kube-bench
- Offensive C2 (6): Sliver, Havoc, NetExec, DPAPI, NTLM relay ESC8, redirectors
- DFIR (6): Hayabusa, Chainsaw, KAPE, Velociraptor, EZ Tools, Plaso
- Backfill (4): OpenCTI, MISP, honeytokens, post-quantum crypto migration

Each skill follows the repo taxonomy (SKILL.md + references/{standards,api-reference}.md
+ scripts/agent.py + LICENSE), with researched real tool commands (no placeholders),
complete frontmatter, and ATT&CK/ATLAS + NIST CSF mappings. Updates README domain
table, skill count, and index.json.
2026-06-22 19:08:16 +02:00

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1.5 KiB
Markdown

# Standards and References — Continuous LLM Red Teaming with Promptfoo
## MITRE ATLAS Techniques
| ID | Name | Tactic | Rationale |
|----|------|--------|-----------|
| AML.T0051 | LLM Prompt Injection | LLM Attack | Core class of attack generated and regression-tested by the suite. |
| AML.T0051.000 | Direct Prompt Injection | LLM Attack | Injection delivered directly in the user prompt. |
| AML.T0051.001 | Indirect Prompt Injection | LLM Attack | Injection delivered via retrieved/external content. |
| AML.T0054 | LLM Jailbreak | LLM Attack | Jailbreak strategies (jailbreak, composite, crescendo) test guardrail bypass. |
## NIST AI RMF
| ID | Function | Rationale |
|----|----------|-----------|
| MANAGE-4.1 | Post-deployment monitoring plans are implemented; AI risks are tracked and managed | Continuous CI/CD red-teaming is the post-deployment monitoring control for LLM risk. |
## Official Resources
- Promptfoo red-team docs: https://www.promptfoo.dev/docs/red-team/
- Promptfoo configuration: https://www.promptfoo.dev/docs/red-team/configuration/
- Promptfoo CI/CD: https://www.promptfoo.dev/docs/integrations/ci-cd/
- Promptfoo GitHub: https://github.com/promptfoo/promptfoo
- DeepTeam GitHub: https://github.com/confident-ai/deepteam
- DeepTeam docs: https://www.trydeepteam.com/docs/getting-started
- OWASP Top 10 for LLM Applications: https://genai.owasp.org/
## Frameworks Tracked
- OWASP LLM Top 10 (`owasp:llm` preset)
- OWASP Agentic threats (`owasp:agentic` preset)
- MITRE ATLAS (Promptfoo ATLAS mapping)