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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.
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1.5 KiB
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:llmpreset) - OWASP Agentic threats (
owasp:agenticpreset) - MITRE ATLAS (Promptfoo ATLAS mapping)